CEDAR CENTER FOR EXPANDED DATA ANNOTATION AND RETRIEVAL Faster and Better Metadata Authoring using CEDAR's Value Recommendations Marcos Martinez-Romero, Martin J. O’ Connor, Ravi D. Shankar, Maryam Panahiazar, Debra Willrett, Attila L. Egyedi, John Graybeal, and Mark A. Musen Stanford University, Stanford, CA 94305, U.S.A. Scientists metadatacenter.org marcosmr@stanford.edu, martin.oconnor@stanford.edu, rshankar@stanford.edu, marypan@stanford.edu, willrett@stanford.edu, attila.egyedi@stanford.edu, jgraybeal@stanford.edu, musen@stanford.edu CEDAR is supported by grant U54 AI117925 awarded by the National Institute of Allergy and Infectious Diseases through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative (www.bd2k.nih.gov) Metadata Editor stored Metadata Repository 11/2016 ﬁll in templates templates ﬁlled in indexed Search Engine real-time analysis suggest values Decrease authoring time Reusable metadata Increase metadata quality Value Recommender more examples Recommendation score 0 20 40 60 80 100 hepatocellular carcinoma hepatitis C liver cirrhosis carcinoma liver cancer cancer hepatocellular adenoma hepatitis B adenoma alcohol abuse tissue = liver disease = ? Recommendation score 0 20 40 60 80 100 hepatocellular carcinoma lipid metabolism disorder carcinoma lung cancer lymphoma cancer acute myeloid leukemia asthma breast cancer rheumatoid arthritis disease = ? (no context) Recommendation score 0 20 40 60 80 100 lung cancer chronic obstructive pulmonary disease lung squamous cell carcinoma idiopathic pulmonary fibrosis lung adenocarcinoma adenocarcinoma carcinoma cancer non−small cell lung carcinoma pulmonary fibrosis tissue = lung disease = ? Figures above show the top 10 suggestions provided by the Value Recommender for the ‘disease’ ﬁeld of the ‘Biosample Human’ template. These recommendations were generated based on over 35K instances of the ‘BioSample Human’ template CEDAR is developing novel methods and tools to simplify the process by which investigators annotate their experimental data with metadata The ‘BioSample Human’ template contains the ﬁelds used in BioSample for human samples The suggestions provided are context-sensitive, meaning that the values predicted for a particular ﬁeld are generated and ranked based on previously entered values CEDAR’s value recommendation technology leverages existing metadata to make the authoring of high-quality metadata a manageable task The Value Recommender supports both free-text values and controlled terms. In this particular example, the system suggests terms from the Human Disease Ontology (DOID) BioSample is a database from the National Center for Biotechnology Information (NCBI) that captures descriptive information about the biological samples investigated in projects CEDAR’s Value Recommender identiﬁes common patterns in the metadata repository, and generates real-time suggestions for ﬁlling out metadata templates The CEDAR Workbench (cedar.metadatacenter.net) is a set of Web-based tools for the acquisition, storage, search, and reuse of metadata acquisition forms (metadata templates). One of those tools is the Metadata Editor, which allows users to ﬁll in metadata templates with metadata In biomedicine, good metadata is crucial to ﬁnding experimental datasets, to understand how experiments were performed, and to reuse data to conduct new analyses We have enhanced the Metadata Editor with value recommendation capabilities Based on: Panahiazar et al. Context Aware Recommendation Engine for Metadata Submission. First Int Work Capturing Sci Knowl. 2015;3–7.