https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/Head https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/assertion https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/provenance https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/pubinfo https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/assertion https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0 http://purl.org/dc/terms/abstract Symbolic approaches to artificial intelligence represent things within a domain of knowledge through physical symbols, combine symbols into symbol ex- pressions, and manipulate symbols and symbol expressionsNN through inference processes. While a large part of Data Science relies on statistics and applies statisti- cal approaches to artificial intelligence, there is an increasing potential for success- fully applying symbolic approaches as well. Symbolic representations and sym- bolic inference are close to human cognitive representations and therefore compre- hensible and interpretable; they are widely used to represent data and metadata, and their specific semantic content must be taken into account for analysis of such in- formation; and human communication largely relies on symbols, making symbolic representations a crucial part in the analysis of natural language. Here we discuss the role symbolic representations and inference can play in Data Science, high- light the research challenges from the perspective of the data scientist, and argue that symbolic methods should become a crucial component of the data scientists’ toolbox. https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0 http://purl.org/dc/terms/date 2017-04-10 https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0 http://purl.org/dc/terms/title Data Science and Symbolic AI: synergies, challenges and opportunities https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/PositionPaper https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Preprint https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0 https://vocab.org/frbr/core#term-revisionOf https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities https://orcid.org/0000-0001-8149-5890 http://schema.org/affiliation https://ror.org/01q3tbs38 https://orcid.org/0000-0001-8149-5890 http://schema.org/email robert.hoehndorf@kaust.edu.sa https://orcid.org/0000-0001-8149-5890 http://xmlns.com/foaf/0.1/name Robert Hoehndorf https://orcid.org/0000-0003-0169-8159 http://schema.org/affiliation https://ror.org/02dxx6824 https://orcid.org/0000-0003-0169-8159 http://xmlns.com/foaf/0.1/name Núria Queralt-Rosinach https://ror.org/01q3tbs38 http://xmlns.com/foaf/0.1/name Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. Computer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia https://ror.org/02dxx6824 http://xmlns.com/foaf/0.1/name Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, USA https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/author-list http://www.w3.org/1999/02/22-rdf-syntax-ns#_1 https://orcid.org/0000-0001-8149-5890 https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/author-list__1 http://www.w3.org/1999/02/22-rdf-syntax-ns#_2 https://orcid.org/0000-0003-0169-8159 https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/provenance https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/assertion http://www.w3.org/ns/prov#wasAttributedTo https://orcid.org/0000-0001-8149-5890 https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/assertion http://www.w3.org/ns/prov#wasAttributedTo 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