--- pretty_name: Ohsumed annotations_creators: - expert-generated language_creators: - crowdsourced language: - en license: - cc-by-nc-4.0 multilinguality: - monolingual size_categories: - 100K used for relevance judgements) - mesh_terms: Human-assigned MeSH terms (MH) - title: Title (TI) - publication_type : Publication type (PT) - abstract: Abstract (AB) - author: Author (AU) - source: Source (SO) Note: some abstracts are truncated at 250 words and some references have no abstracts at all (titles only). We do not have access to the full text of the documents. ### Data Splits The files are Train/ Test. Where the training has files from 1987 while the test files has abstracts from 1988-91 Total number of files: Train: 54710 Test: 348567 ## Dataset Creation ### Curation Rationale The OHSUMED document collection was obtained by William Hersh (hersh@OHSU.EDU) and colleagues for the experiments described in the papers below. [Check citation](#citation-information) ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? The test collection was built as part of a study assessing the use of MEDLINE by physicians in a clinical setting (Hersh and Hickam, above). Novice physicians using MEDLINE generated 106 queries. Only a subset of these queries were used in the TREC-9 Filtering Track. Before they searched, they were asked to provide a statement of information about their patient as well as their information need. The data was collected by William Hersh & colleagues ### Annotations #### Annotation process The existing OHSUMED topics describe actual information needs, but the relevance judgements probably do not have the same coverage provided by the TREC pooling process. The MeSH terms do not directly represent information needs, rather they are controlled indexing terms. However, the assessment should be more or less complete and there are a lot of them, so this provides an unusual opportunity to work with a very large topic sample. The topic statements are provided in the standard TREC format #### Who are the annotators? Each query was replicated by four searchers, two physicians experienced in searching and two medical librarians. The results were assessed for relevance by a different group of physicians, using a three point scale: definitely, possibly, or not relevant. The list of documents explicitly judged to be not relevant is not provided here. Over 10% of the query-document pairs were judged in duplicate to assess inter-observer reliability. For evaluation, all documents judged here as either possibly or definitely relevant were considered relevant. TREC-9 systems were allowed to distinguish between these two categories during the learning process if desired. ### Personal and Sensitive Information No PII data is present in the train, test or query files. ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations Dataset provided for research purposes only. Please check dataset license for additional information. ## Additional Information ### Dataset Curators [Aakash Gupta](mailto:aakashg80@gmail.com) *Th!nkEvolve Consulting* and Researcher at CoronaWhy ### Licensing Information CC BY-NC 4.0 ### Citation Information Hersh WR, Buckley C, Leone TJ, Hickam DH, OHSUMED: An interactive retrieval evaluation and new large test collection for research, Proceedings of the 17th Annual ACM SIGIR Conference, 1994, 192-201. Hersh WR, Hickam DH, Use of a multi-application computer workstation in a clinical setting, Bulletin of the Medical Library Association, 1994, 82: 382-389. ### Contributions Thanks to [@skyprince999](https://github.com/skyprince999) for adding this dataset.