Ontology based data integration and context-based mining for life sciences

Peddinti V. Gopalacharyulu; Erno Lindfors; Catherine Bounsaythip; Winnie Wefelmeyer; Matej Orešič

Ontology based data integration and context-based mining for life sciences

Peddinti V. Gopalacharyulu, Erno Lindfors, Catherine Bounsaythip, Winnie Wefelmeyer, Matej Orešič (Corresponding author)

Research output: Contribution to conference › Conference article › Scientific

Abstract

Semantic web is a useful framework for accessing heterogeneous data sources, and its supporting technologies have already been utilized for data integration in life science domain. In this context, the primary challenge is to tackle the problem of evolving concepts, which is a similar challenge encountered by cognitive scientists using rule-based formalisms. In our data integration effort, we aim at implementing a restricted semantic web framework, complementing it by conceptual modeling methods.

Original language	English
Number of pages	3
Publication status	Published - 2004
MoE publication type	Not Eligible
Event	World Wide Web Consortium (W3C) Workshop on Semantic Web for Life Sciences - Cambridge, United States Duration: 27 Oct 2004 → 28 Oct 2004

Workshop

Workshop	World Wide Web Consortium (W3C) Workshop on Semantic Web for Life Sciences
Country/Territory	United States
City	Cambridge
Period	27/10/04 → 28/10/04

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Gopalacharyulu, P. V., Lindfors, E., Bounsaythip, C., Wefelmeyer, W., & Orešič, M. (2004). Ontology based data integration and context-based mining for life sciences. Paper presented at World Wide Web Consortium (W3C) Workshop on Semantic Web for Life Sciences, Cambridge, Massachusetts, United States. https://publications.vtt.fi/julkaisut/muut/2004/w3csemweblifesci04.pdf

@conference{a1bc5c1a37594c9f889a4915400af14a,

title = "Ontology based data integration and context-based mining for life sciences",

abstract = "Semantic web is a useful framework for accessing heterogeneous data sources, and its supporting technologies have already been utilized for data integration in life science domain. In this context, the primary challenge is to tackle the problem of evolving concepts, which is a similar challenge encountered by cognitive scientists using rule-based formalisms. In our data integration effort, we aim at implementing a restricted semantic web framework, complementing it by conceptual modeling methods.",

author = "Gopalacharyulu, {Peddinti V.} and Erno Lindfors and Catherine Bounsaythip and Winnie Wefelmeyer and Matej Ore{\v s}i{\v c}",

note = "Published online, no ISBN/ISSN; World Wide Web Consortium (W3C) Workshop on Semantic Web for Life Sciences ; Conference date: 27-10-2004 Through 28-10-2004",

year = "2004",

language = "English",

}

Gopalacharyulu, PV, Lindfors, E, Bounsaythip, C, Wefelmeyer, W & Orešič, M 2004, 'Ontology based data integration and context-based mining for life sciences', Paper presented at World Wide Web Consortium (W3C) Workshop on Semantic Web for Life Sciences, Cambridge, United States, 27/10/04 - 28/10/04. <https://publications.vtt.fi/julkaisut/muut/2004/w3csemweblifesci04.pdf>

Ontology based data integration and context-based mining for life sciences. / Gopalacharyulu, Peddinti V.; Lindfors, Erno; Bounsaythip, Catherine et al.
2004. Paper presented at World Wide Web Consortium (W3C) Workshop on Semantic Web for Life Sciences, Cambridge, Massachusetts, United States.

Research output: Contribution to conference › Conference article › Scientific

TY - CONF

T1 - Ontology based data integration and context-based mining for life sciences

AU - Gopalacharyulu, Peddinti V.

AU - Lindfors, Erno

AU - Bounsaythip, Catherine

AU - Wefelmeyer, Winnie

AU - Orešič, Matej

N1 - Published online, no ISBN/ISSN

PY - 2004

Y1 - 2004

N2 - Semantic web is a useful framework for accessing heterogeneous data sources, and its supporting technologies have already been utilized for data integration in life science domain. In this context, the primary challenge is to tackle the problem of evolving concepts, which is a similar challenge encountered by cognitive scientists using rule-based formalisms. In our data integration effort, we aim at implementing a restricted semantic web framework, complementing it by conceptual modeling methods.

AB - Semantic web is a useful framework for accessing heterogeneous data sources, and its supporting technologies have already been utilized for data integration in life science domain. In this context, the primary challenge is to tackle the problem of evolving concepts, which is a similar challenge encountered by cognitive scientists using rule-based formalisms. In our data integration effort, we aim at implementing a restricted semantic web framework, complementing it by conceptual modeling methods.

M3 - Conference article

T2 - World Wide Web Consortium (W3C) Workshop on Semantic Web for Life Sciences

Y2 - 27 October 2004 through 28 October 2004

ER -

Ontology based data integration and context-based mining for life sciences

Abstract

Workshop

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