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.gitattributes

@@ -59,3 +59,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
 metadata.csv filter=lfs diff=lfs merge=lfs -text
 train.csv filter=lfs diff=lfs merge=lfs -text
+tesis_uchile_min.json filter=lfs diff=lfs merge=lfs -text
+tesis_uchile_pretty.json filter=lfs diff=lfs merge=lfs -text
+tesis.uchile.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,167 @@
 ---
+pretty_name: Tesis UChile
 license: unknown
 ---
+
+# Tesis UChile
+
+`erickfmm/Tesis_UChile` is a collection of thesis metadata from the University of Chile repository (`repositorio.uchile.cl`). The data was obtained by scraping public pages around August 2024 (approximately), and then normalized into a row-based CSV plus grouped JSON exports.
+
+## What is in this dataset?
+
+The main file is `train.csv`. Each row represents one metadata value associated with a source record. Rows are linked by the `origen` field, which acts as the record identifier or source URL.
+
+The repository also includes JSON and JSONL exports generated from `train.csv`, where all rows that share the same `origen` are grouped into a single document.
+
+This dataset mainly contains bibliographic and repository metadata, for example:
+
+- thesis title
+- author
+- advisor
+- publisher / faculty / school
+- issue or accession dates
+- language
+- subjects
+- rights / access fields
+- repository links and file links
+
+Most keys follow Dublin Core naming conventions such as `dc.title`, `dc.subject`, `dc.identifier.uri`, and `dcterms.accessRights`.
+
+## Files
+
+| File | Description | Link |
+| --- | --- | --- |
+| `train.csv` | Row-level metadata table used as the base dataset. On Hugging Face, this is exposed as the `train` split. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/train.csv) |
+| `tesis_uchile_pretty.json` | Grouped JSON array, pretty-printed for easier inspection. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis_uchile_pretty.json) |
+| `tesis_uchile_min.json` | Grouped JSON array, compact version of the same data. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis_uchile_min.json) |
+| `tesis.uchile.jsonl` | Grouped JSON Lines export, one record per line, convenient for streaming and incremental processing. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis.uchile.jsonl) |
+
+## CSV schema
+
+The processing script expects at least the following columns in `train.csv`:
+
+| Column | Meaning |
+| --- | --- |
+| `origen` | Source identifier for a thesis record, typically the repository URL used to group rows. |
+| `DC` | Metadata field name, usually a Dublin Core-style key such as `dc.title` or `dc.subject`. |
+| `nombre` | Original scraped field name. A special case maps `filelink` to `extra.file.link` when `DC` is missing. |
+| `value` | Metadata value. Empty values are skipped when building the JSON exports. |
+| `lang` | Optional language tag for the value, for example `es_CL`. |
+
+## JSON / JSONL structure
+
+The JSON exports are built by grouping all rows with the same `origen`.
+
+Rules used in the export:
+
+- each grouped record gets `_id = origen`
+- scalar values are stored as `{"value": "..."}`
+- when a language is available, values become `{"value": "...", "lang": "..."}`
+- repeated metadata fields become lists
+- if `DC` is missing and `nombre == "filelink"`, the field is stored as `extra.file.link`
+
+Example grouped record:
+
+```json
+{
+  "_id": "https://repositorio.uchile.cl/handle/2250/100054",
+  "dc.contributor.advisor": {
+    "value": "Cárdenas, Juan",
+    "lang": "es_CL"
+  },
+  "dc.contributor.author": {
+    "value": "Gallego, Francisco",
+    "lang": "es_CL"
+  },
+  "dc.contributor.editor": [
+    {
+      "value": "Facultad de Arquitectura y Urbanismo",
+      "lang": "es_CL"
+    },
+    {
+      "value": "Escuela de Arquitectura",
+      "lang": "es_CL"
+    }
+  ],
+  "dc.identifier.uri": {
+    "value": "https://repositorio.uchile.cl/handle/2250/100054"
+  },
+  "extra.file.link": {
+    "value": "..."
+  }
+}
+```
+
+## Example code
+
+### Load the CSV with pandas
+
+```python
+import pandas as pd
+
+df = pd.read_csv(
+    "hf://datasets/erickfmm/Tesis_UChile/train.csv",
+    encoding="utf-8",
+)
+
+print(df.head())
+print(df.columns.tolist())
+```
+
+### Load the dataset with `datasets`
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("erickfmm/Tesis_UChile")
+print(dataset)
+print(dataset["train"][0])
+```
+
+### Stream the JSONL export
+
+```python
+import json
+import urllib.request
+
+url = "https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis.uchile.jsonl"
+
+with urllib.request.urlopen(url) as response:
+    for i, line in enumerate(response):
+        record = json.loads(line)
+        title = record.get("dc.title", {})
+        print(record["_id"], title)
+        if i == 2:
+            break
+```
+
+### Read the compact JSON export locally
+
+```python
+import json
+
+with open("tesis_uchile_min.json", "r", encoding="utf-8") as fh:
+    data = json.load(fh)
+
+print(len(data))
+print(data[0]["_id"])
+```
+
+## Source and collection notes
+
+- Source website: public pages from the University of Chile repository (`repositorio.uchile.cl`)
+- Collection method: scraping
+- Collection period: around August 2024 (approximate)
+- Contents: public metadata records and derived grouped exports
+
+## License
+
+No license is provided for this dataset in this repository, or the license is unknown.
+
+If you plan to reuse the data, especially beyond research or indexing purposes, please verify the terms of use of the original source and the rights associated with individual records.
+
+## Limitations
+
+- scraped metadata can contain inconsistencies, missing fields, duplicates, or formatting issues
+- language tags are not guaranteed to exist for every value
+- the JSON exports are derived from `train.csv`, so updates to the CSV should be regenerated in the exported formats

procesar_uchile.py

@@ -0,0 +1,51 @@
+import pandas as pd
+
+print("cargar data")
+# Login using e.g. `huggingface-cli login` to access this dataset
+df = pd.read_csv("hf://datasets/erickfmm/Tesis_UChile/train.csv", encoding="utf-8")
+print("data cargada")
+
+final_data = {}
+total = len(df)
+for idx, row in df.iterrows():
+	#print(idx, row)
+	final_data[row["origen"]] = {"_id": row["origen"]} if row["origen"] not in final_data else final_data[row["origen"]]
+	
+	valor = row["value"] if not pd.isna(row["value"]) or row["value"] is not None else None
+	if valor is None:
+		continue
+	lang = row["lang"] if not pd.isna(row["lang"]) else None
+	valor = {"value": valor}
+	if lang is not None:
+		valor["lang"] = lang
+
+	if pd.isna(row["DC"]) and row["nombre"] == "filelink":
+		row["DC"] = "extra.file.link"
+
+	if row["DC"] not in final_data[row["origen"]]:
+		final_data[row["origen"]][row["DC"]] = valor
+	else:
+		if type(final_data[row["origen"]][row["DC"]]) is list:
+			final_data[row["origen"]][row["DC"]].append(valor)
+		else:
+			final_data[row["origen"]][row["DC"]] = [final_data[row["origen"]][row["DC"]], valor]
+	if idx % 10000 == 0:
+		print("procesados ", idx)
+		print(idx/float(total)*100.0, "%")
+
+#import pprint
+#pprint.pprint(final_data, indent=2)
+
+import json
+#print(json.dumps(final_data, indent=2))
+print("save pretty")
+json.dump([final_data[idx] for idx in final_data.keys()], open("tesis_uchile_pretty.json", "w", encoding="utf-8"), indent=2, ensure_ascii=False)
+print("save min")
+json.dump([final_data[idx] for idx in final_data.keys()], open("tesis_uchile_min.json", "w", encoding="utf-8"), ensure_ascii=False)
+
+print("save jsonl")
+with open("tesis.uchile.jsonl", "w", encoding="utf-8") as fh:
+	for idx in final_data.keys():
+		json.dump(final_data[idx], fh, ensure_ascii=False)
+		fh.write("\n")
+	fh.flush()

tesis.uchile.jsonl

@@ -0,0 +1,3 @@
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+oid sha256:21a068efada8a1533a096c260510509792a1b7c83f4da19eb17dd09a19830ded
+size 185868274

tesis_uchile_min.json

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+oid sha256:b0341072729d6e2b388fac8aa45f64431a8acbb37840f87c548bea3bfa296b6b
+size 185868274

tesis_uchile_pretty.json

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+size 217584687