Additional data and corpus setting of EMNLP Demo Track 2023 contriubution "DOPA METER - A Tool Suite for Metrical Document Profiling and Aggregation"
Creators: name: Lohr, Christina
Publisher: name: Zenodo
Year: 2023

description: This is additional content for the EMNLP demo contributionChristina Lohr and Udo Hahn. 2023. DOPA METER – A Tool Suite for Metrical Document Profiling and Aggregation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 218–228, Singapore. Association for Computational Linguistics.https://aclanthology.org/2023.emnlp-demo.18/This is the detailed description of data composition and configuration of the mentioned use case.
Open data_EMNLP_2023_DEMO_DOPAMETER.zip and unzip the files.## Use caseThe use case features two languages, English and German, and a collections of six text corpora:* **de.Clin** variety of publicly available German synthetic or real, fully deidentified clinical text corpora:  * [JSynCC (Lohr et al., 2018)](https://aclanthology.org/L18-1201/) (only operative reports)  * [ASSESS (Miñarro Giménez et al., 2019)](https://pubmed.ncbi.nlm.nih.gov/30654902/)  * [BRONCO (Kittner et al., 2021)](https://pubmed.ncbi.nlm.nih.gov/33898938/)  * [GraSCCo (Modersohn et al., 2022)](https://pubmed.ncbi.nlm.nih.gov/36073490/)  * [EX4CDS (Roller et al., 2022)](https://aclanthology.org/2022.lrec-1.248/)  * [CARDIO:DE (Richter-Pechanski et al., 2023)](https://www.nature.com/articles/s41597-023-02128-9)  * [X-ray reports (Dewald et al., 2023)](https://www.thieme-connect.de/products/ejournals/abstract/10.1055/a-2061-6562)* **de.SocMed**: [Technical-Laymen Corpus (TLC)](http://macss.dfki.de/tlc.html) contains medical layman and expert expressions from a patient forum ([Seiffe et al., 2020](https://aclanthology.org/2020.lrec-1.759/)),* **de.Wiki**: medical articles from Wikipedia including info-box data with an ICD-10 code (see details below),* **de.PubMed**: German subset of PuMed abstracts featuring clinical cases (see details below)* **en.Clin**: public corpora supplied for the I2B2 and N2C2 challenge series* **en.SocMed**: 3 English language Twitter corpora with biomedical content  * [BEAR (Wührl and Klinger, 2022)](https://aclanthology.org/2022.lrec-1.472/),  * [CoVERT (Mohr et al., 2022)](https://aclanthology.org/2022.lrec-1.26/),  * [BioClaim (Wührl and Klinger, 2021)](https://aclanthology.org/2021.bionlp-1.15/)## Notes creating collections and corporaNote: The following text corpus reproducing instructions based on Python. Before you run the scripts, check the used imported libraries and install them. ### de.clin* _JSynCC_  * Instructions to rebuild the [JSynCC text corpus](https://aclanthology.org/L18-1201/) available under https://github.com/julielab/jsyncc.  * Here, only operative reports from the following sources are used:    * Siekmann, H., Irlenbusch, L., and Klima, S. (2016). [Operationsberichte Orthopädie und Unfallchirurgie.](https://doi.org/10.1007/978-3-642-20790-7) Springer-Verlag.    * Siekmann, H. and Klima, S. (2013). [Operationsberichte Orthopädie: mit speziellen unfallchirurgisch-orthopädischen Eingriffen.](https://doi.org/10.1007/978-3-642-20790-7) Springer-Verlag.    * Siekmann, H. and Irlenbusch, L. (2012). [Operationsberichte Unfallchirurgie.](https://doi.org/10.1007/978-3-642-20784-6) Springer-Verlag.    * Hagen, Monika. (2005). Operationsberichte für Einsteiger-Chirurgie: Operation vorbereiten—Bericht diktieren. Georg Thieme Verlag.* _ASSESS_  * Download the source file from the whole ASSESS CT text corpus from https://doi.org/10.1371/journal.pone.0209547.s002  * The published text corpus is a table formatted file.  * The used text files are reproduced with code from [ASSESS](de.Clin/ASSESS) directory.* _BRONCO_  * Request a data use agreement, instructions: https://www2.informatik.hu-berlin.de/~leser/bronco/index.html  * The public part of the BRONCO corpus consists of 5 text files without a document structure. The 5 single text files were used as 5 single text documents without further editing.* _GraSCCo_  * Download text files from: https://zenodo.org/records/6539131* _EX4CDS_  * Download text files from: https://drive.google.com/file/d/110DUrMdXqdGAJpaUlub_Lr0w3NXU0v0C/view  * Use the text (txt) files only. Do not use the annotation files from Brat tool (ann files).* _CARDIO:DE_  * Request a data use agreement, instructions: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/data/AFYQDY  * Use the text (txt) files only.* _X-ray reports_  * Download the source file from https://doi.org/10.26068/mhhrpm/20230208-000 (file: Röntgenbefunde nach Frakturen der distalen Fibula.csv)  * The published corpus is a table formatted file.  * The used text files are reproduced with code from [X-ray](de.Clin/X-ray) directory.### de.SocMed* Download the [Technical-Laymen Corpus](http://macss.dfki.de/data/LREC2020/TLC_v01.02.zip).* Extract zip file and use all plain text files ('.txt') and do not use the annotation files from Brat tool ('.ann').### de.Wiki* A German Wikipedia dump was downloaded at February 10, 2023.* Current Wikipedia dumps available under https://dumps.wikimedia.org/dewiki/, where the dump was downloaded.* Wikipedia pages with an ICD-10 code info box were extracted and transformed to plain text files without Wikipedia syntax.* Code to create a corpus of Wikipedia articles with ICD-10 codes and remove the Wikipedia syntax is available under [Wikipedia](./de.Wiki), for more details look into [README.md](./deWiki/README.md).* The used Wikipedia articles with cleansed Wikipedia syntax are provided under [Wikipedia](./de.Wiki).### de.PubMed* For the experiments, there were downloaded [German PubMed abstracts of case descriptions](https://pubmed.ncbi.nlm.nih.gov/?term=Case+Reports%5BPublication+Type%5D+AND+GER%5BLA%5D) (2023/07/19).* PubMed query: `Case Reports[Publication Type] AND GER[LA]`* The automatic download was driven by [Entres API](https://www.ncbi.nlm.nih.gov/books/NBK179288/).* For a detailed procedure how to get the data, look into [README.md](./de.PubMed/README.md).* List of used PMID identifieres: [used_pmids.txt](./de.PubMed/used_pmids.txt).### en.Clin * Registration [DBMI Data Portal](https://portal.dbmi.hms.harvard.edu) is mandatory.* Used corpora are from https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/* Unzip the files and create separated directories for every following text corpus.* 2006: [Deidentification](https://doi.org/10.1197/jamia.M2444) & [Smoking](https://doi.org/10.1197/jamia.M2408)  * The provided text data is xml formatted.  * Use the file `1A/unannotated_records_deid_smoking.xml`.  * To get text files as input use code from [./en.Clin/2006_i2b2/create_2006_i2b2_documents.py](./en.Clin/2006_i2b2/create_2006_i2b2_documents.py)* 2008: [Obesity](https://doi.org/10.1197/jamia.M3115)  * The provided text data is xml formatted.  * Use the files:    * `training_data/obesity_patient_records_training.xml`    * `training_data/obesity_patient_records_training2.xml`    * `test_data/obesity_patient_records_test.xml`  * To get text files as input use code from [./en.Clin/2008_i2b2/create_2008_i2b2_documents.py](./en.Clin/2008_i2b2/create_2008_i2b2_documents.py)* 2009: Medication [Information extraction](https://doi.org/10.1136/jamia.2010.003947) & [Annotation](https://doi.org/10.1136/jamia.2010.004200)  * The provided text files are files without file ending.  * Configure empty file format in DoPa Meter configuration via `"file_formats": [""]`. * 2010: [Relations](https://doi.org/10.1136/amiajnl-2011-000203)  * Use the text files from directory `docs`.* 2011: [Coreference](https://doi.org/10.1136/amiajnl-2011-000784)  * Use the text files from directory `docs`.* 2012: [Temporal Relations](https://doi.org/10.1136/amiajnl-2013-001628)   * Use all `.xml.txt` files.* 2014: [Deidentification](https://doi.org/10.1016/j.jbi.2015.06.007) & [Heart Disease](https://doi.org/10.1016/j.jbi.2015.09.018)  * The provided text data is xml formatted.  * Use the directories:    * `testing-PHI-Gold-fixed`    * `training-PHI-Gold-Set1`    * `training-PHI-Gold-Set2`  * To get text files as input use code from [./en.Clin/2014_i2b2/create_2014_i2b2_documents.py](./en.Clin/2014_i2b2/create_2014_i2b2_documents.py)* 2018: [Clinical Trial Cohort Selection](https://doi.org/10.1093/jamia/ocz163) & [Adverse Drug Events and Medication Extraction](https://doi.org/10.1093/jamia/ocz166)  * Use all '.txt' files.### en.SocMedThis collection combines English language Twitter corpora with biomedical content:* _BEAR_  * Download data from: https://www.ims.uni-stuttgart.de/documents/ressourcen/korpora/bioclaim/WuehrlKlinger-Bioclaim2021.zip  * Enzip the zip file and use the file `corpus/a1.jsonl`.  * Use the code from [./en.SocMed/BEAR/create_BEAR_documents.py](./en.SocMed/BEAR/create_BEAR_documents.py) to create text files.* _BioClaim_  * Download data from: https://www.ims.uni-stuttgart.de/documents/ressourcen/korpora/bioclaim/WuehrlKlinger-Bioclaim2021.zip  * Enzip the zip file and use the files under the `corpus` repository.  * Use the code from [./en.SocMed/BioClaim/create_BioClaim_documents.py](./en.SocMed/BioClaim/create_BioClaim_documents.py) to create text files.* _CoVERT_  * Download data from: https://www.ims.uni-stuttgart.de/documents/ressourcen/korpora/bioclaim/mohr-wuehrl-klinger-2022_covert.zip  * Enzip the zip file and use the file `CoVERT_FC_annotations.jsonl`.  * Use the code from [./en.SocMed/CoVERT/create_CoVERT_documents.py](./en.SocMed/CoVERT/create_CoVERT_documents.py) to create text files.### Configuration of Corpora in DOPA METER* Create a directory with the text files for every corpus of the mentioned collection.* Configure a json file like following code snippet with the definition of the corpora (e.g., name, path name, file ending). This snippet is needed in all configuration files of the here named use case.* The directory [./json_configuration](./json_configuration) contains example configuration files to run DOPA METER.* More details and how to run: https://github.com/dopameter/dopameter