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cold-cases

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united states
law
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12
Michael Della Bitta commited on
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a603086
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1 Parent(s): d576298

JSON-L sample in README

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README.md CHANGED
@@ -11,20 +11,13 @@ tags:
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  size_categories:
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  - 1M<n<10M
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  viewer: true
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- configs:
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- - config_name: jsonl
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- data_files: "cold.jsonl/*"
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- - config_name: parquet
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- data_files: "cold.parquet/*"
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- default: true
20
  ---
21
 
22
  <a href="https://huggingface.co/datasets/harvard-lil/cold-cases/resolve/main/coldcases.png"><img src="https://huggingface.co/datasets/harvard-lil/cold-cases/resolve/main/coldcases-banner.webp"/></a>
23
 
24
  # Collaborative Open Legal Data (COLD) - Cases
25
 
26
- COLD Cases is a dataset of 8.3 million United States legal decisions with text and metadata, formatted as one JSON object per decision.
27
- The total dataset size is approximately 104GB of uncompressed JSON.
28
 
29
  This dataset exists to support the open legal movement exemplified by projects like
30
  [Pile of Law](https://huggingface.co/datasets/pile-of-law/pile-of-law) and
@@ -34,7 +27,7 @@ United States caselaw is collected and published as open data by [CourtListener]
34
  a wide range of public sources.
35
 
36
  COLD Cases reformats CourtListener's [bulk data](https://www.courtlistener.com/help/api/bulk-data) so that all of the semantic information about each legal decision
37
- (the authors and text of majority and dissenting opinions; head matter; and substantive metadata) is encoded in a single JSON object per decision,
38
  with extraneous data removed. Serving in the traditional role of libraries as a standardization steward, the Harvard Library Innovation Lab is maintaining
39
  this [open source](https://github.com/harvard-lil/cold-cases-export) pipeline to consolidate the data engineering for preprocessing caselaw so downstream machine
40
  learning and natural language processing projects can use consistent, high quality representations of cases for legal understanding tasks.
@@ -57,37 +50,9 @@ Prepared by the [Harvard Library Innovation Lab](https://lil.law.harvard.edu) in
57
 
58
  ---
59
 
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- ## Formats
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- We've released this data in two different formats:
63
-
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- ### JSON-L or JSON Lines
65
-
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- This format consists of a JSON document for every row in the dataset, one per line. This makes it easy to sample a selection of the data or split it out into multiple files for parallel processing using ordinary command line tools such as `head`, `split` and `jq`.
67
-
68
- Just about any language you can think of has a ready way to parse JSON data, which makes this version of the dataset more compatible.
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-
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- See: https://jsonlines.org/
71
-
72
- ### Apache Parquet
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-
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- Parquet is binary format that makes filtering and retrieving the data quicker because it lays out the data in columns, which means columns that are unnecessary to satisfy a given query or workflow don't need to be read.
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-
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- Parquet has more limited support outside the Python and JVM ecosystems, however.
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-
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- See: https://parquet.apache.org/
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-
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- [☝️ Go back to Summary](#summary)
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-
82
- ---
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-
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- ## File structure
85
-
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- Both of these datasets were exported by the same system based on [Apache Spark](https://spark.apache.org/), so within each subdirectory, you'll find a similar list of files:
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-
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- - **_SUCCESS**: This indicates that the job that built the dataset ran successfully and therefore this is a complete dataset.
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- - **.json.gz or .gz.parquet**: Each of these is a slice of the full dataset, encoded in JSON-L or Parquet, and compressed with [GZip](https://www.gnu.org/software/gzip/).
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- - **Hidden `.crc` files**: These can be used to verify that the data transferred correctly and otherwise ignored.
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  [☝️ Go back to Summary](#summary)
93
 
 
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  size_categories:
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  - 1M<n<10M
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  viewer: true
 
 
 
 
 
 
14
  ---
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  <a href="https://huggingface.co/datasets/harvard-lil/cold-cases/resolve/main/coldcases.png"><img src="https://huggingface.co/datasets/harvard-lil/cold-cases/resolve/main/coldcases-banner.webp"/></a>
17
 
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  # Collaborative Open Legal Data (COLD) - Cases
19
 
20
+ COLD Cases is a dataset of 8.3 million United States legal decisions with text and metadata, formatted as compressed parquet files. If you'd like to view a sample of the dataset formatted as JSON Lines, you can view one [here](https://raw.githubusercontent.com/harvard-lil/cold-cases-export/main/sample.jsonl)
 
21
 
22
  This dataset exists to support the open legal movement exemplified by projects like
23
  [Pile of Law](https://huggingface.co/datasets/pile-of-law/pile-of-law) and
 
27
  a wide range of public sources.
28
 
29
  COLD Cases reformats CourtListener's [bulk data](https://www.courtlistener.com/help/api/bulk-data) so that all of the semantic information about each legal decision
30
+ (the authors and text of majority and dissenting opinions; head matter; and substantive metadata) is encoded in a single record per decision,
31
  with extraneous data removed. Serving in the traditional role of libraries as a standardization steward, the Harvard Library Innovation Lab is maintaining
32
  this [open source](https://github.com/harvard-lil/cold-cases-export) pipeline to consolidate the data engineering for preprocessing caselaw so downstream machine
33
  learning and natural language processing projects can use consistent, high quality representations of cases for legal understanding tasks.
 
50
 
51
  ---
52
 
53
+ ## Format
54
 
55
+ [Apache Parquet](https://parquet.apache.org/) is binary format that makes filtering and retrieving the data quicker because it lays out the data in columns, which means columns that are unnecessary to satisfy a given query or workflow don't need to be read. Hugging Face's [Datasets](https://huggingface.co/docs/datasets/index) library is an easy way to get started working with the entire dataset, and has features for loading and streaming the data, so you don't need to store it all locally or pay attention to how it's formatted on disk.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  [☝️ Go back to Summary](#summary)
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cold.parquet/part-00000-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00000-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00001-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00001-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00002-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00002-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00003-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00003-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00004-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00004-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00005-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00005-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00006-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00006-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00007-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00007-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00008-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00008-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00009-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00009-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00010-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00010-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00011-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00011-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00012-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00012-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00013-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00013-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00014-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00014-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes
cold.parquet/part-00015-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet → part-00015-1db87b40-dcd1-44cd-a005-6c6d7742d1f8-c000.gz.parquet RENAMED
File without changes