Nanopublication

ID

https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY
Formats

Content

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@prefix sub: <https://w3id.org/np/RA9oo9RIbNIT1l_5fgHBKvnGhfmLbc0t1wyOWl5EVuGEY/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix nt: <https://w3id.org/np/o/ntemplate/> .
@prefix npx: <http://purl.org/nanopub/x/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix orcid: <https://orcid.org/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .

sub:Head {
  this: a np:Nanopublication;
    np:hasAssertion sub:assertion;
    np:hasProvenance sub:provenance;
    np:hasPublicationInfo sub:pubinfo .
}

sub:assertion {
  <https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0>
    a <http://purl.org/spar/fabio/PositionPaper>, <http://purl.org/spar/fabio/Preprint>;
    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";
    <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 {
  sub:assertion prov:wasAttributedTo orcid:0000-0001-8149-5890, orcid:0000-0003-0169-8159 .
}

sub:pubinfo {
  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" .
  
  this: dct:created "2025-05-26T10:11:16.457Z"^^xsd:dateTime;
    dct:creator orcid:0000-0002-1267-0234;
    dct:license <https://creativecommons.org/licenses/by/4.0/>;
    npx:hasNanopubType <http://purl.org/spar/fabio/Preprint>;
    npx:introduces <https://datasciencehub.net/paper/data-science-and-symbolic-ai-synergies-challenges-and-opportunities-0>;
    npx:wasCreatedAt <https://nanodash.knowledgepixels.com/>;
    <http://purl.org/ontology/bibo/authorList> sub:author-list;
    rdfs:label "Preprint: Data Science and Symbolic AI: synergies, challenges and opportunities";
    nt:wasCreatedFromProvenanceTemplate <https://w3id.org/np/RAekcN47h13fk6ZK4XiObgGgk-qB01sLOjyGyhMCq_jT4>;
    nt:wasCreatedFromPubinfoTemplate <https://w3id.org/np/RA0J4vUn_dekg-U1kK3AOEt02p9mT2WO03uGxLDec1jLw>,
      <https://w3id.org/np/RA16U9Wo30ObhrK1NzH7EsmVRiRtvEuEA_Dfc-u8WkUCA>, <https://w3id.org/np/RAYrlN4s93vVe9LGI-gmPLTb-QZGHKd0mxx8VxJ3XVhuw>,
      <https://w3id.org/np/RAukAcWHRDlkqxk7H2XNSegc1WnHI569INvNr-xdptDGI>;
    nt:wasCreatedFromTemplate <https://w3id.org/np/RAoPQDgI37NCPA3ZmqIMiSLJPf-WHXVHN_fyq1EYl1pAk> .
  
  sub:author-list rdf:_1 orcid:0000-0001-8149-5890;
    rdf:_2 orcid:0000-0003-0169-8159 .
  
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    npx:signedBy orcid:0000-0002-1267-0234 .
}