text:
},
  pages={421--430},
  year={2013},
  organization={Wiley Online Library}
}

%This article describes new interactive techniques capable of handling a million items(effectively visible and manageable on screen).
@inproceedings{fekete2002interactive,
  title={Interactive information visualization of a million items},
  author={Fekete, Jean-Daniel and Plaisant, Catherine},
  booktitle={Information Visualization, 2002. INFOVIS 2002. IEEE Symposium on},
  pages={117--124},
  year={2002},
  organization={IEEE}
}

%This paper describes Show Me, an integrated set of user interface commands and defaults that incorporate automatic presentation into a commercial visual analysis system called Tableau.
@article{mackinlay2007show,
  title={Show me: Automatic presentation for visual analysis},
  author={Mackinlay, Jock and Hanrahan, Pat and Stolte, Chris},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={13},
  number={6},
  pages={1137--1144},
  year={2007},
  publisher={IEEE}
}

%With sampleAction we have explored whether interaction techniques to present query results running over only incremental samples can be presented as sufficiently trustworthy for analysts both to make closer to real time decisions about their queries and to be more exploratory in their questions of the data.
@inproceedings{fisher2012trust,
  title={Trust me, I'm partially right: Incremental visualization lets analysts explore large datasets faster},
  author={Fisher, Danyel and Popov, Igor and Drucker, Steven and others},
  booktitle={Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems},
  pages={1673--1682},
  year={2012},
  organization={ACM}
}

%In this paper, we present a novel analysis-guided exploration system. It leverages the collaborative effort of human comprehensibility and machine computations to facilitate users' visual exploration processes.
@inproceedings{yang2007analysis,
  title={Analysis guided visual exploration of multivariate data},
  author={Yang, Di and Rundensteiner, Elke A and Ward, Matthew O},
  booktitle={Visual Analytics Science and Technology, 2007. VAST 2007. IEEE Symposium on},
  pages={83--90},
  year={2007},
  organization={IEEE}
}

%This paper presents new interactive methods to explore multidimensional data using scatterplots. This exploration is performed using a matrix of scatterplots that gives an overview of the possible configurations, thumbnails of the scatterplots, and support for interactive navigation in the multidimensional space.
@article{elmqvist2008rolling,
  title={Rolling the dice: Multidimensional visual exploration using scatterplot matrix navigation},
  author={Elmqvist, Niklas and Dragicevic, Pierre and Fekete, Jean-Daniel},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={14},
  number={6},
  pages={1539--1148},
  year={2008},
  publisher={IEEE}
}

%The Google Public Data Explorer makes large, public-interest datasets easy to explore, visualize and communicate
@online{googledataexplorer,
  author = {Google},
  title = {Google Public Data Explorer},
  url = {http://www.google.com/publicdata.}
}

%This paper introduces a concept for automatic focusing on features within a volumetric data set.
@article{viola2006importance,
  title={Importance-driven focus of attention},
  author={Viola, Ivan and Feixas, Miquel and Sbert, Mateu and Groller, Meister Eduard},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={12},
  number={5},
  pages={933--940},
  year={2006},
  publisher={IEEE}
}

%In this paper we describe the design of N-dimensional brushes which are defined in data space rather than screen space, and show how they have been integrated into XmdvTool, a visualization package for displaying multivariate data.
@inproceedings{martin1995high,
  title={High dimensional brushing for interactive exploration of multivariate data},
  author={Martin, Allen R and Ward, Matthew O},
  booktitle={Proceedings of the 6th Conference on Visualization'95},
  pages={271},
  year={1995},
  organization={IEEE Computer Society}
}

% In this framework, query distribution estimates help users to interactively explore their query's solution and visually identify the regions where the combined behavior of constrained variables is most important, statistically, to their inquiry.
@article{gosink2011application,
  title={An application of multivariate statistical analysis for query-driven visualization},
  author={Gosink, Luke J and Garth, Christoph and Anderson, John C and Bethel, E Wes and Joy, Kenneth I},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={17},
  number={3},
  pages={264--275},
  year={2011},
  publisher={IEEE}
}

%Information theory is used to explore the interesting dataset. Specifically, the variables are classified into groups.  Information metrics is used to choose isocontours of selected variables.
@article{biswas2013information,
  title={An Information-Aware Framework for Exploring Multivariate Data Sets},
  author={Biswas, Ayan and Dutta, Soumya and Shen, Han-Wei and Woodring, Jonathan},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={12},
  pages={2683--2692},
  year={2013},
  publisher={IEEE}
}

% One such intuitive navigation paradigm is interactive route planning on a connected network. We have employed such an interface and have paired it with a prominent high-dimensional visualization paradigm showing the N-D data in undistorted raw form: parallel coordinates. A user then interactively specifies nodes/edges to visit, and the system computes an optimal route, which can be further edited and manipulated.
@inproceedings{zhang2012network,
  title={A network-based interface for the exploration of high-dimensional data spaces},
  author={Zhang, Zhiyuan and McDonnell, Kevin T and Mueller, Klaus},
  booktitle={Pacific Visualization Symposium (PacificVis), 2012 IEEE},
  pages={17--24},
  year={2012},
  organization={IEEE}
}

% In this paper, we address this challenge at its core, i.e., how to query the query space associated with a given database. The space considered is formed by conjunctive predicates. To express them, we introduce the Segmentation Description Language (SDL). The user provides a query. Charles, our query advisory system, breaks its extent into meaningful segments and returns the subsequent SDL descriptions.
@inproceedings{sellam2013meet,
  title={Meet Charles, big data query advisor},
  author={Sellam, Thibault and Kersten, Martin L},
  booktitle={CIDR},
  year={2013}
}

%Visualising large data is challenging both perceptually and computationally: it is hard to know what to display and hard to efﬁciently display it once you know what you want. This paper proposes a framework that tackles both problems, based around a four step process of bin, summarise, smooth, and visualise.
@techreport{wickham2013bin,
  title={Bin-summarise-smooth: a framework for visualising large data},
  author={Wickham, Hadley},
  year={2013},
  institution={Tech. rep., had. co. nz}
}

@article{kim2014rapid,
  title={Rapid Sampling for Visualizations with Ordering Guarantees},
  author={Kim, Albert and Blais, Eric and Parameswaran, Aditya and Indyk, Piotr and Madden, Sam and Rubinfeld, Ronitt},
  journal={arXiv preprint arXiv:1412.3040},
  year={2014}
}

scalar
@article{battle2013scalar,
  author = {Battle, Leilani and Chang, Remco and Stonebraker, Michael},
  title = {Dynamic Reduction of Query Result Sets for Interactive Visualization},
  Journal = {IEEE Big Data Visualization},
  year = {2013},
}

@article{olston1998datasplash,
  title={DataSplash},
  author={Olston, Chris and Woodruff, Allison and Aiken, Alexander and Chu, Michael and Ercegovac, Vuk and Lin, Mark and Spalding, Mybrid and Stonebraker, Michael},
  journal={ACM SIGMOD Record},
  volume={27},
  number={2},
  pages={550--552},
  year={1998},
  organization={ACM}
}

% DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentations of large tabular dataset from several sources.
@inproceedings{livny1997devise,
  title={DEVise: Integrated Querying and Visual Exploration of Large Datasets (Demo Abstract)},
  author={Livny, M and Ramakrishnan, R and Beyer, K and Chen, G and Donjerkovic, D and Lawande, S and Myllymaki, J and Wenger, K},
  booktitle={In Proceedings of ACM SIGMOD},
  year={1997},
  organization={Citeseer}
}

% This paper offers new principles for visual information seeking (VIS). A key concept is to support browsing, which is distinguished from familiar query composition and information retrieval because of its emphasis on rapid filtering to reduce result sets, progressive refinement of search parameters, continuous reformulation of goals, and visual scanning to identify results.
@inproceedings{ahlberg1994visual,
  title={Visual information seeking: tight coupling of dynamic query filters with starfield displays},
  author={Ahlberg, Christopher and Shneiderman, Ben},
  booktitle={Proceedings of the SIGCHI conference on Human factors in computing systems},
  pages={313--317},
  year={1994},
  organization={ACM}
}

% In this paper, we propose a classification of information visualization and visual data mining techniques which is based on the data type to be visualized, the visualization technique, and the interaction and distortion technique.
@article{keim2002information,
  title={Information visualization and visual data mining},
  author={Keim, Daniel A},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={8},
  number={1},
  pages={1--8},
  year={2002},
  publisher={IEEE}
}

% Ploceus supports flexible construction and transformation of networks through a direct manipulation interface, and integrates dynamic network manipulation with visual exploration for a seamless analytic experience.
@inproceedings{liu2011network,
  title={Network-based visual analysis of tabular data},
  author={Liu, Zhicheng and Navathe, Shamkant B and Stasko, John T},
  booktitle={Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on},
  pages={41--50},
  year={2011},
  organization={IEEE}
}

%This paper provides a detailed analysis of the expressive power of existing visual querying systems and describes a more flexible approach in which users can explore n-ary conjunctive inter- and intra- dimensional relationships by interactively constructing queries as visual hypergraphs.
@article{shadoan2013visual,
  title={Visual Analysis of Higher-Order Conjunctive Relationships in Multidimensional Data Using a Hypergraph Query System},
  author={Shadoan, Rachel and Weaver, Chris},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={12},
  pages={2070--2079},
  year={2013},
  publisher={IEEE}
}

%We demonstrate that engineering applications represent a challenging but very applicable area for visual analytics.
@article{konyha2006interactive,
  title={Interactive visual analysis of families of function graphs},
  author={Konyha, Zoltan and Matkovic, Kresimir and Gracanin, Denis and Jelovic, Mario and Hauser, Helwig},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={12},
  number={6},
  pages={1373--1385},
  year={2006},
  publisher={IEEE}
}

%To aid analysis of the gathered usability test data, the WebQuilt visualization provides filtering capabilities and semantic zooming, allowing the designer to understand the test results at the gestalt view of the entire graph, and then drill down to sub-paths and single pages.
@inproceedings{waterson2002did,
  title={What did they do? understanding clickstreams with the webquilt visualization system},
  author={Waterson, Sarah J and Hong, Jason I and Sohn, Tim and Landay, James A and Heer, Jeffrey and Matthews, Tara},
  booktitle={Proceedings of the Working Conference on Advanced Visual Interfaces},
  pages={94--102},
  year={2002},
  organization={ACM}
}

%We present invis, the first visual analysis tool to facilitate exploration of in vitro selection sequence spaces. invis introduces a novel configuration of coordinated views that enables simultaneous inspection of global projections of sequence data alongside local regions of selected dimensions and sequence clusters. It allows scientists to isolate related sequences for further data analysis, compare sequence populations over varying conditions, filter sequences based on their similarities, and visualize likely pathways of genetic evolution.
@inproceedings{demiralp2013invis,
  title={invis: Exploring high-dimensional RNA sequences from in vitro selection},
  author={Demiralp, Cagatay and Hayden, Eric and Hammerbacher, Jeff and Heer, Jeffrey},
  booktitle={Biological Data Visualization (BioVis), 2013 IEEE Symposium on},
  pages={1--8},
  year={2013},
  organization={IEEE}
}

%This paper discusses two issues that influence design of discovery tools: statistical algorithms vs. visual data presentation, and hypothesis testing vs. exploratory data analysis.
@inproceedings{shneiderman2001inventing,
  title={Inventing discovery tools: Combining information visualization with data mining},
  author={Shneiderman, Ben},
  booktitle={Discovery Science},
  pages={17--28},
  year={2001},
  organization={Springer}
}

%--------------------------------------------------Visual Analysis with Multiple Views-------------------------------------------%
%VisTrails is a new system that enables interactive multiple-view visualizations by simplifying the creation and maintenance of visualization pipelines, and by optimizing their execution.
@inproceedings{bavoil2005vistrails,
  title={Vistrails: Enabling interactive multiple-view visualizations},
  author={Bavoil, Louis and Callahan, Steven P and Crossno, Patricia J and Freire, Juliana and Scheidegger, Carlos E and Silva, Cl{\'a}udio T and Vo, Huy T},
  booktitle={Visualization, 2005. VIS 05. IEEE},
  pages={135--142},
  year={2005},
  organization={IEEE}
}

%We introduce PointCloudXplore (PCX), an interactive visualization tool that supports visual exploration of relationships between different genes' expression using a combination of established visualization techniques.
@article{weber2009visual,
  title={Visual exploration of three-dimensional gene expression using physical views and linked abstract views},
  author={Weber, Gunther H and Rubel, Oliver and Huang, Min-Yu and DePace, Angela H and Fowlkes, Charless C and Keranen, Soile VE and Luengo Hendriks, Cris L and Hagen, Hans and Knowles, David W and Malik, Jitendra and others},
  journal={Computational Biology and Bioinformatics, IEEE/ACM Transactions on},
  volume={6},
  number={2},
  pages={296--309},
  year={2009},
  publisher={IEEE}
}

%PointCloudXplore uses the established visualization techniques of multiple views, brushing, and linking to support the analysis of high-dimensional datasets that describe many genes' expression.
@inproceedings{rubel2006pointcloudxplore,
  title={PointCloudXplore: Visual analysis of 3D gene expression data using physical views and parallel coordinates},
  author={R{\"u}bel, Oliver and Weber, Gunther H and Ker{\"a}nen, Soile VE and Fowlkes, Charless C and Hendriks, C Luengo and Simirenko, Lisa and Shah, NY and Eisen, Michael B and Biggin, Mark D and Hagen, Hans and others},
  booktitle={Proceedings of the Eighth Joint Eurographics/IEEE VGTC conference on Visualization},
  pages={203--210},
  year={2006},
  organization={Eurographics Association}
}

%We present a systematic study of opportunities for the interactive visual analysis of multi-dimensional scientific data that is based on the integration of statistical aggregations along selected independent data dimensions in a framework of coordinated multiple views (with linking and brushing).
@inproceedings{kehrer2010brushing,
  title={Brushing moments in interactive visual analysis},
  author={Kehrer, Johannes and Filzmoser, Peter and Hauser, Helwig},
  booktitle={Computer Graphics Forum},
  volume={29},
  number={3},
  pages={813--822},
  year={2010},
  organization={Wiley Online Library}
}

%In this paper, we demonstrate the visual exploration of such movement data through the concept of interactive difference views
@inproceedings{lampe2010visual,
  title={Visual Analysis of Multivariate Movement Data using Interactive Difference Views.},
  author={Lampe, Ove Daae and Kehrer, Johannes and Hauser, Helwig},
  booktitle={VMV},
  pages={315--322},
  year={2010}
}

@article{swayne1998xgobi,
  title={XGobi: Interactive dynamic data visualization in the X Window System},
  author={Swayne, Deborah F and Cook, Dianne and Buja, Andreas},
  journal={Journal of Computational and Graphical Statistics},
  volume={7},
  number={1},
  pages={113--130},
  year={1998},
  publisher={Taylor \& Francis Group}
}

@article{ahlberg1996spotfire,
  title={Spotfire: an information exploration environment},
  author={Ahlberg, Christopher},
  journal={ACM SIGMOD Record},
  volume={25},
  number={4},
  pages={25--29},
  year={1996},
  publisher={ACM}
}

%--------------------------------Interactive Visualization Language--------------------------------------------------------------%
% Wrangler combines direct manipulation of visualized data with automatic inference of relevant transforms, enabling analysts to iteratively explore the space of applicable operations and preview their effects.
@inproceedings{kandel2011wrangler,
  title={Wrangler: Interactive visual specification of data transformation scripts},
  author={Kandel, Sean and Paepcke, Andreas and Hellerstein, Joseph and Heer, Jeffrey},
  booktitle={PART 5--------Proceedings of the 2011 annual conference on Human factors in computing systems},
  pages={3363--3372},
  year={2011},
  organization={ACM}
}

%The paper presents VIQING, an environment for expressing queries via direct manipulation of data visualizations.
@inproceedings{olsten1998viqing,
  title={VIQING: Visual interactive querying},
  author={Olsten, C and Stonebraker, Michael and Aiken, Alexander and Hellerstein, Joseph M},
  booktitle={Visual Languages, 1998. Proceedings. 1998 IEEE Symposium on},
  pages={162--169},
  year={1998},
  organization={IEEE}
}

%We investigate the design of declarative, domain-specific languages for constructing interactive visualizations.
@article{heer2010declarative,
  title={Declarative language design for interactive visualization},
  author={Heer, Jeffrey and Bostock, Michael},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={16},
  number={6},
  pages={1149--1156},
  year={2010},
  publisher={IEEE}
}

% VizDeck automatically recommends appropriate visualizations based on the statistical properties of the data and adopts a card game metaphor to help organize the recommended visualizations into interactive visual dashboard applications in seconds with zero programming.
@inproceedings{key2012vizdeck,
  title={VizDeck: self-organizing dashboards for visual analytics},
  author={Key, Alicia and Howe, Bill and Perry, Daniel and Aragon, Cecilia},
  booktitle={Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data},
  pages={681--684},
  year={2012},
  organization={ACM}
}

%In this paper, we present the case for an integrated Data Visualization Management System (DVMS) based on a declarative visualization language that fully compiles the end-to-end visualization pipeline into a set of relational algebra queries.
@inproceedings{EugeneWuVision2014,
  title={The Case for Data Visualization Management Systems},
  author={Eugene, Wu and Leilani, Battle and Samuel, R. Madden},
  booktitle={Proceedings of the 40th international conference on Very large data bases},
  pages={903--906},
  year={2014},
  organization={VLDB Endowment}
}

%We present Lyra, an interactive environment for designing customized visualizations without writing code. Using drag-and-drop interactions, designers can bind data to the properties of graphical marks to author expressive visualization designs.
@article{lyra,
 title = {Lyra: An Interactive Visualization Design Environment},
 author = {Arvind Satyanarayan AND Jeffrey Heer},
 journal = {EuroVis},
 year = {2014},
 url = {http://idl.cs.washington.edu/papers/lyra},
}

% more visage
@inproceedings{roth1996visage,
  title={Visage: a user interface environment for exploring information},
  author={Roth, Steven F and Lucas, Peter and Senn, Jeffrey A and Gomberg, Cristina C and Burks, Michael B and Stroffolino, Philip J and Kolojechick, AJ and Dunmire, Carolyn},
  booktitle={Information Visualization'96, Proceedings IEEE Symposium on},
  pages={3--12},
  year={1996},
  organization={IEEE}
}

%This paper describes Visage's Visual Query Language and visualization tools, and illustrates their application to several stages of the exploration process: creating the target dataset, data cleaning and preprocessing, data reduction and projection, and visualization of the reduced data.
@inproceedings{derthick1997interactive,
  title={An Interactive Visualization Environment for Data Exploration.},
  author={Derthick, Mark and Kolojejchick, John and Roth, Steven F},
  booktitle={KDD},
  pages={2--9},
  year={1997}
}

%----------------------------------------------------------------------------Interactive Visual Analysis of Hierachical Data---------------------------------%
%In this paper, we present an interactive visual exploration tool that facilitates exploratory analysis of data warehouses with rich hierarchical structure, such as might be stored in data cubes.
@inproceedings{stolte2002query,
  title={Query, analysis, and visualization of hierarchically structured data using Polaris},
  author={Stolte, Chris and Tang, Diane and Hanrahan, Pat},
  booktitle={Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining},
  pages={112--122},
  year={2002},
  organization={ACM}
}

%---------------------------------------------------------------------------Visual Exploration with spreadsheet interface----------------------------------%
%The needs of these two groups are addressed by the spreadsheet-like interface described in this paper.
@article{jankun2001visualization,
  title={Visualization exploration and encapsulation via a spreadsheet-like interface},
  author={Jankun-Kelly, TJ and Ma, Kwan-Liu},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={7},
  number={3},
  pages={275--287},
  year={2001},
  publisher={IEEE}
}

% add eirik's stuff
% add ted's thing
% add hadley wickham's stuff
% ed chi's thesis
% add haystack

%--------------------------------------------------------------------------Widgets & Accentuating visualization to Guide Exploration----------------------%
%This paper presents scented widgets, graphical user interface controls enhanced with embedded visualizations that facilitate navigation in information spaces.
@article{willett2007scented,
  title={Scented widgets: Improving navigation cues with embedded visualizations},
  author={Willett, Wesley and Heer, Jeffrey and Agrawala, Maneesh},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={13},
  number={6},
  pages={1129--1136},
  year={2007},
  publisher={IEEE}
}

% To support casual visualization use, we propose using social and semantic signals to guide data explorers. With ‘social’ signals we refer to aggregate use statistics of the visualization or any activity outside of the visualization that could inform its use. ‘Semantic’ signals refer to interest indications derived directly from the data.
@inproceedings{dork2013accentuating,
  title={Accentuating visualization parameters to guide exploration},
  author={D{\"o}rk, Marian and Lam, Heidi and Benjelloun, Omar},
  booktitle={CHI'13 Extended Abstracts on Human Factors in Computing Systems},
  pages={1755--1760},
  year={2013},
  organization={ACM}
}

%--------------------------------------------------------Web Data----------------------------------------------------------------%
%Interactive visual exploration of the clickstream clusters. Users can get a summary of a selected data or refine the cluster result.
@inproceedings{wei2012visual,
  title={Visual cluster exploration of web clickstream data},
  author={Wei, Jishang and Shen, Zeqian and Sundaresan, Neel and Ma, Kwan-Liu},
  booktitle={Visual Analytics Science and Technology (VAST), 2012 IEEE Conference on},
  pages={3--12},
  year={2012},
  organization={IEEE}
}

%Session Viewer is a visualization tool designed to support exploratory analysis of web session logs at the statistical-aggregate to the detailed-session analysis level.
@inproceedings{lam2007session,
  title={Session Viewer: Visual Exploratory Analysis of Web Session Logs.},
  author={Lam, Heidi and Russell, Daniel M and Tang, Diane and Munzner, Tamara},
  booktitle={IEEE VAST},
  pages={147--154},
  year={2007},
  organization={Citeseer}
}

% MieLog uses two techniques for manual log inspection tasks: information visualization and statistical analysis. Information visualization is helpful in reducing the recognition load because it provides an alternative method of interpreting textual information without reading. Statistical analysis enables the extraction of unusual log messages without domain specific knowledge.
@inproceedings{takada2002mielog,
  title={MieLog: A Highly Interactive Visual Log Browser Using Information Visualization and Statistical Analysis.},
  author={Takada, Tetsuji and Koike, Hideki},
  booktitle={LISA},
  volume={2},
  pages={133--144},
  year={2002}
}

%----------------------------------------------------------------Digital Collection & Scientific Data-----------------------------------------------------------%
%We present a systematic approach to the interactive visual analysis of heterogeneous scientific data. The data consist of two interrelated parts given on spatial grids over time (e.g., atmosphere and ocean part from a coupled climate model).
@article{kehrer2011interactive,
  title={Interactive visual analysis of heterogeneous scientific data across an interface},
  author={Kehrer, Johannes and Muigg, Philipp and Doleisch, Helmut and Hauser, Helwig},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={17},
  number={7},
  pages={934--946},
  year={2011},
  publisher={IEEE}
}

%Explore the scientific dataset by model training, efficient model summary generation, and novel parallel join techniques.
@article{okcan2013scolopax,
  title={Scolopax: exploratory analysis of scientific data},
  author={Okcan, Alper and Riedewald, Mirek and Panda, Biswanath and Fink, Daniel},
  journal={Proceedings of the VLDB Endowment},
  volume={6},
  number={12},
  pages={1298--1301},
  year={2013},
  publisher={VLDB Endowment}
}

%We propose an approach that integrates projections and aggregations of the data surfaces at different levels (one scalar aggregate per surface, a 1D profile per surface, or the surface as such).
@article{matkovic2009interactive,
  title={Interactive visual analysis of complex scientific data as families of data surfaces},
  author={Matkovic, Kresimir and Gracanin, Denis and Klarin, Borislav and Hauser, Helwig},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={15},
  number={6},
  pages={1351--1358},
  year={2009},
  publisher={IEEE}
}

% The application narrows down different kinds of information about the collection, and presents them as meaningful data views. Multiple views and analysis features can be linked or unlinked on demand to enable researchers to compare and contrast different analyses, and to identify trends..
@inproceedings{xu2011analysis,
  title={Analysis of large digital collections with interactive visualization},
  author={Xu, Weijia and Esteva, Maria and Jain, Suyog Dutt and Jain, Varun},
  booktitle={Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on},
  pages={241--250},
  year={2011},
  organization={IEEE}
}

%PhD Dissertion.
@phdthesis{kehrer2011interactive,
  title={Interactive visual analysis of multi-faceted scientific data},
  author={Kehrer, Johannes},
  year={2011},
  school={The University of Bergen}
}

%The approach is proposed as an interface for visual exploration, leading the user to discover interesting relationships between data items relying on content-based similarity between data items and their respective metadata labels.
@inproceedings{bernard2012content,
  title={Content-based layouts for exploratory metadata search in scientific research data},
  author={Bernard, J{\"u}rgen and Ruppert, Tobias and Scherer, Maximilian and Kohlhammer, J{\"o}rn and Schreck, Tobias},
  booktitle={Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries},
  pages={139--148},
  year={2012},
  organization={ACM}
}

%A novel method supporting content-based retrieval and exploratory search in repositories of multivariate research data. Our basic idea is to use feature vectors based on the goodness-of-fit of a set of regression models, to describe the data mathematically.
@inproceedings{scherer2011retrieval,
  title={Retrieval and exploratory search in multivariate research data repositories using regressional features},
  author={Scherer, Maximilian and Bernard, J{\"u}rgen and Schreck, Tobias},
  booktitle={Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries},
  pages={363--372},
  year={2011},
  organization={ACM}
}

%-----------------------------------------------------------Outlier Detection----------------------------------------------%
% In this demo proposal, we introduce an innovative outlier detection system, called SODIT, that uses localized thresholding to assist the value specification of the thresholds that reflect closely the local data distribution. In addition, easy-to-use user feedback are employed to further facilitate the determination of optimal parameter values.
@inproceedings{zhang2013sodit,
  title={SODIT: An innovative system for outlier detection using multiple localized thresholding and interactive feedback},
  author={Zhang, Ji and Wang, Hua and Tao, Xiaohui and Sun, Lili},
  booktitle={Data Engineering (ICDE), 2013 IEEE 29th International Conference on},
  pages={1364--1367},
  year={2013},
  organization={IEEE}
}

%  We present concrete cooperation between automatic algorithms, interactive algorithms and visualisation tools: the evolutionary algorithm is used to obtain optimal dimension subsets which represent the original dataset without loosing information for unsupervised mode (clustering or outlier detection).
@article{boudjeloud2012visual,
  title={Visual interactive evolutionary algorithm for high dimensional outlier detection and data clustering problems},
  author={Boudjeloud--Assala, Lydia},
  journal={International Journal of Bio-Inspired Computation},
  volume={4},
  number={1},
  pages={6--13},
  year={2012},
  publisher={Inderscience}
}

%----------------------------------------------------------------Business---------------------------------------------------%
%Interaction visualization of business ecosystems which enables the analyst to explore, discover, and understand interfirm networks.
@article{basole2013understanding,
  title={Understanding Interfirm Relationships in Business Ecosystems with Interactive Visualization},
  author={Basole, Rahul C and Clear, Trustin and Hu, Mengdie and Mehrotra, Harshit and Stasko, John},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={12},
  pages={2526--2535},
  year={2013},
  publisher={IEEE}
}

%----------------------------------------------------------------Social Network--------------------------------------------%
%MatrixExplorer provides several novel features to support the exploration of social networks with a matrix-based representation, in addition to the standard interactive filtering and clustering functions.
@article{henry2006matrixexplorer,
  title={Matrixexplorer: a dual-representation system to explore social networks},
  author={Henry, Nathalie and Fekete, Jean-Daniel},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={12},
  number={5},
  pages={677--684},
  year={2006},
  publisher={IEEE}
}

% We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures.
@article{perer2006balancing,
  title={Balancing systematic and flexible exploration of social networks},
  author={Perer, Adam and Shneiderman, Ben},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={12},
  number={5},
  pages={693--700},
  year={2006},
  publisher={IEEE}
}

%-----------------------------------------------------------------Patent-----------------------------------------------------%
%PatViz provides a visual environment allowing for interactive reintegration of insights into subsequent search iterations, thereby bridging the gap between search and analytic processes.
@article{koch2011iterative,
  title={Iterative integration of visual insights during scalable patent search and analysis},
  author={Koch, Steffen and Bosch, Harald and Giereth, Mark and Ertl, Thomas},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={17},
  number={5},
  pages={557--569},
  year={2011},
  publisher={IEEE}
}

%----------------------------------------------------------------Human Motion Data---------------------------------------%
%Exploratory search and analysis of human motion data. The data is aggregated into hierarchies.
@article{bernard2013motionexplorer,
  title={MotionExplorer: Exploratory search in human motion capture data based on hierarchical aggregation},
  author={Bernard, Jurgen and Wilhelm, Nils and Kruger, Bjorn and May, Thorsten and Schreck, Tobias and Kohlhammer, Jorn},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={12},
  pages={2257--2266},
  year={2013},
  publisher={IEEE}
}

%----------------------------------------------------------------Survey & Tutorial & Book & Vision------------------------------------------------------%
%A book talks about the exploratory analysis.
@Book{ExploratoryBook,
 author= {N. Andrienko and G. Andrienko},
 title={Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach},
 publisher={Springer},
 year= {2006}
}

%This article presents this new agenda for direct manipulation for visual analytics of big data.
@article{endert2013beyond,
  title={Beyond control panels: Direct manipulation for visual analytics},
  author={Endert, Alex and Bradel, Lauren and North, Chris},
  journal={Computer Graphics and Applications, IEEE},
  volume={33},
  number={4},
  pages={6--13},
  year={2013},
  publisher={IEEE}
}

%We present the challenges and opportunities in building next-generation visual analytics services.
@article{morton2014support,
  title={Support the Data Enthusiast: Challenges for Next-Generation Data-Analysis Systems},
  author={Morton, Kristi and Balazinska, Magdalena and Grossman, Dan and Mackinlay, Jock},
  journal={Proceedings of the VLDB Endowment},
  volume={7},
  number={6},
  year={2014}
}

%In this paper, we argue for Advanced Visual Analytics Interfaces (AVAIs), visual interfaces in which neither the analytics nor the visualization needs to be advanced in itself but where the synergy between automation and visualization is in fact advanced. We offer a detailed argumentation around the needs and challenges of AVAIs and provide several examples of this type of interfaces.
@inproceedings{keim2010advanced,
  title={Advanced visual analytics interfaces},
  author={Keim, Daniel A and Bak, Peter and Bertini, Enrico and Oelke, Daniela and Spretke, David and Ziegler, Hartmut},
  booktitle={Proceedings of the International Conference on Advanced Visual Interfaces},
  pages={3--10},
  year={2010},
  organization={ACM}
}

@book{hartwig1979exploratory,
  title={Exploratory data analysis},
  author={Hartwig, Frederick},
  year={1979},
  publisher={Sage}
}

%In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data.
@article{bertini2011quality,
  title={Quality metrics in high-dimensional data visualization: an overview and systematization},
  author={Bertini, Enrico and Tatu, Andrada and Keim, Daniel},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={17},
  number={12},
  pages={2203--2212},
  year={2011},
  publisher={IEEE}
}

%This paper provides the "state of the art' of coordinated and multiple views, it describes areas that should be developed further and looks at what the future may hold for coordinated and multiple views.
@inproceedings{roberts2007state,
  title={State of the art: Coordinated \& multiple views in exploratory visualization},
  author={Roberts, Jonathan C},
  booktitle={Coordinated and Multiple Views in Exploratory Visualization, 2007. CMV'07. Fifth International Conference on},
  pages={61--71},
  year={2007},
  organization={IEEE}
}

%The goal of the tutorial is to provide an overview of visualization and interaction techniques that directly address specific data mining tasks.
@book{ankerst2001visual,
  title={Visual data mining},
  author={Ankerst, Mihael},
  year={2001},
  publisher={Dissertation. de}
}

%The aim of this work is to survey and reflect on the various ways visualization and data mining can be integrated to achieve effective knowledge discovery by involving the best of human and machine capabilities.
@article{bertini2010investigating,
  title={Investigating and reflecting on the integration of automatic data analysis and visualization in knowledge discovery},
  author={Bertini, Enrico and Lalanne, Denis},
  journal={ACM SIGKDD Explorations Newsletter},
  volume={11},
  number={2},
  pages={9--18},
  year={2010},
  publisher={ACM}
}

%We present a series of published and ongoing projects, on developing interactive visualizations for document exploration using statistical topic models.
@article{chuangdocument,
  title={Document Exploration with Topic Modeling: Designing Interactive Visualizations to Support Effective Analysis Workflows},
  author={Chuang, Jason and Hu, Yuening and Jin, Ashley and Wilkerson, John D and McFarland, Daniel A and Manning, Christopher D and Heer, Jeffrey}
}

%New user interfaces can transform how we work with big data, and raise exciting research problems that span human-computer interaction, machine learning, and distributed systems.
@article{heerkandel2012interactive,
  title={Interactive analysis of big data},
  author={Heer, Jeffrey and Kandel, Sean},
  journal={XRDS: Crossroads, The ACM Magazine for Students},
  volume={19},
  number={1},
  pages={50--54},
  year={2012},
  publisher={ACM}
}

%A taxonomy of tools that support the fluent and flexible use of visualizations.
@article{heer2012interactive,
  title={Interactive dynamics for visual analysis},
  author={Heer, Jeffrey and Shneiderman, Ben},
  journal={Queue},
  volume={10},
  number={2},
  pages={30},
  year={2012},
  publisher={ACM}
}

% A survey on interactive visual analysis in engineering.
@article{konyha2009interactive,
  title={Interactive visual analysis in engineering: A survey},
  author={Konyha, Zolt{\'a}n and Matkovic, Kre{\v{s}}imir and Hauser, Helwig},
  journal={Posters at SCCG},
  pages={31--38},
  year={2009}
}

%A survey on different uses of graphical mapping and interaction techniques for visual data mining of large data.
@article{de2003visual,
  title={From visual data exploration to visual data mining: A survey},
  author={De Oliveira, Maria Cristina Ferreira and Levkowitz, Haim},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={9},
  number={3},
  pages={378--394},
  year={2003},
  publisher={IEEE}
}

%In this survey, we study existing methods for visualization and interactive visual analysis of multifaceted scientific data.
@article{kehrer2013visualization,
  title={Visualization and visual analysis of multifaceted scientific data: A survey},
  author={Kehrer, Johannes and Hauser, Helwig},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={3},
  pages={495--513},
  year={2013},
  publisher={IEEE}
}

%A survey on the use of relevance feedback for information access systems. We study both automatic techniques, in which the system modifies the user's query, and interactive techniques, in which the user has control over query modification.
@article{ruthven2003survey,
  title={A survey on the use of relevance feedback for information access systems},
  author={Ruthven, Ian and Lalmas, Mounia},
  journal={The Knowledge Engineering Review},
  volume={18},
  number={02},
  pages={95--145},
  year={2003},
  publisher={Cambridge Univ Press}
}

%--------------------------------------------------------------Interactive Cluster Analysis----------------------------------------------------------%
% In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information.
@article{cao2011dicon,
  title={Dicon: Interactive visual analysis of multidimensional clusters},
  author={Cao, Nan and Gotz, David and Sun, Jimeng and Qu, Huamin},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={17},
  number={12},
  pages={2581--2590},
  year={2011},
  publisher={IEEE}
}

%The proposed approach involves building a hierachical  spatial cluster structure within the high-dimensional feature space, and using this combined space for discovering multi-dimensional patters with efficient computational clustering methods and highly interactive visualization.
@article{guo2003iceage,
  title={ICEAGE: Interactive clustering and exploration of large and high-dimensional geodata},
  author={Guo, Diansheng and Peuquet, Donna J and Gahegan, Mark},
  journal={GeoInformatica},
  volume={7},
  number={3},
  pages={229--253},
  year={2003},
  publisher={Springer}
}

%The framework implements the general Visual Analytics idea to effectively combine automatic data analysis with human expert supervision. It provides simple, yet effective facilities for visually monitoring and interactively controlling the trajectory clustering process at arbitrary levels of detail.
@article{schreck2009visual,
  title={Visual cluster analysis of trajectory data with interactive kohonen maps},
  author={Schreck, Tobias and Bernard, J{\"u}rgen and Von Landesberger, Tatiana and Kohlhammer, J{\"o}rn},
  journal={Information Visualization},
  volume={8},
  number={1},
  pages={14--29},
  year={2009},
  publisher={SAGE Publications}
}

%We propose visualization and interaction methods for analyzing individual clusters as well as cluster distribution within and across levels in the cluster hierarchy.
@inproceedings{van2009multiclustertree,
  title={MultiClusterTree: interactive visual exploration of hierarchical clusters in multidimensional multivariate data},
  author={Van Long, Tran and Linsen, Lars},
  booktitle={Computer Graphics Forum},
  volume={28},
  number={3},
  pages={823--830},
  year={2009},
  organization={Wiley Online Library}
}

%Hierarchical Clustering Explorer integrates four interactive features to provide information visualization techniques that allow users to control the processes and interact with the results.
@article{seo2002interactively,
  title={Interactively exploring hierarchical clustering results [gene identification]},
  author={Seo, Jinwook and Shneiderman, Ben},
  journal={Computer},
  volume={35},
  number={7},
  pages={80--86},
  year={2002},
  publisher={IEEE}
}

%In this paper, we present two novel and interactive visualization techniques that enable users to explore and interpret the structural changes of temporal clusters.
@inproceedings{turkay2011interactive,
  title={Interactive visual analysis of temporal cluster structures},
  author={Turkay, Cagatay and Parulek, J{\'u}lius and Reuter, Nathalie and Hauser, Helwig},
  booktitle={Computer Graphics Forum},
  volume={30},
  number={3},
  pages={711--720},
  year={2011},
  organization={Wiley Online Library}
}

%Visual analytics for spatial clustering. A heuristic method is used to guide users to explore the interesting clusters. Users can view the hierarchy levels during exploration.
@article{packer2013visual,
  title={Visual Analytics for Spatial Clustering: Using a Heuristic Approach for Guided Exploration},
  author={Packer, Eli and Bak, Peter and Nikkila, Mikko and Polishchuk, Valentin and Ship, Harold J},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={12},
  pages={2179--2188},
  year={2013},
  publisher={IEEE}
}

%------------------------------------------------------------Time-Series Data----------------------------------------------------------%
%We address the problem of visualizing large time-related data sets which are difficult to visualize effectively with standard techniques given the limitations of current display devices
@inproceedings{hao2007multi,
  title={Multi-resolution techniques for visual exploration of large time-series data},
  author={Hao, Ming C and Dayal, Umeshwar and Keim, Daniel A and Schreck, Tobias},
  booktitle={EuroVis},
  pages={27--34},
  year={2007}
}

% In this paper we present a novel approach to time-series data visualization, namely creating multivariate data records out of short subsequences of the data and then using multivariate visualization methods to display and explore the data in the resulting shape space.
@inproceedings{ward2011visual,
  title={Visual Exploration of Time-Series Data with Shape Space Projections},
  author={Ward, Matthew O and Guo, Zhenyu},
  booktitle={Computer Graphics Forum},
  volume={30},
  number={3},
  pages={701--710},
  year={2011},
  organization={Wiley Online Library}
}

% In this paper, we propose a method to explore data at different temporal resolutions to discover and highlight data based upon time-varying trends.
@article{woodring2009multiscale,
  title={Multiscale time activity data exploration via temporal clustering visualization spreadsheet},
  author={Woodring, Jonathan and Shen, Han-Wei},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={15},
  number={1},
  pages={123--137},
  year={2009},
  publisher={IEEE}
}

%In this paper, we present ATLAS, a visualization tool for temporal data that addresses these issues using a combination of high performance database technology, predictive caching, and level of detail management.
@inproceedings{chan2008maintaining,
  title={Maintaining interactivity while exploring massive time series},
  author={Chan, Sye-Min and Xiao, Ling and Gerth, John and Hanrahan, Pat},
  booktitle={Visual Analytics Science and Technology, 2008. VAST'08. IEEE Symposium on},
  pages={59--66},
  year={2008},
  organization={IEEE}
}

%We contribute a two-dimensional color coding scheme for inter-/intra-asset analysis that extends the two paradigms and supports the discovery of significant characteristics of assets.
@inproceedings{ziegler2007visual,
  title={Visual exploration and discovery of atypical behavior in financial time series data using two-dimensional colormaps},
  author={Ziegler, Hartmut and Nietzschmann, Tilo and Keim, Daniel A},
  booktitle={Information Visualization, 2007. IV'07. 11th International Conference},
  pages={308--315},
  year={2007},
  organization={IEEE}
}

%A visualization system that supports the analysis of large collections of system management time-series data consisting of hundreds of parameters across thousands of network devices.
@inproceedings{mclachlan2008liverac,
  title={LiveRAC: interactive visual exploration of system management time-series data},
  author={McLachlan, Peter and Munzner, Tamara and Koutsofios, Eleftherios and North, Stephen},
  booktitle={Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
  pages={1483--1492},
  year={2008},
  organization={ACM}
}

%---------------------------------------------------------------------------Spatio-Temporal Data-------------------------------%
%We show that this model is able to express a wide range of spatio-temporal queries, and it is also flexible in that not only can queries be composed but also different aggregations and visual representations can be applied, allowing users to explore and compare results. We have built a scalable system that implements this model which supports interactive response times; makes use of an adaptive level-of-detail rendering strategy to generate clutter-free visualization for large results; and shows hidden details to the users in a summary through the use of overlay heat maps.
@article{ferreira2013visual,
  title={Visual exploration of big spatio-temporal urban data: A study of new york city taxi trips},
  author={Ferreira, Nivan and Poco, Jorge and Vo, Huy T and Freire, Juliana and Silva, Cl{\'a}udio T},
  journal={EuroVis},
  year={2013},
}

%--------------------------------------------------Query Refinement on Cardinality Constraints------------------------------------%
%we present SAUNA, a server-side query relaxation algorithm that, given the user's initial range query and a desired cardinality for the answer set, produces a relaxed query that is expected to contain the required number of answers. The algorithm incorporates a range-query-specific distance metric that is weighted to produce relaxed queries of a desired shape (e.g. aspect ratio preserving), and utilizes multi-dimensional histograms for query size estimation.
@article{kadlag2003supporting,
  title={Supporting Exploratory Queries in Database Centric Web Applications},
  author={Kadlag, Abhijit and Wanjari, Amol and Freire, Juliana and Haritsa, Jayant R},
  journal={arXiv preprint cs/0310035},
  year={2003}
}

% We investigate the problem of refining SQL queries to satisfy cardinality constraints on the query result. We introduce an interactive model of refinement that incorporates user feedback to best capture user preferences. Our techniques are designed to handle queries having range and equality predicates on numerical and categorical attributes.
@inproceedings{mishra2009interactive,
  title={Interactive query refinement},
  author={Mishra, Chaitanya and Koudas, Nick},
  booktitle={Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology},
  pages={862--873},
  year={2009},
  organization={ACM}
}

%SAQR aims to balance the tradeoff between satisfying the cardinality and similarity constraints imposed on the refined query so that to maximize its overall benefit to the user. To achieve that goal, SAQR implements efficient strategies to minimize the costs incurred in exploring the available search space. In particular, SAQR utilizes both similarity-based and cardinality-based pruning techniques to bound the search space and quickly find a refined query that meets the user expectations.
@inproceedings{albarrak2014saqr,
  title={SAQR: An Efficient Scheme for Similarity-Aware Query Refinement},
  author={Albarrak, Abdullah and Sharaf, Mohamed A and Zhou, Xiaofang},
  booktitle={Database Systems for Advanced Applications},
  pages={110--125},
  year={2014},
  organization={Springer}
}

% In this demonstration, we present QRelX a novel framework to automatically generate alternate queries that meet the cardinality and closeness criteria.
@inproceedings{vartak2010qrelx,
  title={QRelX: generating meaningful queries that provide cardinality assurance},
  author={Vartak, Manasi and Raghavan, Venkatesh and Rundensteiner, Elke A},
  booktitle={Proceedings of the 2010 ACM SIGMOD International Conference on Management of data},
  pages={1215--1218},
  year={2010},
  organization={ACM}
}

%--------------------------------------------------Query Refinement based on Probabilistic Method------------------------------%
% To recover from input errors, we introduce the notion of sensitivity and propose efficient algorithms for identifying the most sensitive user input, i.e., those inputs that had the greatest influence on the query results. For the third challenge, we develop techniques that can deliver estimates of the required probabilities within a given hard realtime limit and are able to adapt automatically as the interactive query refinement proceeds.
@inproceedings{qarabaqi2014user,
  title={User-driven refinement of imprecise queries},
  author={Qarabaqi, Bahar and Riedewald, Mirek},
  booktitle={Data Engineering (ICDE), 2014 IEEE 30th International Conference on},
  pages={916--927},
  year={2014},
  organization={IEEE}
}

% Our proposed approach for suggesting query relaxations is driven by a novel probabilistic framework based on optimizing a wide variety of application-dependent objective functions
@article{mottin2013probabilistic,
  title={A probabilistic optimization framework for the empty-answer problem},
  author={Mottin, Davide and Marascu, Alice and Roy, Senjuti Basu and Das, Gautam and Palpanas, Themis and Velegrakis, Yannis},
  journal={Proceedings of the VLDB Endowment},
  volume={6},
  number={14},
  pages={1762--1773},
  year={2013},
  publisher={VLDB Endowment}
}

% The relaxation suggestions hinge on a probabilistic framework that takes into account the probability of the user accepting a suggested relaxation, as well as how much that relaxation serves towards the optimization objective.
@article{mottin2014iqr,
  title={IQR: An Interactive Query Relaxation System for the Empty-Answer Problem},
  author={Mottin, Davide and Marascu, Alice and Roy, Senjuti Basu and Das, Gautam and Palpanas, Themis and Velegrakis, Yannis},
  booktitle={Proceedings of the 2013 international conference on Management of data},
  year={2014},
  organization={ACM}
}

%--------------------------------------------------Data Exploration based on Faceted Search-----------------------------------------------%
%Our proposed techniques dynamically suggest facets for drilling down into the database such that the cost of navigation is minimized. At every step, the system asks the user a question or a set of questions on different facets and depending on the user response, dynamically fetches the next most promising set of facets, and the process repeats.
@inproceedings{basu2008minimum,
  title={Minimum-effort driven dynamic faceted search in structured databases},
  author={Basu Roy, Senjuti and Wang, Haidong and Das, Gautam and Nambiar, Ullas and Mohania, Mukesh},
  booktitle={Proceedings of the 17th ACM conference on Information and knowledge management},
  pages={13--22},
  year={2008},
  organization={ACM}
}

%We present the FACeTOR system that proposes a cost-based approach to faceted navigation. At each step of the navigation, the user is presented with a subset of all possible facet conditions that are selected such that the overall expected navigation cost is minimized and every result is guaranteed to be reachable by a facet condition.
@inproceedings{kashyap2010facetor,
  title={Facetor: cost-driven exploration of faceted query results},
  author={Kashyap, Abhijith and Hristidis, Vagelis and Petropoulos, Michalis},
  booktitle={Proceedings of the 19th ACM international conference on Information and knowledge management},
  pages={719--728},
  year={2010},
  organization={ACM}
}

%---------------------------------------------------Query Relaxation based on Hierarchy--------------------------------------------------%
%In this paper, we consider possible expansions of the query context produced by relaxing one or more of its context attributes. A hierarchical attribute may be relaxed upwards by replacing its value by a more general one, downwards by replacing its value by a set of more specific values or sideways by replacing its value by sibling values in the hierarchy.
@inproceedings{stefanidis2007relaxing,
  title={On relaxing contextual preference queries},
  author={Stefanidis, Kostas and Pitoura, Evaggelia and Vassiliadis, Panos},
  booktitle={2013 IEEE 14th International Conference on Mobile Data Management},
  pages={289--293},
  year={2007},
  organization={Conference and Custom Publishing}
}

% In this paper, we present the BioNav system, a novel search interface that enables the user to navigate large number of query results by organizing them using the MeSH concept hierarchy.
@article{kashyap2011effective,
  title={Effective navigation of query results based on concept hierarchies},
  author={Kashyap, Abhijith and Hristidis, Vagelis and Petropoulos, Michalis and Tavoulari, Sotiria},
  journal={Knowledge and Data Engineering, IEEE Transactions on},
  volume={23},
  number={4},
  pages={540--553},
  year={2011},
  publisher={IEEE}
}

%In this paper, we present the BioNav system, a novel search interface that enables the user to navigate large number of query results by organizing them using the MeSH concept hierarchy.
@inproceedings{kashyap2009bionav,
  title={BioNav: Effective Navigation on Query Results of Biomedical Databases},
  author={Kashyap, Abhijith and Hristidis, Vagelis and Petropoulos, Michalis and Tavoulari, Sotiria},
  booktitle={Data Engineering, 2009. ICDE'09. IEEE 25th International Conference on},
  pages={1287--1290},
  year={2009},
  organization={IEEE}
}

%This paper presents a data abstraction approach to facilitate the development of such a fault-tolerant and intelligent query processing system. It specifically proposes a knowledge abstraction database that adopts a multilevel knowledge representation scheme called the knowledge abstraction hierarchy.
@article{huh2000data,
  title={A data abstraction approach for query relaxation},
  author={Huh, S-Y and Moon, K-H and Lee, Heeseok},
  journal={Information and Software Technology},
  volume={42},
  number={6},
  pages={407--418},
  year={2000},
  publisher={Elsevier}
}

%--------------------------------------------------Query Refinement & Relaxation & Steering Others--------------------------------------%
% This chapter proposes two new algorithms for query relaxation.  The first algorithm addresses the problem of response times for computing user-optimal relaxations in interactive recommendation sessions. The proposed algorithm is based on a combination of different techniques like partial evaluation of subqueries, precomputation of query results and compact in-memory data structures. The second algorithm is an improvement of previous approaches to mixed-initiative failure recovery: Instead of computing all minimal ‘conflicts’ within the user requirements in advance – as suggested in previous algorithms – we propose to determine preferred conflicts ‘on demand’ and use a recent, general-purpose and fast conflict detection algorithm for this task
@incollection{jannach2008finding,
  title={Finding preferred query relaxations in content-based recommenders},
  author={Jannach, Dietmar},
  booktitle={Intelligent Techniques and Tools for Novel System Architectures},
  pages={81--97},
  year={2008},
  publisher={Springer}
}

%Query relaxation for xml model
@phdthesis{lee2002query,
  title={Query relaxation for xml model},
  author={Lee, Dongwon},
  year={2002},
  school={University of California Los Angeles}
}

%. In this paper, we propose a novel query relaxation scheme that enables users to ﬁnd best matching information by exploiting malleable schemas to eﬀectively query vaguely structured information.
@inproceedings{zhou2007query,
  title={Query relaxation using malleable schemas},
  author={Zhou, Xuan and Gaugaz, Julien and Balke, Wolf-Tilo and Nejdl, Wolfgang},
  booktitle={Proceedings of the 2007 ACM SIGMOD international conference on Management of data},
  pages={545--556},
  year={2007},
  organization={ACM}
}

%In this paper, we describe new techniques for the fast computation of ‘user-optimal’ query relaxations.First, we show how the number of required database queries for determining an optimal relaxation can be limited to the number of given subqueries by evaluating the subqueries individually. Next, it is described how the problem of finding relaxations returning ‘at-least-n’ products can be efficiently solved by analyzing these partial query results in memory. Finally, we show how a general-purpose conflict detection algorithm can be applied for determining ‘preferred’ conflicts in interactive relaxation scenarios.
@incollection{jannach2007techniques,
  title={Techniques for fast query relaxation in content-based recommender systems},
  author={Jannach, Dietmar},
  booktitle={KI 2006: Advances in Artificial Intelligence},
  pages={49--63},
  year={2007},
  publisher={Springer}
}

%In this paper, we show how the task of finding adequate or customer optimal relaxations for a given recommendation problem can be efficiently achieved by applying techniques from the field of model-based diagnosis.
@incollection{jannach2006conflict,
  title={Conflict-directed relaxation of constraints in content-based recommender systems},
  author={Jannach, Dietmar and Liegl, Johannes},
  booktitle={Advances in Applied Artificial Intelligence},
  pages={819--829},
  year={2006},
  publisher={Springer}
}

%A user of an interactive application, however, desires explanations and relaxations containing the most important constraints.
@inproceedings{junker2004quickxplain,
  title={QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems},
  author={Junker, Ulrich},
  booktitle={AAAI},
  volume={4},
  pages={167--172},
  year={2004}
}

% In this paper, we propose a framework to systematically relax queries involving joins and selections. We first characterize the types of answers that we return to relaxed queries. We then propose a lattice based framework in order to aid query relaxation. Nodes in the lattice correspond to different ways to relax queries. We characterize the properties of relaxation at each node and present algorithms to compute the corresponding answer. We then discuss how to traverse this lattice in a way that a non-empty query answer is obtained with the minimum amount of query condition relaxation.
@inproceedings{koudas2006relaxing,
  title={Relaxing join and selection queries},
  author={Koudas, Nick and Li, Chen and Tung, Anthony KH and Vernica, Rares},
  booktitle={Proceedings of the 32nd international conference on Very large data bases},
  pages={199--210},
  year={2006},
  organization={VLDB Endowment}
}

%This paper proposes a two-step solution to address the diversity issue of user preferences for the categorization approach. The proposed solution does not require explicit user involvement. The first step analyzes query history of all users in the system offline and generates a set of clusters over the data, each corresponding to one type of user preferences. When user asks a query, the second step presents to the user a navigational tree over clusters generated in the first step such that the user can easily select the subset of clusters matching his needs.
@inproceedings{chen2007addressing,
  title={Addressing diverse user preferences in SQL-query-result navigation},
  author={Chen, Zhiyuan and Li, Tao},
  booktitle={Proceedings of the 2007 ACM SIGMOD international conference on Management of data},
  pages={641--652},
  year={2007},
  organization={ACM}
}

%  We present direct manipulation techniques that couple declarative selection queries with a query relaxation engine that enables users to interactively generalize their selections. We apply our selection techniques in both information visualization and graphics editing applications, enabling generalized selection over both static and dynamic interface objects.
@inproceedings{heer2008generalized,
  title={Generalized selection via interactive query relaxation},
  author={Heer, Jeffrey and Agrawala, Maneesh and Willett, Wesley},
  booktitle={Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
  pages={959--968},
  year={2008},
  organization={ACM}
}

%The methods to control and restrict the relaxation process introduced in this paper focus the relaxation process and make it more efficient. User restrictions over the database domain may be expressed as user constraints. This paper describes how user constraints can restrict relaxed queries.
@inproceedings{gaasterland1993restricting,
  title={Restricting query relaxation through user constraints},
  author={Gaasterland, Terry},
  booktitle={Intelligent and Cooperative Information Systems, 1993., Proceedings of International Conference on},
  pages={359--366},
  year={1993},
  organization={IEEE}
}

%We introduce a novel algorithm, loqr, which is designed to relax queries that are in the disjunctive normal form and contain a mixture of discrete and continuous attributes. loqr discovers the implicit relationships that exist among the various domain attributes and then uses this knowledge to relax the constraints from the failing query.
@inproceedings{muslea2004machine,
  title={Machine learning for online query relaxation},
  author={Muslea, Ion},
  booktitle={Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining},
  pages={246--255},
  year={2004},
  organization={ACM}
}

%We propose database systems be augmented with an automated “database navigator” (DBNav) service that assists as a “tour guide” to facilitate Interative Data Explorer. We sketch a general data navigation framework and discuss some specific components and approaches that we believe belong to any such system.
@inproceedings{cetintemel2013query,
  title={Query Steering for Interactive Data Exploration},
  author={Cetintemel, Ugur and Cherniack, Mitch and DeBrabant, Justin and Diao, Yanlei and Dimitriadou, Kyriaki and Kalinin, Alexander and Papaemmanouil, Olga and Zdonik, Stanley B},
  booktitle={CIDR},
  year={2013}
}

%To assist users in this context, we draw inspiration from Web recommender systems and propose the use of personalized query recommendations. The idea is to track the querying behavior of each user, identify which parts of the database may be of interest for the corresponding data analysis task, and recommend queries that retrieve relevant data.
@inproceedings{chatzopoulou2009query,
  title={Query recommendations for interactive database exploration},
  author={Chatzopoulou, Gloria and Eirinaki, Magdalini and Polyzotis, Neoklis},
  booktitle={Scientific and Statistical Database Management},
  pages={3--18},
  year={2009},
  organization={Springer}
}

% The aim of this work is to capture this iterative process by extending the query model. Extended queries, which express additional constraints on the answer set and designate some of the conditions in the relational query as flexible, are defined. The query modification operators modify flexible constraints to satisfy an extended query. The query modification operation, generalization, is described.
@inproceedings{chaudhuri1990generalization,
  title={Generalization and a framework for query modification},
  author={Chaudhuri, Surajit},
  booktitle={Data Engineering, 1990. Proceedings. Sixth International Conference on},
  pages={138--145},
  year={1990},
  organization={IEEE}
}

% In this paper, we propose assisting users in database exploration by recommending to them additional items, called Ymal (“You May Also Like”) results. Such items are computed based on the most interesting sets of attribute values, called faSets, that appear in the result of the original query. The interestingness of a faSet is defined based on its frequency in the query result and in the database.
@article{drosou2013ymaldb,
  title={YmalDB: exploring relational databases via result-driven recommendations},
  author={Drosou, Marina and Pitoura, Evaggelia},
  journal={The VLDB Journal},
  volume={22},
  number={6},
  pages={849--874},
  year={2013},
  publisher={Springer}
}

%We envision that next generation database systems should interpret queries by their intent, rather than as a contract carved in stone for complete and correct answers. The result set should aid the user in understanding the database’s content and provide guidance to continue the data exploration journey.
@article{kersten2011researcher,
  title={The researcher’s guide to the data deluge: Querying a scientific database in just a few seconds},
  author={Kersten, Martin L and Idreos, Stratos and Manegold, Stefan and Liarou, Erietta},
  journal={PVLDB Challenges and Visions},
  year={2011}
}

%  In particular, we propose that, along with the results of each query, the user gets additional recommended results that we call “You May Also Like ” or Ymal results. We discuss a suite of different approaches to computing Ymal results and exploit one that uses only the database content and the query results.
@article{stefanidis2009you,
  title={You May Also Like” results in relational databases},
  author={Stefanidis, Kostas and Drosou, Marina and Pitoura, Evaggelia},
  journal={Proc. PersDB, Lyon, France},
  year={2009},
  publisher={Citeseer}
}

%The second major research area is how to interactively improve the query through user interaction (query refinement). We address this problem by extending some information retrieval and machine learning techniques to affect the interpretation of similarity predicates and the query search condition itself. The result is a new query that better satisfies the users information need.
@article{ortega2002integrating,
  title={Integrating similarity based retrieval and query refinement in databases},
  author={Ortega-Binderberger, Michael},
  year={2002},
  publisher={University of Illinois at Urbana-Champaign}
}

%--------------------------------------------------------------Query Steering based on Users' Feedback-----------------------------------------------%
%The feedback in our framework consists of both unexpected tuples currently present in the query output and expected tuples that are missing from the query output.
@article{islam2013framework,
  title={A framework for query refinement with user feedback},
  author={Islam, Md Saiful and Liu, Chengfei and Zhou, Rui},
  journal={Journal of Systems and Software},
  volume={86},
  number={6},
  pages={1580--1595},
  year={2013},
  publisher={Elsevier}
}

%Our system asks users for their relevance feedback on strategically collected samples in an interactive manner, steers them towards the interesting parts of the database and eventually formulates the query that retrieves their data of interest.
@inproceedings{dimitriadou2014automatic,
  title={Automatic user steering for interactive data exploration},
  author={Dimitriadou, Kyriaki},
  booktitle={Data Engineering Workshops (ICDEW), 2014 IEEE 30th International Conference on},
  pages={320--324},
  year={2014},
  organization={IEEE}
}

%Our approach relies on user relevance feedback on data samples to model user interests and strategically collects more samples to refine the model while minimizing the user effort. The system leverages decision tree classifiers to generate an effective user model that balances the trade-off between identifying all relevant objects and reducing the size of final returned objects.
@inproceedings{dimitriadou2014interactive,
  title={Interactive data exploration based on user relevance feedback},
  author={Dimitriadou, Kyriaki and Papaemmanouil, Olga and Diao, Yanlei},
  booktitle={Data Engineering Workshops (ICDEW), 2014 IEEE 30th International Conference on},
  pages={292--295},
  year={2014},
  organization={IEEE}
}

%Query refinement has several motivations. First, the `starting' query may only partially capture the user's information need. The user may find better examples among the answers returned to the starting query which then become the basis of the `refined' query. Second, multimedia objects are represented as a collection of features.
@inproceedings{chakrabarti2000efficient,
  title={Efficient query refinement in multimedia databases},
  author={Chakrabarti, Kaushik and Porkaew, Kriengkrai and Mehrotra, Sharad},
  booktitle={Proceedings of the International Conference on Data Engineering},
  pages={196--196},
  year={2000},
  organization={Citeseer}
}

% DataPlay provides two interaction features that support trial-and-error query specification. First, DataPlay allows users to directly manipulate a graphical query by changing quantifiers and modifying dependencies between constraints. Users receive real-time feedback in the form of updated answers and non-answers. Second, DataPlay can auto-correct a user's query, based on user feedback about which tuples to keep or drop from the answers and non-answers.
@article{abouzied2012dataplay,
  title={{DataPlay: Interactive Tweaking and Example-driven Correction of Graphical Database Queries}},
  author={Abouzied, Azza and Hellerstein, Joseph and Silberschatz, Avi},
  journal={UIST},
  year={2012},
}

% We present a mixed-initiative approach to recovery from the retrieval failures that occur when there is no case that satisfies all the user’s requirements. The recovery process begins with an explanation of the retrieval failure in which the user’s attention is drawn to combinations of constraints in her query for which there are no matching cases. The user is then guided in the selection of the most useful attribute, and associated constraint, to be eliminated from her query at each stage of an incremental relaxation process.
@incollection{mcsherry2004incremental,
  title={Incremental relaxation of unsuccessful queries},
  author={McSherry, David},
  booktitle={Advances in Case-Based Reasoning},
  pages={331--345},
  year={2004},
  publisher={Springer}
}

%An automatic interactive data exploration framework, that iteratively steers the user towards interesting data areas and predicts a query that retrieves his objects of interest. In every iteration, the user is prompted to label a set of strategically collected sample objects as relevant or irrelevant. Based on the feedback, a new sample is generated.
@article{dimitriadou2014explore,
  title={Explore-by-Example: An Automatic Query Steering Framework for Interactive Data Exploration},
  author={Dimitriadou, Kyriaki and Papaemmanouil, Olga and Diao, Yanlei},
  booktitle={Proceedings of the 2013 international conference on Management of data},
  year={2014},
  organization={ACM}
}

%---------------------------------------------------------------Data Stream-------------------------------------------------------------------%
% Our system is equipped with both computational pattern mining and visualization techniques, which allow it to not only efficiently discover and manage patterns but also effectively convey the mining results to human analysts through visual displays.
@article{yang2013mining,
  title={Mining and linking patterns across live data streams and stream archives},
  author={Yang, Di and Zhao, Kaiyu and Hasan, Maryam and Lu, Hanyuan and Rundensteiner, Elke and Ward, Matthew},
  journal={Proceedings of the VLDB Endowment},
  volume={6},
  number={12},
  pages={1346--1349},
  year={2013},
  publisher={VLDB Endowment}
}

% We introduce the Event Visualizer, which is a loosely coupled modular system for collecting, processing, analyzing and visualizing dynamic real-time event data streams.
@inproceedings{fischer2012real,
  title={Real-time visual analytics for event data streams},
  author={Fischer, Fabian and Mansmann, Florian and Keim, Daniel A},
  booktitle={Proceedings of the 27th Annual ACM Symposium on Applied Computing},
  pages={801--806},
  year={2012},
  organization={ACM}
}

%In this paper, we propose a framework to visualize multivariate data streams via a combination of windowing and sampling strategies. In order to help users observe how data patterns change over time, we display not only the current sliding window but also abstractions of past data in which users are interested. Uniform sampling is applied within a single sliding window to help reduce visual clutter as well as preserve the data patterns.
@article{xie2008exploring,
  title={Exploring multivariate data streams using windowing and sampling strategies},
  author={Xie, Zaixian and Ward, Matthew and Rundensteiner, Elke},
  year={2008},
  publisher={Citeseer}
}

%We present a framework called CLUES to both computationally and visually support the process of real-time mining of density-based clusters.
@inproceedings{yang2011clues,
  title={CLUES: a unified framework supporting interactive exploration of density-based clusters in streams},
  author={Yang, Di and Guo, Zhenyu and Rundensteiner, Elke A and Ward, Matthew O},
  booktitle={Proceedings of the 20th ACM international conference on Information and knowledge management},
  pages={815--824},
  year={2011},
  organization={ACM}
}

%  V iStream does not only apply innovative multi-query strategies to compute a broad range of popular patterns, such as clusters and outliers, in a highly efficient manner, but it also provides a rich set of visual interfaces and interactions to enable real-time pattern exploration. With ViStream, analysts can easily interact with pattern mining processes by navigating along the time horizons, abstraction levels and parameter spaces, and thus better understand the phenomena of interest.
@inproceedings{yang2010interactive,
  title={Interactive visual exploration of neighbor-based patterns in data streams},
  author={Yang, Di and Guo, Zhenyu and Xie, Zaixian and Rundensteiner, Elke A and Ward, Matthew O},
  booktitle={Proceedings of the 2010 ACM SIGMOD International Conference on Management of data},
  pages={1151--1154},
  year={2010},
  organization={ACM}
}

%-----------------------------------------------------------Others----------------------------------------------------------------%
%Social navigation is a closer reflection of what people actually do than it is a result of what designers think people should be doing.
@article{dieberger2000social,
  title={Social navigation: techniques for building more usable systems},
  author={Dieberger, Andreas and Dourish, Paul and H{\"o}{\"o}k, Kristina and Resnick, Paul and Wexelblat, Alan},
  journal={interactions},
  volume={7},
  number={6},
  pages={36--45},
  year={2000},
  publisher={ACM}
}

% Altogether our findings suggest that quantifying memorability is a general metric of the utility of information, an essential step towards determining how to design effective visualizations.
@article{borkin2013makes,
  title={What makes a visualization memorable?},
  author={Borkin, Michelle A and Vo, Azalea A and Bylinskii, Zoya and Isola, Phillip and Sunkavalli, Shashank and Oliva, Aude and Pfister, Hanspeter},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={12},
  pages={2306--2315},
  year={2013},
  publisher={IEEE}
}

%This short paper reflects recent concerns with the models on which we base navigation mechanisms for information space.
@inproceedings{dourish1994running,
  title={Running out of space: Models of information navigation},
  author={Dourish, Paul and Chalmers, Matthew},
  booktitle={Short paper presented at HCI},
  volume={94},
  pages={23--26},
  year={1994}
}

%---------------------------------------------------------------------------------------Injection System-----------------------------------------------%
%We describe how basic information visualization techniques can help in visualizing, understanding and analyzing the simulation data.
@inproceedings{matkovic2005interactive,
  title={Interactive visual analysis and exploration of injection systems simulations},
  author={Matkovic, Kresimir and Jelovic, Mario and Juric, Josip and Konyha, Zoltan and Gracanin, Denis},
  booktitle={Visualization, 2005. VIS 05. IEEE},
  pages={391--398},
  year={2005},
  organization={IEEE}
}

%------------------------------------------------------------------------------Perfusion Data------------------------------------------------------%
% We present an interactive visual analysis approach for the evaluation of perfusion data. For this purpose, we integrate statistical methods and interactive feature specification. Correlation analysis and Principal Component Analysis (PCA) are applied for dimension reduction and to achieve a better understanding of the inter-parameter relations. Multiple, linked views facilitate the definition of features by brushing multiple dimensions.
@article{oeltze2007interactive,
  title={Interactive visual analysis of perfusion data},
  author={Oeltze, Steffen and Doleisch, Helmut and Hauser, Helwig and Muigg, Philipp and Preim, Bernhard},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={13},
  number={6},
  pages={1392--1399},
  year={2007},
  publisher={IEEE}
}

%-------------------------------------------------------------------------------Atmosphere & Climate------------------------------------------------%
% Our system allows for the integrated visualization of 1D, 2D, and 3D atmospheric data sets in common meteorological grid structures and utilizes a variety of rendering techniques.
@article{song2006atmospheric,
  title={An atmospheric visual analysis and exploration system},
  author={Song, Yuyan and Ye, Jing and Svakhine, Nikolai and Lasher-Trapp, Sonia and Baldwin, Mike and Ebert, David S},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={12},
  number={5},
  pages={1157--1164},
  year={2006},
  publisher={IEEE}
}

%One of the most prominent topics in climate research is the investigation, detection, and allocation of climate change. In this paper, we aim at identifying regions in the atmosphere (e.g., certain height layers) which can act as sensitive and robust indicators for climate change. We demonstrate how interactive visual data exploration of large amounts of multi-variate and time-dependent climate data enables the steered generation of promising hypotheses for subsequent statistical evaluation.
@article{kehrer2008hypothesis,
  title={Hypothesis generation in climate research with interactive visual data exploration},
  author={Kehrer, Johannes and Ladstadter, Florian and Muigg, Philipp and Doleisch, Helmut and Steiner, Andrea and Hauser, Helwig},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={14},
  number={6},
  pages={1579--1586},
  year={2008},
  publisher={IEEE}
}

%In this paper we will explore different techniques to visually assist the user in the analysis of variability and variability changes to allow for a holistic analysis of a global climate model data set consisting of several variables and extending over 250 years.
@article{janicke2009visual,
  title={Visual exploration of climate variability changes using wavelet analysis},
  author={Janicke, Heike and Bottinger, Michael and Mikolajewicz, Uwe and Scheuermann, Gerik},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={15},
  number={6},
  pages={1375--1382},
  year={2009},
  publisher={IEEE}
}

%This paper introduces a library of visualization techniques, tailored to support exploration and evaluation of climate simulation data.
@inproceedings{nocke2007visual,
  title={Visual exploration and evaluation of climate-related simulation data},
  author={Nocke, Thomas and Flechsig, Michael and Bohm, U},
  booktitle={Simulation Conference, 2007 Winter},
  pages={703--711},
  year={2007},
  organization={IEEE}
}

%Because of the complexity of the explorations, provenance is critical, allowing scientists to ensure reproducibility, revisit existing computational pipelines, and more easily share analyses and results.
@incollection{santos2012designing,
  title={Designing a provenance-based climate data analysis application},
  author={Santos, Emanuele and Koop, David and Maxwell, Thomas and Doutriaux, Charles and Ellqvist, Tommy and Potter, Gerald and Freire, Juliana and Williams, Dean and Silva, Cl{\'a}udio T},
  booktitle={Provenance and Annotation of Data and Processes},
  pages={214--219},
  year={2012},
  publisher={Springer}
}

%--------------------------------------------------------------------------------Rail Injection System----------------------------------------------%
% In this paper we describe a successful realization of a tightly coupled steering loop, integrating new simulation technology and interactive visual analysis in a prototyping environment for automotive industry system design.
@article{matkovic2008interactive,
  title={Interactive visual steering-rapid visual prototyping of a common rail injection system},
  author={Matkovic, Kresimir and Gracanin, Denis and Jelovic, Mario and Hauser, Helwig},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={14},
  number={6},
  pages={1699--1706},
  year={2008},
  publisher={IEEE}
}

%--------------------------------------------------------------------------------Histogram Computation----------------------------------------%
%How to compute histograms fast.
@article{lee2013efficient,
  title={Efficient Local Statistical Analysis via Integral Histograms with Discrete Wavelet Transform},
  author={Lee, Teng-Yok and Shen, Han-Wei},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={19},
  number={12},
  pages={2693--2702},
  year={2013},
  publisher={IEEE}
}

%----------------------------------------------------------------------------------Categorical Data------------------------------------------------%
%Parallel Sets are a new method for the visualization and interactive exploration of categorical data that shows data frequencies instead of the individual data points.
@article{kosara2006parallel,
  title={Parallel sets: Interactive exploration and visual analysis of categorical data},
  author={Kosara, Robert and Bendix, Fabian and Hauser, Helwig},
  journal={Visualization and Computer Graphics, IEEE Transactions on},
  volume={12},
  number={4},
  pages={558--568},
  year={2006},
  publisher={IEEE}
}

%This dissertation describes several interactive visualization techniques designed to enhance analysts' experience in performing search, exploration, and summarization of multiple sets of temporal categorical data.
@article{wang2010interactive,
  title={Interactive visualization techniques for searching temporal categorical data},
  author={Wang, Taowei David},
  year={2010}
}

@article{nandi2009hamster,
  title={HAMSTER: using search clicklogs for schema and taxonomy matching},
  author={Nandi, Arnab and Bernstein, Philip A},
  journal={Proceedings of the VLDB Endowment},
  volume={2},
  number={1},
  pages={181--192},
  year={2009},
  publisher={VLDB Endowment}
}

@article{hackathondispatch,
  title={Hackathon teams at Ohio State create code to success},
  author={Ben Sutherly},
  journal={The Columbus Dispatch},
  year={2013}
}

@article{hacktv,
  title={Second Annual Hackathon},
  author={WCMH},
  journal={NBC Columbus Nightly News},
  year={2014}
}

@misc{hortonworks,
   author = "Hortonworks, Inc.",
   title="New features in Pig 0.11\newline
 ( \texttt{http://www.slideshare.net/hortonworks/new-features-in-pig-011/6} )"
 }

 @inproceedings{nandi2013little,
   title={With a little help from my friends},
   author={Nandi, Arnab and Paparizos, Stelios and Shafer, John C and Agrawal, Rakesh},
   booktitle={Data Engineering (ICDE), 2013 IEEE 29th International Conference on},
   pages={1288--1291},
   year={2013},
   organization={IEEE}
 }

@article{dicedemo,
  title={Combining User Interaction, Speculative Query Execution and Sampling in the DICE System},
  author={Kamat, Prasanth Jayachandran Karthik Tunga Niranjan and Nandi, Arnab},
  journal={Proceedings of the VLDB Endowment},
  volume={7},
  number={13},
  year={2014}
}

@article{gopalakrishnan2012shale,
  title={Is the Shale Boom a Bust for Nearby Residents? Evidence from Housing Values in Pennsylvania},
  author={Gopalakrishnan, Sathya and Klaiber, H Allen},
  journal={American Journal of Agricultural Economics},
  year={2013}
}

@inproceedings{gesturequery,
  title={Gestural Query Specification},
  author={Arnab Nandi and Lilong Jiang and Michael Mandel},
  booktitle={Proceedings of the 40th International Conference on Very large data bases},
  year={2014},
  organization={VLDB}
}

@article{hackathonlantern,
  title={Ohio State students create software programs in 25-hour Hackathon},
  author={Alexa Carson},
  journal={The Lantern},
  year={2013}
}

@article{hackathoneventreport,
title={{The 2013 OSU Hackathon: Event Report}},
author={Arnab Nandi and Meris Mandernach},
url={{http://arnab.org/files/HackathonReport.pdf}}
}

@book{saltelli2000sensitivity,
  title={Sensitivity analysis},
  author={Saltelli, Andrea and Chan, Karen and Scott, E Marian and others},
  volume={134},
  year={2000},
  publisher={Wiley New York}
}

% Perception

@incollection{acousticshandbook,
  year={2008},
  isbn={978-0-387-77698-9},
  booktitle={Handbook of Signal Processing in Acoustics},
  editor={Havelock, David and Kuwano, Sonoko and Vorländer, Michael},
  doi={10.1007/978-0-387-30441-0_42},
  title={Perceptually Based Audio Coding},
  url={http://dx.doi.org/10.1007/978-0-387-30441-0_42},
  publisher={Springer New York},
  author={Houtsma, AdrianusJ.M.},
  pages={797-817},
  language={English}
}

@article{card-goms,
 author = {Card, Stuart K. and Moran, Thomas P. and Newell, Allen},
 title = {The Keystroke-level Model for User Performance Time with Interactive Systems},
 journal = {Commun. ACM},
 issue_date = {July 1980},
 volume = {23},
 number = {7},
 month = jul,
 year = {1980},
 issn = {0001-0782},
 pages = {396--410},
 numpages = {15},
 url = {http://doi.acm.org/10.1145/358886.358895},
 doi = {10.1145/358886.358895},
 acmid = {358895},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {cognitive psychology, ergonomics, human factors, human-computer interaction, human-computer interface, systems design, user model, user performance},
}

% Query Scheduling

@inproceedings{queryscheduling,
 author = {Urhan, Tolga and Franklin, Michael J.},
 title = {Dynamic Pipeline Scheduling for Improving Interactive Query Performance},
 booktitle = {Proceedings of the 27th International Conference on Very Large Data Bases},
 series = {VLDB '01},
 year = {2001},
 isbn = {1-55860-804-4},
 pages = {501--510},
 numpages = {10},
 url = {http://dl.acm.org/citation.cfm?id=645927.672188},
 acmid = {672188},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
}

@article {perceptualmodelpersonalized,
author = {Cleveland, W. S. and Harris, C. S. and McGill, R.},
title = {Human Factors and Behavioral Science: Experiments on Quantitative Judgments of Graphs and Maps},
journal = {Bell System Technical Journal},
volume = {62},
number = {6},
publisher = {Blackwell Publishing Ltd},
issn = {1538-7305},
url = {http://dx.doi.org/10.1002/j.1538-7305.1983.tb03504.x},
doi = {10.1002/j.1538-7305.1983.tb03504.x},
pages = {1659--1674},
year = {1983},
}

@ARTICLE{talbot,
author={Talbot, J. and Setlur, V. and Anand, A.},
journal={Visualization and Computer Graphics, IEEE Transactions on},
title={Four Experiments on the Perception of Bar Charts},
year={2014},
month={Dec},
volume={20},
number={12},
pages={2152-2160},
keywords={data visualisation;human factors;aligned bar charts;bar chart configuration;bar chart design;bar chart reading task;bar charts perception;graphical perception paper;perceptual task;stacked bar charts;visualization type;Bar charts;Data visualization;Estimation;Information analysis;Three-dimensional displays;Visual analytics;Graphical perception;bar charts},
doi={10.1109/TVCG.2014.2346320},
ISSN={1077-2626},}

@inproceedings{heerperception,
  title = {Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design},
  author = {Jeffrey Heer AND Michael Bostock},
  booktitle = {ACM Human Factors in Computing Systems (CHI)},
  year = {2010},
  pages = {203--212},
  url = {http://vis.stanford.edu/papers/crowdsourcing-graphical-perception}
}

@article{clevelandmcgill1984,
  added-at = {2012-05-05T17:00:53.000+0200},
  author = {Cleveland, William S. and McGill, Robert},
  biburl = {http://www.bibsonomy.org/bibtex/25234fbbabcf2ac0bfab4f335af2f18ee/procomun},
  copyright = {Copyright © 1984 American Statistical Association},
  file = {Cleveland.McGill1984.pdf:Cleveland.McGill1984.pdf:PDF},
  groups = {public},
  interhash = {8f85e9b8f15a85291d8c1d47c1c42e84},
  intrahash = {5234fbbabcf2ac0bfab4f335af2f18ee},
  issn = {01621459},
  journal = {Journal of the American Statistical Association},
  jstor_articletype = {research-article},
  jstor_formatteddate = {Sep., 1984},
  keywords = {},
  language = {English},
  number = 387,
  pages = {pp. 531-554},
  publisher = {American Statistical Association},
  timestamp = {2012-05-05T17:00:53.000+0200},
  title = {Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods},
  url = {http://www.jstor.org/stable/2288400},
  username = {procomun},
  volume = 79,
  year = 1984
}

@book{stevens1975,
  title={Psychophysics},
  author={Stevens, S.S.},
  isbn={9781412832335},
  url={http://books.google.com/books?id=r5JOHlXX8bgC},
  year={1975},
  publisher={Transaction Publishers}
}

@inproceedings{jpegqualityfactor,
 author = {Chandra, Surendar and Ellis, Carla Schlatter},
 title = {JPEG Compression Metric As a Quality-aware Image Transcoding},
 booktitle = {Proceedings of the 2Nd Conference on USENIX Symposium on Internet Technologies and Systems - Volume 2},
 series = {USITS'99},
 year = {1999},
 location = {Boulder, Colorado},
 pages = {8--8},
 numpages = {1},
 url = {http://dl.acm.org/citation.cfm?id=1251480.1251488},
 acmid = {1251488},
 publisher = {USENIX Association},
 address = {Berkeley, CA, USA},
}

% APPROXIMATION SECTION REFS

@ARTICLE{keimpixel,
    author = {Daniel A. Keim},
    title = {Pixel-oriented Visualization Techniques for Exploring Very Large Databases},
    journal = {Journal of Computational and Graphical Statistics},
    year = {1996},
    volume = {5},
    pages = {58--77}
}

@article{weber,
year={1968},
issn={0031-5117},
journal={Perception And Psychophysics},
volume={4},
number={2},
doi={10.3758/BF03209518},
title={A study of the near-miss involving Weber’s law and pure-tone intensity discrimination},
url={http://dx.doi.org/10.3758/BF03209518},
publisher={Springer-Verlag},
author={McGill, W.J. and Goldberg, J.P.},
pages={105-109},
language={English}
}

@inproceedings{control,
 author = {Hellerstein, Joseph M. and Haas, Peter J. and Wang, Helen J.},
 title = {Online Aggregation},
 booktitle = {Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data},
 series = {SIGMOD '97},
 year = {1997},
 isbn = {0-89791-911-4},
 location = {Tucson, Arizona, USA},
 pages = {171--182},
 numpages = {12},
 url = {http://doi.acm.org/10.1145/253260.253291},
 doi = {10.1145/253260.253291},
 acmid = {253291},
 publisher = {ACM},
 address = {New York, NY, USA},
}

@inproceedings{blinkdb,
 author = {Agarwal, Sameer and Mozafari, Barzan and Panda, Aurojit and Milner, Henry and Madden, Samuel and Stoica, Ion},
 title = {BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data},
 booktitle = {Proceedings of the 8th ACM European Conference on Computer Systems},
 series = {EuroSys '13},
 year = {2013},
 isbn = {978-1-4503-1994-2},
 location = {Prague, Czech Republic},
 pages = {29--42},
 numpages = {14},
 url = {http://doi.acm.org/10.1145/2465351.2465355},
 doi = {10.1145/2465351.2465355},
 acmid = {2465355},
 publisher = {ACM},
 address = {New York, NY, USA},
}

@INPROCEEDINGS{aqua,
    author = {Swarup Acharya Phillip and Phillip B. Gibbons and Viswanath Poosala},
    title = {Aqua: A Fast Decision Support System Using Approximate Query Answers},
    booktitle = {In Proc. of 25th Intl. Conf. on Very Large Data Bases},
    year = {1999},
    pages = {754--755}
}

@article{chaudhuristratsample,
 author = {Chaudhuri, Surajit and Das, Gautam and Narasayya, Vivek},
 title = {Optimized Stratified Sampling for Approximate Query Processing},
 journal = {ACM Trans. Database Syst.},
 issue_date = {June 2007},
 volume = {32},
 number = {2},
 month = jun,
 year = {2007},
 issn = {0362-5915},
 articleno = {9},
 url = {http://doi.acm.org/10.1145/1242524.1242526},
 doi = {10.1145/1242524.1242526},
 acmid = {1242526},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {Random sampling, approximation, query processing},
}

@INPROCEEDINGS{haashoeffding,
    author = {Peter J. Haas and Peter J. Haas},
    title = {Hoeffding Inequalities for Join-Selectivity Estimation and Online Aggregation},
    booktitle = {IBM Research Report RJ 10040, IBM Almaden Research},
    year = {1996}
}

@article{harrison2014ranking,
  title = {Ranking Visualizations of Correlation using Weber's Law},
  author = {Lane Harrison AND Fumeng Yang AND Steven Franconeri AND Remco Chang},
  journal = {IEEE Conference on Information Visualization (InfoVis)},
  year = {2014}
}

@inproceedings{relcloud,
author =       "Carlo Curino and Evan Jones and Raluca Ada Popa and Nirmesh Malviya and Eugene Wu and Samuel Madden and Hari Balakrishnan and Nickolai Zeldovich",
title =        "{Relational Cloud: A Database Service for the Cloud}",
booktitle =    {CIDR},
year =         {2011}
}

@inproceedings{rodent,
  author    = {Philippe Cudr{\'e}-Mauroux and
               Eugene Wu and
               Samuel Madden},
  title     = {The Case for RodentStore: An Adaptive, Declarative Storage System},
  booktitle = {CIDR},
  year      = {2009}
}

@inproceedings{webtables,
  author    = {Michael J. Cafarella and
               Alon Y. Halevy and
               Yang Zhang and
               Daisy Zhe Wang and
               Eugene Wu},
  title     = {Uncovering the Relational Web},
  booktitle = {WebDB},
  year      = {2008}
}

@inproceedings{smoke,
title = {Smoke: Visualization Interactions using Provenance (In preparation)},
author = {Eugene Wu and Samuel Madden}
}

@inproceedings{sase,
  title={High-performance complex event processing over streams},
  author={Wu, Eugene and Diao, Yanlei and Rizvi, Shariq},
  booktitle={SIGMOD},
  year={2006},
  organization={ACM}
}

@inproceedings{sorts,
  title={Human-powered sorts and joins},
  author={Marcus, Adam and Wu, Eugene and Karger, David R and Madden, Samuel R and Miller, Robert C},
  booktitle={VLDB},
  year={2011}
}

@inproceedings{qurk,
  title={Crowdsourced databases: Query processing with people},
  author={Marcus, Adam and Wu, Eugene and Karger, David R and Madden, Samuel R and Miller, Robert C},
  year={2011},
  booktitle={CIDR}
}

@inproceedings{shinobi,
  title={Partitioning techniques for fine-grained indexing},
  author={Wu, Eugene and Madden, Samuel},
  booktitle={ICDE},
  year={2011}
}

@inproceedings{nobits,
  title={No bits left behind},
  author={Wu, Eugene and Curino, Carlo Aldo and Madden, Samuel R},
  year={2011},
  booktitle={CIDR}
}

@inproceedings{data,
  title={Data In Context: Aiding News Consumers while Taming Dataspaces},
  author={Marcus, Adam and Wu, Eugene and Madden, Sam},
  booktitle={DBCrowd},
  year={2013}
}

@inproceedings{satsuma,
  title={Mobile applications need targeted micro-updates},
  author={Cheung, Alvin and Ravindranath, Lenin and Wu, Eugene and Madden, Samuel and Balakrishnan, Hari},
  booktitle={APSys},
  year={2013},
  organization={ACM}
}

@inproceedings{trajstore,
  title={Trajstore: An adaptive storage system for very large trajectory data sets},
  author={Cudre-Mauroux, Philippe and Wu, Eugene and Madden, Samuel},
  booktitle={ICDE},
  year={2010}
}

@inproceedings{dice2014,
	title={{Distributed and Interactive Cube Exploration}},
	author={Niranjan Kamat and Prasanth Jayachandran and Kathik Tunga and Arnab Nandi},
	booktitle={ICDE},
	year={2014},
}

@article{kandel2012,
  title = {Enterprise Data Analysis and Visualization: An Interview Study},
  author = {Kandel, Sean and Paepcke, Andreas and Hellerstein, Joseph and Heer Jeffrey},
  journal = {VAST},
  year = {2012},
}

blinkdb
@inproceedings{agarwal2013blinkdb,
 author = {Agarwal, Sameer and Mozafari, Barzan and Panda, Aurojit and Milner, Henry and Madden,
Samuel and Stoica, Ion},
 title = {BlinkDB: queries with bounded errors and bounded response times on very large data},
 Journal = {EuroSys},
 year = {2013}
}

@misc{ggplot2,
  key={ggplot},
  year=2015,
  title =  {ggplot2},
  howpublished = "\url{ggplot2.org}",
}

protovis
@article{Bostock09protovis,
  title = {Protovis: A Graphical Toolkit for Visualization},
  author = {Michael Bostock and Jeffrey Heer},
  journal = {InfoVis},
  year = {2009},
  url = {http://vis.stanford.edu/papers/protovis}
}

d3 paper
@article{Bostock11d3,
  title = {D3: Data-Driven Documents},
  author = {Michael Bostock AND Vadim Ogievetsky AND Jeffrey Heer},
  journal = {InfoVis},
  year = {2011},
  url = {http://vis.stanford.edu/papers/d3},
}

@Article{matplotlib,
  Author    = {Hunter, J. D.},
  Title     = {Matplotlib: A 2D graphics environment},
  Journal   = {Computing In Science \& Engineering},
  year      = 2007
}

graphics visibility culling
@ARTICLE{cullingsurvey,
  author = {Daniel Cohen-Or and Yiorgos L. Chrysanthou and Cláudio T. Silva and Frédo Durand},
  title = { A survey of visibility for walkthrough applications},
  journal = {IEEE Transactions on Visualization and Computers},
  year = {2003}
}

@article{brushing,
 author = {Becker, Richard A. and Cleveland, William S.},
 title = {Brushing Scatterplots},
 journal = {Technometrics},
 year = {1987},
}

@inproceedings{visreduce,
  author    = {Jean-Francois Im and
               Felix Giguere Villegas and
               Michael J. McGuffin},
  title     = {VisReduce: Fast and responsive incremental information visualization
               of large datasets},
  booktitle = {BigData Conference},
  year      = {2013},
}

@book{eda,
  author = {Tukey, John W.},
  publisher = {Addison-Wesley},
  title = {Exploratory Data Analysis},
  year = 1977
}

@book{cleveland1994elements,
  address = {Murray Hill, N.J.},
  author = {Cleveland, William S.},
  publisher = {ATT Bell Laboratories},
  title = {The elements of graphing data},
  url = {http://www.worldcat.org/search?qt=worldcat_org_all&q=0963488414},
  year = 1994
}

@TechReport{bigvis,
  title = {Bin-summarise-smooth: a framework for visualising large data},
  author = {Hadley Wickham},
  year = {2013},
  institution = {had.co.nz}
}

grammar of graphics
@book{grammar,
 author = {Wilkinson, Leland},
 title = {The Grammar of Graphics (Statistics and Computing)},
 year = {2005},
 publisher = {Springer-Verlag New York, Inc.},
}

@inproceedings{autoadmin,
  author = {Chaudhuri, Surajit and Narasayya, Vivek R.},
  booktitle = {SIGMOD},
  title = {AutoAdmin 'What-if' Index Analysis Utility.},
  url = {http://dblp.uni-trier.de/db/conf/sigmod/sigmod98.html#ChaudhuriN98},
  year = 1998
}

@inproceedings{selinger,
 author = {Selinger, P. Griffiths and Astrahan, M. M. and Chamberlin, D. D. and Lorie, R. A. and Price, T. G.},
 title = {Access Path Selection in a Relational Database Management System},
 booktitle = {SIGMOD},
 year = {1979},
 url = {http://doi.acm.org/10.1145/582095.582099},
}

@article{datacube,
 author = {Gray, Jim and Chaudhuri, Surajit and Bosworth, Adam and Layman, Andrew and Reichart, Don and Venkatrao, Murali and Pellow, Frank and Pirahesh, Hamid},
 title = {Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals},
 journal = {KDD},
 year = {1997},
}

@inproceedings{asr,
  author = {Kemper, Alfons and Moerkotte, Guido},
  booktitle = {VLDB},
  title = {Advanced Query Processing in Object Bases Using Access Support Relations.},
  url = {http://dblp.uni-trier.de/db/conf/vldb/vldb90.html#KemperM90},
  year = 1990
}

estcost
@inproceedings{estcost,
  author = {Chaudhuri, Surajit and Narasayya, Vivek and Ramamurthy, Ravishankar},
  booktitle = {SIGMOD},
  title = {Estimating progress of execution for SQL queries},
  year = 2004
}

@article{ermac,
  author = {Eugene Wu and Leilani Battle and Samuel R. Madden},
  title = {The Case for Data Visualization Management Systems [Vision Paper]},
  booktitle = {VLDB},
  year = {2014}
}

@article{scorpion,
  author    = {Eugene Wu and Samuel Madden},
  title     = {Scorpion: Explaining Away Outliers in Aggregate Queries},
  journal   = {PVLDB},
  year      = {2013}
}

@article{reverseqmanagement,
  author    = {Alexandra Meliou and
               Wolfgang Gatterbauer and
               Dan Suciu},
  title     = {Reverse Data Management},
  journal   = {PVLDB},
  year      = {2011}
}

@inproceedings{willett,
 author = {Willett, Wesley and Heer, Jeffrey and Agrawala, Maneesh},
 title = {Strategies for Crowdsourcing Social Data Analysis},
 booktitle = {CHI},
 year = {2012}
}

@article{vizdeck,
  author = {Key, Alicia and Howe, Bill and Perry, Daniel and Aragon, Cecilia R.},
  journal = {SIGMOD},
  title = {VizDeck: self-organizing dashboards for visual analytics.},
  url = {http://dblp.uni-trier.de/db/conf/sigmod/sigmod2012.html#KeyHPA12},
  year = 2012
}

@article{seedb,
  title = {SeeDB: Visualizing Database Queries Efficiently},
  author = {Aditya Parameswaran and Neoklis Polyzotis and Hector Garcia-Molina},
  journal = {PVLDB},
  year      = {2014}
}

i^3 paper
@inproceedings{sunita,
  author = {Sarawagi, Sunita and Sathe, Gayatri},
  booktitle = {SIGMOD},
  title = {i3: Intelligent, Interactive Investigaton of OLAP data cubes.},
  url = {http://dblp.uni-trier.de/db/conf/sigmod/sigmod2000.html#Sarawagi00},
  year = 2000
}

showme paper
@article{showme,
 author = {Mackinlay, Jock and Hanrahan, Pat and Stolte, Chris},
 title = {Show Me: Automatic Presentation for Visual Analysis},
 journal = {IEEE Transactions on Visualization and Computer Graphics},
 year = {2007},
}

@inproceedings{imagefeatures,
    author = {Aude Oliva and Antonio Torralba},
    title = {Building the gist of a scene: the role of global image features in recognition},
    booktitle = {Progress in Brain Research},
    year = {2006},
}

@article{dataenthusiast,
  author    = {Kristi Morton and
               Magdalena Balazinska and
               Dan Grossman and
               Jock D. Mackinlay},
  title     = {Support the Data Enthusiast: Challenges for Next-Generation
               Data-Analysis Systems},
  journal   = {PVLDB},
  year      = {2014},
}

tableaudb
@inproceedings{tableaudb,
 author = {Wesley, Richard and Eldridge, Matthew and Terlecki, Pawel T.},
 title = {An Analytic Data Engine for Visualization in Tableau},
 booktitle = {SIGMOD},
 year = {2011},
 url = {http://doi.acm.org/10.1145/1989323.1989449},
}

chris weaver improvise
@inproceedings{improvise,
  author = {Weaver, Chris},
  booktitle = {INFOVIS},
  title = {Building Highly-Coordinated Visualizations in Improvise.},
  url = {http://dblp.uni-trier.de/db/conf/infovis/infovis2004.html#Weaver04},
  year = 2004
}

@article{interactivedynamics,
 author = {Heer, Jeffrey and Shneiderman, Ben},
 title = {Interactive Dynamics for Visual Analysis},
 journal = {Commun. ACM},
 issue_date = {April 2012},
 volume = {55},
 number = {4},
 month = apr,
 year = {2012},
 issn = {0001-0782},
 pages = {45--54},
 numpages = {10},
 url = {http://doi.acm.org/10.1145/2133806.2133821},
 doi = {10.1145/2133806.2133821},
 acmid = {2133821},
 publisher = {ACM},
 address = {New York, NY, USA},
}

@phdthesis{anoto,
  added-at = {2012-04-18T00:00:00.000+0200},
  author = {Signer, Beat},
  biburl = {http://www.bibsonomy.org/bibtex/2119db91587a84c4bdcc27befb9909ac4/dblp},
  interhash = {aaad88cd2853c82e2a2d6e438a79b99e},
  intrahash = {119db91587a84c4bdcc27befb9909ac4},
  isbn = {978-3-8370-2713-6},
  keywords = {dblp},
  note = {http://d-nb.info/991213726},
  pages = {1-257},
  school = {ETH Zurich},
  timestamp = {2012-04-18T00:00:00.000+0200},
  title = {Fundamental concepts for interactive paper and cross-media information spaces.},
  year = 2008
}

@article{wacom,
  title = {Wacom Inc.},
  journal = {http://www.wacom.com}
}

@inproceedings{robwang,
 author = {Wang, Robert Y. and Popovi\'{c}, Jovan},
 title = {Real-time Hand-tracking with a Color Glove},
 booktitle = {ACM SIGGRAPH 2009 Papers},
 series = {SIGGRAPH '09},
 year = {2009},
 isbn = {978-1-60558-726-4},
 location = {New Orleans, Louisiana},
 pages = {63:1--63:8},
 articleno = {63},
 numpages = {8},
 url = {http://doi.acm.org/10.1145/1576246.1531369},
 doi = {10.1145/1576246.1531369},
 acmid = {1531369},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {augmented reality, hand tracking, motion capture, user interface},
}

@article{kinect,
 author = {Zhang, Zhengyou},
 title = {Microsoft Kinect Sensor and Its Effect},
 journal = {IEEE MultiMedia},
 issue_date = {April 2012},
 volume = {19},
 number = {2},
 month = apr,
 year = {2012},
 issn = {1070-986X},
 pages = {4--10},
 numpages = {7},
 url = {http://dx.doi.org/10.1109/MMUL.2012.24},
 doi = {10.1109/MMUL.2012.24},
 acmid = {2225203},
 publisher = {IEEE Computer Society Press},
 address = {Los Alamitos, CA, USA},
 keywords = {multimedia, Microsoft Kinect, human-computer interaction, motion capture, computer vision},
}

@article{percfusion,
  title={Cross-modal bias and perceptual fusion with auditory-visual spatial discordance},
  author={Bertelson, Paul and Radeau, Monique},
  journal={Perception And Psychophysics},
  volume={29},
  number={6},
  pages={578--584},
  year={1981},
  publisher={Springer}
}

@inproceedings{olston2009interactive,
  title={Interactive Analysis of Web-Scale Data.},
  author={Olston, Christopher and Bortnikov, Edward and Elmeleegy, Khaled and Junqueira, Flavio and Reed, Benjamin},
  booktitle={CIDR},
  year={2009}
}

@phdthesis{wuthesis,
  author       = {Eugene Wu},
  title        = {Explaining Data in Visual Analytic Systems},
  school       = {Massachusetts Institute of Technology },
  year         = 2015,
  month        = 2

}

@misc{dbtruck,
  title = {{DBTruck}: Humane Data Import},
  author = {Wu, Eugene},
  month = {October},
  year = {2012},
  note = {\url{http://istc-bigdata.org/index.php/dbtruck-humane-data-import/}}
}

@inproceedings{cord,
  added-at = {2013-12-17T10:11:22.000+0100},
  address = {New York, NY, USA},
  author = {Ilyas, Ihab F and Aboulnaga, Ashraf and Road, Harry and B, K and Jose, San and Markl, Volker and Haas, Peter and Brown, Paul},
  biburl = {http://www.bibsonomy.org/bibtex/2b4e04b56f42dc3459318afbbf8d80d3c/jullybobble},
  booktitle = {SIGMOD},
  doi = {10.1145/1007568.1007641},
  interhash = {1fb24548bc9185e1dc1fca95da16ea5e},
  intrahash = {b4e04b56f42dc3459318afbbf8d80d3c},
  isbn = {1-58113-859-8},
  keywords = {imported phd},
  pages = {647--658},
  publisher = {ACM},
  series = {SIGMOD '04},
  timestamp = {2013-12-17T10:11:22.000+0100},
  title = {{CORDS: automatic discovery of correlations and soft functional dependencies}},
  url = {http://doi.acm.org/10.1145/1007568.1007641},
  year = 2004
}

@inproceedings{profiler,
title = {Profiler: Integrated Statistical Analysis and Visualization for Data Quality Assessment},
author = {Sean Kandel AND Ravi Parikh AND Andreas Paepcke AND Joseph Hellerstein AND Jeffrey Heer},
booktitle = {Advanced Visual Interfaces},
year = {2012},
url = {http://vis.stanford.edu/papers/profiler}
}

@article{dirmanip,
  title={Direct manipulation for comprehensible, predictable and controllable user interfaces},
  author={Shneiderman, Ben},
  journal={IUI},
  year={1997},
}

@article{qwik,
  title={{Querying Without Keyboards}},
  author={Nandi, Arnab},
  journal={CIDR},
  year={2013}
}

@article{ijoin,
  title={{The Interactive Join: Recognizing Gestures for Database Queries}},
  author={Nandi, A. and Mandel, M.},
  journal={CHI},
  year={2013},
}

@article{sqlkinection,
          title={Sql server kinection},
          author={{Patney, S., et al}},
          journal={PASS},
          year={2011},
}

@misc{pgAdmin,
  title = {{pgAdmin}},
  howpublished = "\url{http://www.pgadmin.org/}",
}

@article{canalys,
  title={{Worldwide Smartphone and Client PC Shipment Estimates}},
  author={Canalys},
  year={2012},
}

@misc{tornado,
  title = {{Tornado}},
  howpublished = "\url{ http://www.tornadoweb.org/}",
}

@misc{apple,
  title = {{Apple Developer}},
  howpublished = "\url{ http://developer.apple.com/}",
}

@misc{zepto,
  title = {{Zepto}},
  howpublished = "\url{ http://zeptojs.com/}",
}

@misc{chinook,
  title = {{Chinook Database}},
  howpublished = "\url{ http://chinookdatabase.codeplex.com/}",
}

@misc{tpch,
  title = {{TPC-H Benchmark}},
  howpublished = "\url{ http://www.tpc.org/tpch/}",
}

@misc{vqb,
  title = {{Active Query Builder}},
  howpublished = "\url{ http://www.activequerybuilder.com/}",
}

@article{qbe,
  title={Query by example},
  author={Zloof, Mosh{\'e} M},
  journal={NCCE},
  year={1975},
}

@article{codd,
  title={A relational model of data for large shared data banks},
  author={Codd, Edgar F},
  journal={CACM},
  year={1970},
}

@article{jagadish2007making,
  title={Making database systems usable},
  author={Jagadish, HV and others},
  journal={SIGMOD},
  year={2007},
}

@article{nandi2007assisted,
  title={Assisted querying using instant-response interfaces},
  author={Nandi, Arnab and Jagadish, HV},
  journal={SIGMOD},
  year={2007},
  organization={ACM}
}

@article{abouzied2012dataplay,
  title={DataPlay: interactive tweaking and example-driven correction of graphical database queries},
  author={Abouzied, Azza and others},
  journal={UIST},
  year={2012},
}

@article{kammer2010taxonomy,
  title={Taxonomy and overview of multi-touch frameworks: Architecture, scope and features},
  author={Kammer, D. and Keck, M. and Freitag, G. and Wacker, M.},
  journal={EPMI},
  year={2010}
}

@article{hirte2012data3,
  title={Data3--A Kinect Interface for OLAP Using Complex Event Processing},
  author={Hirte, Steffen and others},
  journal={ICDE},
  year={2012}
}

@article{ishikawa1998mindreader,
  author    = {Yoshiharu Ishikawa and others},
  title     = {MindReader: Querying Databases Through Multiple Examples},
  journal = {{VLDB}},
  year  = {1998},
}

@article{shneiderman1984response,
  title={{Response Time and Display Rate in Human Performance with Computers}},
  author={Shneiderman, B.},
  journal={CSUR},
  year={1984},
}
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license: MIT

license_type: permissive

branch_name: refs/heads/master

extension: bib