Nanopublication

ID

https://w3id.org/np/RAKXwfrK-hCvg3btuMaAcb0laMNIgUF5OmQUXs5tJwVcM
Formats

Content

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sub:assertion {
  sub:semantics-the-dna-of-biotechnology-data a wd:Q604733;
    dct:description "<span><p><strong>Context</strong></p><ul><li>The biotechnology industry has embraced semantic data in the form of taxonomies and ontologies for several decades. Examples include the Gene Ontology, dating to 1998, and the Cell Ontology, which was initially released in 2004.</li><li>While the use of semantic data on the research and development side of biotechnology is well established, changes in the semantic industry on the business side are evolving more rapidly.</li><li>Many biotechnology companies face the same challenges as other industries when it comes to data:</li><li>Siloed systems with standalone metadata structures.</li><li>Using the wrong systems to manage data and assets.</li><li>Inadequately managed data for use in reporting and analytics.</li></ul><p><em><strong>With the sudden growth and adoption of artificial intelligence, ontologies, knowledge graphs, and semantic layers are being viewed with renewed interest in biotechnology business operations.</strong></em></p><p><strong>Covering</strong></p><ul><li><strong>How</strong> semantics is used in the biotechnology industry.</li><li><strong>How</strong> artificial intelligence is driving semantic adoption to meet marketing use cases.</li><li>The general relevance of what the biotech industry is learning and doing for other managers of semantic data.</li></ul></span>";
    dct:isPartOf <https://w3id.org/spaces/semantic-data-ny/2026>;
    pav:authoredBy <https://orcid.org/0000-0002-8691-6487>;
    rdfs:label "Semantics, the ‘DNA’ of Biotechnology Data";
    rdfs:seeAlso <https://henrystewartconferences.com/session/events-semantic-data-new-york-2026-semantics-dna-biotechnology-data>;
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  <https://orcid.org/0000-0001-8492-0354> foaf:name "Ashley Caselli" .
  
  <https://orcid.org/0000-0002-8691-6487> foaf:name "Ahren Lehnert" .
  
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