Please name your PR after the issue it closes. You can use the following line: "Closes #ISSUE-NUMBER" where you replace the ISSUE-NUMBER with the one corresponding to your dataset.

If the following information is NOT present in the issue, please populate:

• Name: name of the dataset
• Description: short description of the dataset (or link to social media or blog post)
• Paper: link to the dataset paper if available
• Data: link to the online home of the dataset

Checkbox

• [x] Confirm that this PR is linked to the dataset issue.
• [x] Create the dataloader script biodatasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [x] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _BIGBIO_VERSION variables.
• [x] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [x] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one BigBioConfig for the source schema and one for a bigbio schema.
• [x] Confirm dataloader script works with datasets.load_dataset function.
• [x] Confirm that your dataloader script passes the test suite run with python -m tests.test_bigbio biodatasets/my_dataset/my_dataset.py.

• Name: PubTator Central
• Description: PubTator Central (PTC, https://www.ncbi.nlm.nih.gov/research/pubtator/) is a web service for exploring and retrieving bioconcept annotations in full text biomedical articles. PTC provides automated annotations from state-of-the-art text mining systems for genes/proteins, genetic variants, diseases, chemicals, species and cell lines, all available for immediate download.
• Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692066/
• Data: https://ftp.ncbi.nlm.nih.gov/pub/lu/PubTatorCentral/

Checkbox

• [X] Confirm that this PR is linked to the dataset issue.
• [X] Create the dataloader script biodatasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [x] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _BIGBIO_VERSION variables.
• [X] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [X] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one BigBioConfig for the source schema and one for a bigbio schema.
• [X] Confirm dataloader script works with datasets.load_dataset function.
• [x] Confirm that your dataloader script passes the test suite run with python -m tests.test_bigbio biodatasets/my_dataset/my_dataset.py.

Closes #222.

Closes #156

Local dataset, output in file: test_log.txt

Dataset is of task Word Sense Disambiguation fitted into Tasks.NAMED_ENTITY_DISAMBIGUATION. There was a discussion starting from here.

There are a lot of mismatches between entity and offset, this is intended as there can be slight variations of ambiguous word/word in text (in case, singular/plural, ...).

Adding a Dataset

• Name: MedHop
• Description: None provided
• Task: QA
• Paper: https://transacl.org/ojs/index.php/tacl/article/viewFile/1325/299
• Data: http://qangaroo.cs.ucl.ac.uk
• License: CC BY-SA 3.0

• Name: CODIESP
• Description: Collection of 1,000 manually selected clinical case studies in Spanish.
• Paper: link to the dataset paper
• Data: link to the online home of the dataset

Checkbox

• [x] Confirm that this PR is linked to the dataset issue.
• [x] Create the dataloader script biodatasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [x] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _BIGBIO_VERSION variables.
• [x] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [x] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one BigBioConfig for the source schema and one for a bigbio schema.
• [x] Confirm dataloader script works with datasets.load_dataset function.
• [x] Confirm that your dataloader script passes the test suite run with python -m tests.test_bigbio biodatasets/my_dataset/my_dataset.py.
• [x] If my dataset is local, I have provided an output of the unit-tests in the PR (please copy paste). This is OPTIONAL for public datasets, as we can test these without access to the data files.

The idea is to have classes for different type of licenses whit each license having a subset of available parameters: name, type, version, link, description.

This entails replacing:

_LICENSE = "CC BY-NC-SA"
_LICENSE= "CC BY-NC-SA 3.0"

With

from bigbio.utils import license
_LICENSE = license.CreativeCommons(type="BY-NC-SA")
_LICENSE = license.CreativeCommons(type="BY-NC-SA", version=3.0)

and

return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license= str(_LICENSE),
            citation=_CITATION,
        )

Special ones are Custom for dataset-specific license and PubliclyAvailable for those datasets which can be freely downloaded but do not provide license information.

Please name your PR after the issue it closes. You can use the following line: "Closes #ISSUE-NUMBER" where you replace the ISSUE-NUMBER with the one corresponding to your dataset.

If the following information is NOT present in the issue, please populate:

• Name: name of the dataset
• Description: short description of the dataset (or link to social media or blog post)
• Paper: link to the dataset paper if available
• Data: link to the online home of the dataset

Checkbox

• [x] Confirm that this PR is linked to the dataset issue.
• [x] Create the dataloader script biodatasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [x] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _BIGBIO_VERSION variables.
• [x] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [x] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one BigBioConfig for the source schema and one for a bigbio schema.
• [x] Confirm dataloader script works with datasets.load_dataset function.
• [x] Confirm that your dataloader script passes the test suite run with python -m tests.test_bigbio biodatasets/my_dataset/my_dataset.py.
• [x] If my dataset is local, I have provided an output of the unit-tests in the PR (please copy paste). This is OPTIONAL for public datasets, as we can test these without access to the data files.

(bigscience-biomedical) root@docker-desktop:/workspaces/biomedical# python -m tests.test_bigbio biodatasets/n2c2_2014/n2c2_2014.py --data_dir /workspaces/biomedical/biodatasets/n2c2_2014/tar_gz
INFO:__main__:args: Namespace(path='biodatasets/n2c2_2014/n2c2_2014.py', schema=None, subset_id=None, data_dir='/workspaces/biomedical/biodatasets/n2c2_2014/tar_gz', use_auth_token=None)
INFO:__main__:self.PATH: biodatasets/n2c2_2014/n2c2_2014.py
INFO:__main__:self.SUBSET_ID: n2c2_2014
INFO:__main__:self.SCHEMA: None
INFO:__main__:self.DATA_DIR: /workspaces/biomedical/biodatasets/n2c2_2014/tar_gz
INFO:__main__:Checking for _SUPPORTED_TASKS ...
INFO:__main__:Found _SUPPORTED_TASKS=[<Tasks.NAMED_ENTITY_RECOGNITION: 'NER'>, <Tasks.TEXT_CLASSIFICATION: 'TXTCLASS'>]
INFO:__main__:_SUPPORTED_TASKS implies _MAPPED_SCHEMAS={'KB', 'TEXT'}
INFO:__main__:schemas_to_check: {'KB', 'TEXT'}
INFO:__main__:Checking load_dataset with config name n2c2_2014_source
WARNING:datasets.builder:Using custom data configuration n2c2_2014_source-57e9df040ed9f011
Downloading and preparing dataset n2c2_2014/n2c2_2014_source to /home/jovyan/.cache/huggingface/datasets/n2c2_2014/n2c2_2014_source-57e9df040ed9f011/1.0.0/1e3e609086987a589ee6db853ac5c55fe73648c31096f144bb0dbbd670cb2f72...
Dataset n2c2_2014 downloaded and prepared to /home/jovyan/.cache/huggingface/datasets/n2c2_2014/n2c2_2014_source-57e9df040ed9f011/1.0.0/1e3e609086987a589ee6db853ac5c55fe73648c31096f144bb0dbbd670cb2f72. Subsequent calls will reuse this data.
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 282.37it/s]
INFO:__main__:Checking load_dataset with config name n2c2_2014_bigbio_kb
WARNING:datasets.builder:Using custom data configuration n2c2_2014_bigbio_kb-57e9df040ed9f011
Downloading and preparing dataset n2c2_2014/n2c2_2014_bigbio_kb to /home/jovyan/.cache/huggingface/datasets/n2c2_2014/n2c2_2014_bigbio_kb-57e9df040ed9f011/1.0.0/1e3e609086987a589ee6db853ac5c55fe73648c31096f144bb0dbbd670cb2f72...
Dataset n2c2_2014 downloaded and prepared to /home/jovyan/.cache/huggingface/datasets/n2c2_2014/n2c2_2014_bigbio_kb-57e9df040ed9f011/1.0.0/1e3e609086987a589ee6db853ac5c55fe73648c31096f144bb0dbbd670cb2f72. Subsequent calls will reuse this data.
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 384.62it/s]
INFO:__main__:Checking load_dataset with config name n2c2_2014_bigbio_text
WARNING:datasets.builder:Using custom data configuration n2c2_2014_bigbio_text-57e9df040ed9f011
Downloading and preparing dataset n2c2_2014/n2c2_2014_bigbio_text to /home/jovyan/.cache/huggingface/datasets/n2c2_2014/n2c2_2014_bigbio_text-57e9df040ed9f011/1.0.0/1e3e609086987a589ee6db853ac5c55fe73648c31096f144bb0dbbd670cb2f72...
Dataset n2c2_2014 downloaded and prepared to /home/jovyan/.cache/huggingface/datasets/n2c2_2014/n2c2_2014_bigbio_text-57e9df040ed9f011/1.0.0/1e3e609086987a589ee6db853ac5c55fe73648c31096f144bb0dbbd670cb2f72. Subsequent calls will reuse this data.
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 514.01it/s]
INFO:__main__:Checking global ID uniqueness
INFO:__main__:Found 12490 unique IDs
INFO:__main__:Gathering schema statistics
INFO:__main__:Gathering schema statistics
train
==========
id: 790
document_id: 790
passages: 790
entities: 17405
normalized: 0
events: 0
coreferences: 0
relations: 0

test
==========
id: 514
document_id: 514
passages: 514
entities: 11462
normalized: 0
events: 0
coreferences: 0
relations: 0

INFO:__main__:Checking if referenced IDs are properly mapped
INFO:__main__:KB ONLY: Checking passage offsets
INFO:__main__:KB ONLY: Checking entity offsets

<SPECIFIC ERRORS ARE HIDDEN> 

There are features with wrong offsets! This is not a hard failure, as it is common for this type of datasets. However, if the error list is long (e.g. >10) you should double check your code. 


INFO:__main__:KB ONLY: Checking event offsets
INFO:__main__:KB ONLY: Checking coref offsets
INFO:__main__:Checking global ID uniqueness
INFO:__main__:Found 514 unique IDs
INFO:__main__:Gathering schema statistics
INFO:__main__:Gathering schema statistics
train
==========
id: 790
document_id: 790
text: 790
labels: 16501

test
==========
id: 514
document_id: 514
text: 514
labels: 10970

.
----------------------------------------------------------------------
Ran 1 test in 11.258s

OK

Closes #246

• Description: PsyTAR dataset contains 891 drugs reviews posted by patients on "askapatient.com", about the effectiveness and adverse drug events associated with Zoloft, Lexapro, Cymbalta, and Effexor XR.

Checkbox

• [x] Confirm that this PR is linked to the dataset issue.
• [x] Create the dataloader script biodatasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [x] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _BIGBIO_VERSION variables.
• [x] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [x] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one BigBioConfig for the source schema and one for a bigbio schema.
• [x] Confirm dataloader script works with datasets.load_dataset function.
• [x] Confirm that your dataloader script passes the test suite run with python -m tests.test_bigbio biodatasets/my_dataset/my_dataset.py.

• Name: Bio-SimLex
• Description: Noun pairs with similarity scores
• Task: Semantic Similarity
• Paper: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2039-z
• Data: https://github.com/cambridgeltl/bio-simverb/tree/master/wvlib/word-similarities/bio-simlex
• License: ?
• Motivation: Evaluation

Closes #217

Task of dataset is Relation Extraction, however it was part of a challenge where the correct answers to the test set were never released. Since data["test"]["relations"] is thus empty for the testset the test fails with:

ERROR: runTest (__main__.TestDataLoader)
Run all tests that check:
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\Users\ottsi\biomedical\tests\test_bigbio.py", line 116, in runTest
    self.test_schema(schema)
  File "C:\Users\ottsi\biomedical\tests\test_bigbio.py", line 518, in test_schema
    self.assertTrue(self._check_subkey(example[key][0], attrs))
IndexError: list index out of range

----------------------------------------------------------------------
Ran 1 test in 1.195s

FAILED (errors=1)

Edit: On second thought I think this might be a bug in the test-script, since it is assumed that a required subkey has to have elements in it. F.e. also in NER there could be documents without any entities at all in them.

Closes #137

Checkbox

• [x] Confirm that this PR is linked to the dataset issue.
• [x] Create the dataloader script biodatasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [x] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _BIGBIO_VERSION variables.
• [x] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [x] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one BigBioConfig for the source schema and one for a bigbio schema.
• [x] Confirm dataloader script works with datasets.load_dataset function.
• [ ] Confirm that your dataloader script passes the test suite run with python -m tests.test_bigbio biodatasets/my_dataset/my_dataset.py.
• [ ] If my dataset is local, I have provided an output of the unit-tests in the PR (please copy paste). This is OPTIONAL for public datasets, as we can test these without access to the data files.

Add the Paragraph-Level Simplification of Medical Texts dataset. Closes #854

Checkbox

• [X] Confirm that this PR is linked to the dataset issue.
• [X] Create the dataloader script biodatasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [X] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _BIGBIO_VERSION variables.
• [X] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [X] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one BigBioConfig for the source schema and one for a bigbio schema.
• [X] Confirm dataloader script works with datasets.load_dataset function.
• [X] Confirm that your dataloader script passes the test suite run with python -m tests.test_bigbio biodatasets/my_dataset/my_dataset.py.
• [X] If my dataset is local, I have provided an output of the unit-tests in the PR (please copy paste). This is OPTIONAL for public datasets, as we can test these without access to the data files.

Adding a Dataset

• Name: Paragraph-level Simplification of Medical Texts
• Description: A paired dataset of technical medical abstracts and their plain-language summarizations.
• Task: SUM
• Paper: https://arxiv.org/abs/2104.05767
• Data: https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts
• License: CC_BY_4p0
• Motivation: High-quality summarization dataset for translating biomedical technical language -> layman's terms

This PR improves the implementation of the BioRed corpus:

• In the previous implementation a unique entity was created per entity mention and database identifier. This was fixed to a single entity mention having multiple database ids.
• Furthermore, the name of the database a entity is linked to was added
• BioRed only provides abstract-level annotations for entity-linked relation pairs rather than materializing links between all surface form mentions of relation. Analogous to BC5CDR we enumerate all mention pairs concerning the entities in the triple.

Enables unit testing of local scripts with --test_local flag; borrows the test_bigbio_hub.py script. I tested this by making a copy of scitail as test_scitail in the biodatasets folder, and

To replicate:

• copy the scitail folder in bigbio/biodatasets as cp -r bigbio/biodatasets/scitail bigbio/biodatasets/test_scitail.
• change the name of scitail.py in this folder as test_scitail.py
• add bigbiohub.py into this new test_scitail folder
• in the main directory, run python -m tests.test_bigbio_hub test_scitail --test_local

Note- the contributions guide makes a reference to the templates folder that has 2 scripts; bigbiohub and a template file that can be used to fill-in-the-blanks. To avoid a deprecated script, maybe we should automate that for every new update, bigbiohub is either copied into the template folder OR I can just change the tutorial to reflect it's actual "default" location of bigbio/hub/bigbiohub.py

TODO: on 2023/01/03 I'm going to add one more small change that also tests whether the METADATA is in the acceptable set of values to ensure standardization!

@galtay

Adding a Dataset

• Name: CPI
• Description: The compound-protein relationship (CPI) dataset consists of 2,613 sentences from abstracts containing
  annotations of proteins, small molecules, and their relationships
• Task: NER,RE,NEN
• Paper: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220925
• Data: https://github.com/KerstenDoering/CPI-Pipeline
• License: ISC
• Motivation: High quality NER and RE annotations

Adding a Dataset

• Name: DrugProt
• Description: https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-1/
• Task: NER, RE
• Paper: https://biocreative.bioinformatics.udel.edu/media/store/files/2021/Track1_pos_1_BC7_overview.pdf
• Data: https://zenodo.org/record/5119892#.Y6A4RtLMKV4
• License: Creative Commons Attribution 4.0 International
• Motivation: High-quality annotations for NER and RE