A publicly available benchmark for biomedical dataset retrieval: the reference standard for the 2016 bioCADDIE dataset retrieval challenge

作者：Cohen Trevor^*; Roberts Kirk^*; Gururaj Anupama E; Chen Xiaoling; Pournejati Saeid; Alter George; Hersh William R; Demner Fushman Dina; Ohno Machado Lucila; Xu Hua^*

来源：Database-The Journal of Biological Databases and Curation, 2017, 2017: bax061.

DOI：10.1093/database/bax061

The rapid proliferation of publicly available biomedical datasets has provided abundant resources that are potentially of value as a means to reproduce prior experiments, and to generate and explore novel hypotheses. However, there are a number of barriers to the re- use of such datasets, which are distributed across a broad array of dataset repositories, focusing on different data types and indexed using different terminologies. New methods are needed to enable biomedical researchers to locate datasets of interest within this rapidly expanding information ecosystem, and new resources are needed for the formal evaluation of these methods as they emerge. In this paper, we describe the design and generation of a benchmark for information retrieval of biomedical datasets, which was developed and used for the 2016 bioCADDIE Dataset Retrieval Challenge. In the tradition of the seminal Cranfield experiments, and as exemplified by the Text Retrieval Conference (TREC), this benchmark includes a corpus (biomedical datasets), a set of queries, and relevance judgments relating these queries to elements of the corpus. This paper describes the process through which each of these elements was derived, with a focus on those aspects that distinguish this benchmark from typical information retrieval reference sets. Specifically, we discuss the origin of our queries in the context of a larger collaborative effort, the biomedical and healthCAre Data Discovery Index Ecosystem (bioCADDIE) consortium, and the distinguishing features of biomedical dataset retrieval as a task. The resulting benchmark set has been made publicly available to advance research in the area of biomedical dataset retrieval.

• 出版日期2017-8-18