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sub:assertion {
  <https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0>
    dct: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.";
    dct:date "2017-04-10";
    dct:title "Data Science and Symbolic AI: synergies, challenges and opportunities";
    a <http://purl.org/spar/fabio/PositionPaper>, <http://purl.org/spar/fabio/Preprint>;
    <https://vocab.org/frbr/core#term-revisionOf> <https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities> .
  
  orcid:0000-0001-8149-5890 <http://schema.org/affiliation> <https://ror.org/01q3tbs38>;
    <http://schema.org/email> "robert.hoehndorf@kaust.edu.sa";
    foaf:name "Robert Hoehndorf" .
  
  orcid:0000-0003-0169-8159 <http://schema.org/affiliation> <https://ror.org/02dxx6824>;
    foaf:name "Núria Queralt-Rosinach" .
  
  <https://ror.org/01q3tbs38> foaf: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> foaf:name "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, USA" .
  
  sub:author-list rdf:_1 orcid:0000-0001-8149-5890 .
  
  sub:author-list__1 rdf:_2 orcid:0000-0003-0169-8159 .
}

sub:provenance {
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  orcid:0000-0001-8149-5890 foaf:name "Robert Hoehndorf" .
  
  orcid:0000-0002-1267-0234 foaf:name "Tobias Kuhn" .
  
  orcid:0000-0003-0169-8159 foaf:name "Núria Queralt-Rosinach" .
  
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    dct:license <https://creativecommons.org/licenses/by/4.0/>;
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    npx:introduces <https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0>;
    npx:wasCreatedAt <https://nanodash.knowledgepixels.com/>;
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    rdfs:label "Preprint: Data Science and Symbolic AI: synergies, challenges and opportunities";
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