https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/Head https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8 http://www.nanopub.org/nschema#hasAssertion https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/assertion https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8 http://www.nanopub.org/nschema#hasProvenance https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/provenance https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8 http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/pubinfo https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/assertion http://id.crossref.org/issn/2451-8492 http://purl.org/dc/terms/title Data Science https://doi.org/10.3233/DS-170001 http://purl.org/dc/terms/abstract Computational manipulation of knowledge is an important, and often under-appreciated, aspect of biomedical Data Science. The first Data Science initiative from the US National Institutes of Health was entitled “Big Data to Knowledge (BD2K).” The main emphasis of the more than $200M allocated to that program has been on “Big Data;” the “Knowledge” component has largely been the implicit assumption that the work will lead to new biomedical knowledge. However, there is long-standing and highly productive work in computational knowledge representation and reasoning, and computational processing of knowledge has a role in the world of Data Science. Knowledge-based biomedical Data Science involves the design and implementation of computer systems that act as if they knew about biomedicine. There are many ways in which a computational approach might act as if it knew something: for example, it might be able to answer a natural language question about a biomedical topic, or pass an exam; it might be able to use existing biomedical knowledge to rank or evaluate hypotheses; it might explain or interpret data in light of prior knowledge, either in a Bayesian or other sort of framework. These are all examples of automated reasoning that act on computational representations of knowledge. After a brief survey of existing approaches to knowledge-based data science, this position paper argues that such research is ripe for expansion, and expanded application. https://doi.org/10.3233/DS-170001 http://purl.org/dc/terms/date 2017-10-17 https://doi.org/10.3233/DS-170001 http://purl.org/dc/terms/isPartOf http://id.crossref.org/issn/2451-8492 https://doi.org/10.3233/DS-170001 http://purl.org/dc/terms/title Knowledge-based biomedical Data Science https://doi.org/10.3233/DS-170001 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/PositionPaper https://orcid.org/0000-0003-1455-3370 http://schema.org/affiliation https://ror.org/03wmf1y16 https://orcid.org/0000-0003-1455-3370 http://schema.org/email Larry.Hunter@UCDenver.edu https://orcid.org/0000-0003-1455-3370 http://xmlns.com/foaf/0.1/name Lawrence E. Hunter https://ror.org/03wmf1y16 http://xmlns.com/foaf/0.1/name Computational Bioscience, University of Colorado School of Medicine, Aurora, CO 80045, USA https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/author-list http://www.w3.org/1999/02/22-rdf-syntax-ns#_1 https://orcid.org/0000-0003-1455-3370 https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/provenance https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/assertion http://www.w3.org/ns/prov#wasAttributedTo https://orcid.org/0000-0003-1455-3370 https://w3id.org/kpxl/ios/ds/np/RAnLA9VQ9VRJiPGq5_C4xlszHbVu-t-pJCo3YDnsq51q8/pubinfo https://orcid.org/0000-0002-1267-0234 http://xmlns.com/foaf/0.1/name Tobias Kuhn https://orcid.org/0000-0003-1455-3370 http://xmlns.com/foaf/0.1/name Lawrence E. 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