This preface summarises the first Workshop on the 5th International Workshop on Semantic Web Solutions for Large-scale Biomedical Data Analytics (SeWebMeDa-2022), a co-event with The ESWC 0000-0003-4014-4394 (A. Hasnain); 0000-0003-4262-6872 (T. Robson); 0000-0003-4727-9435 (M. Dumontier) htp:/ceur-ws.org CEUR Workshop Proceedings (CEUR-WS.org) ISN1613-073
CEUR
ceur-ws.org 1. Introduction The fith edition of this International workshop invites papers for life sciences and biomedical data processing, as well as the amalgamation with Linked Data and Semantic Web technologies for better data analytics, knowledge discovery and user-targeted applications. This research contribution should provide useful information for the Knowledge Acquisition research community and the working Data Scientist. This workshop at the Extended Semantic Web Conference ESWC) seeks original contributions describing theoretical and practical methods and techniques that present the anatomy of large-scale linked data infrastructure, which covers: the distributed infrastructure to consume, store and query large volumes of heterogeneous linked data; using indexes and graph aggregation to better understand large linked data graphs, query federation to mix internal and external data sources, and linked data visualisation tools for health care and life sciences. It will further cover topics around data integration, data profiling, data curation, querying, knowledge discovery, ontology mapping / matching / reconciliation and data / ontology visualisation, applications/tools/technologies/techniques for life sciences and biomedical domain. SeWeBMeDA aims to provide researchers in biomedical and life science, an insight and awareness about large-scale data technologies for linked data, which are becoming increasingly important for knowledge discovery in the life sciences domain.
SeWebMeDa-2022: 5th International Workshop on Semantic Web solutions for large-scale biomedical data analytics, CEUR Workshop Proceedings 2. Organisation 2.2. Programme Committee