Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA).
Abstract. To enable better representations of biomedical argumentation over collections of research papers, we propose a model and a lightweight ontology to represent interpersonal, discourse-based, data-driven reasoning. This model is applied to a collection of scientific documents, to show how it...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.1082.6073 2023-05-15T17:53:35+02:00 Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA). Anita De Waard Jodi Schneider The Pennsylvania State University CiteSeerX Archives 2012 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1082.6073 http://jodischneider.com/pubs/satbi-swim2012.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1082.6073 http://jodischneider.com/pubs/satbi-swim2012.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://jodischneider.com/pubs/satbi-swim2012.pdf text 2012 ftciteseerx 2020-05-03T00:27:09Z Abstract. To enable better representations of biomedical argumentation over collections of research papers, we propose a model and a lightweight ontology to represent interpersonal, discourse-based, data-driven reasoning. This model is applied to a collection of scientific documents, to show how it can be applied in practice. We present three biomedical applications for this work, and suggest connections with other, existing, ontologies and reasoning tools. Specifically, this model offers a lightweight way to connect nanopublication-like formal representations to scientific papers written in natural language. Text Orca Unknown |
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English |
description |
Abstract. To enable better representations of biomedical argumentation over collections of research papers, we propose a model and a lightweight ontology to represent interpersonal, discourse-based, data-driven reasoning. This model is applied to a collection of scientific documents, to show how it can be applied in practice. We present three biomedical applications for this work, and suggest connections with other, existing, ontologies and reasoning tools. Specifically, this model offers a lightweight way to connect nanopublication-like formal representations to scientific papers written in natural language. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Anita De Waard Jodi Schneider |
spellingShingle |
Anita De Waard Jodi Schneider Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA). |
author_facet |
Anita De Waard Jodi Schneider |
author_sort |
Anita De Waard |
title |
Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA). |
title_short |
Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA). |
title_full |
Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA). |
title_fullStr |
Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA). |
title_full_unstemmed |
Formalising uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA). |
title_sort |
formalising uncertainty: an ontology of reasoning, certainty and attribution (orca). |
publishDate |
2012 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1082.6073 http://jodischneider.com/pubs/satbi-swim2012.pdf |
genre |
Orca |
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Orca |
op_source |
http://jodischneider.com/pubs/satbi-swim2012.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1082.6073 http://jodischneider.com/pubs/satbi-swim2012.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766161291119951872 |