Scientific lenses to support multiple views over linked chemistry data

Colin Batchelor; Christian Y.A. Brenninkmeijer; Christine Chichester; Mark Davies; Daniela Digles; Ian Dunlop; Chris T. Evelo; Anna Gaulton; Carole Goble; Alasdair J.G. Gray; Paul Groth; Lee Harland; Karen Karapetyan; Antonis Loizou; John P. Overington; Steve Pettifer; Jon Steele; Robert Stevens; Valery Tkachenko; Andra Waagmeester; Antony Williams; Egon L. Willighagen

doi:10.1007/978-3-319-11964-9

Scientific lenses to support multiple views over linked chemistry data

Colin Batchelor, Christian Y.A. Brenninkmeijer, Christine Chichester, Mark Davies, Daniela Digles, Ian Dunlop, Chris T. Evelo, Anna Gaulton, Carole Goble, Alasdair J.G. Gray, Paul Groth, Lee Harland, Karen Karapetyan, Antonis Loizou, John P. Overington, Steve Pettifer, Jon Steele, Robert Stevens, Valery Tkachenko, Andra WaagmeesterAntony Williams, Egon L. Willighagen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

22 Scopus citations

Abstract

When are two entries about a small molecule in different datasets the same? If they have the same drug name, chemical structure, or some other criteria? The choice depends upon the application to which the data will be put. However, existing Linked Data approaches provide a single global view over the data with no way of varying the notion of equivalence to be applied.

In this paper, we present an approach to enable applications to choose the equivalence criteria to apply between datasets. Thus, supporting multiple dynamic views over the Linked Data. For chemical data, we show that multiple sets of links can be automatically generated according to different equivalence criteria and published with semantic descriptions capturing their context and interpretation. This approach has been applied within a large scale public-private data integration platform for drug discovery. To cater for different use cases, the platform allows the application of different lenses which vary the equivalence rules to be applied based on the context and interpretation of the links.

Original language	English
Title of host publication	The SemanticWeb - ISWC 2014 - 13th International SemanticWeb Conference, Proceedings
Editors	Tania Tudorache, Craig Knoblock, Paul Groth, Carole Goble, Chris Welty, Abraham Bernstein, Peter Mika, Denny Vrandečić, Natasha Noy, Krzysztof Janowicz
Publisher	Springer Verlag
Pages	98-113
Number of pages	16
ISBN (Electronic)	9783319119632
DOIs	https://doi.org/10.1007/978-3-319-11964-9
State	Published - 2014
Externally published	Yes
Event	13th International Semantic Web Conference, ISWC 2014 - Riva del Garda, Italy Duration: Oct 19 2014 → Oct 23 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8796
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Semantic Web Conference, ISWC 2014
Country/Territory	Italy
City	Riva del Garda
Period	10/19/14 → 10/23/14

Access to Document

10.1007/978-3-319-11964-9

Cite this

Batchelor, C., Brenninkmeijer, C. Y. A., Chichester, C., Davies, M., Digles, D., Dunlop, I., Evelo, C. T., Gaulton, A., Goble, C., Gray, A. J. G., Groth, P., Harland, L., Karapetyan, K., Loizou, A., Overington, J. P., Pettifer, S., Steele, J., Stevens, R., Tkachenko, V., ... Willighagen, E. L. (2014). Scientific lenses to support multiple views over linked chemistry data. In T. Tudorache, C. Knoblock, P. Groth, C. Goble, C. Welty, A. Bernstein, P. Mika, D. Vrandečić, N. Noy, & K. Janowicz (Eds.), The SemanticWeb - ISWC 2014 - 13th International SemanticWeb Conference, Proceedings (pp. 98-113). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8796). Springer Verlag. https://doi.org/10.1007/978-3-319-11964-9

Batchelor, Colin ; Brenninkmeijer, Christian Y.A. ; Chichester, Christine et al. / Scientific lenses to support multiple views over linked chemistry data. The SemanticWeb - ISWC 2014 - 13th International SemanticWeb Conference, Proceedings. editor / Tania Tudorache ; Craig Knoblock ; Paul Groth ; Carole Goble ; Chris Welty ; Abraham Bernstein ; Peter Mika ; Denny Vrandečić ; Natasha Noy ; Krzysztof Janowicz. Springer Verlag, 2014. pp. 98-113 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Scientific lenses to support multiple views over linked chemistry data",

abstract = "When are two entries about a small molecule in different datasets the same? If they have the same drug name, chemical structure, or some other criteria? The choice depends upon the application to which the data will be put. However, existing Linked Data approaches provide a single global view over the data with no way of varying the notion of equivalence to be applied.In this paper, we present an approach to enable applications to choose the equivalence criteria to apply between datasets. Thus, supporting multiple dynamic views over the Linked Data. For chemical data, we show that multiple sets of links can be automatically generated according to different equivalence criteria and published with semantic descriptions capturing their context and interpretation. This approach has been applied within a large scale public-private data integration platform for drug discovery. To cater for different use cases, the platform allows the application of different lenses which vary the equivalence rules to be applied based on the context and interpretation of the links.",

author = "Colin Batchelor and Brenninkmeijer, {Christian Y.A.} and Christine Chichester and Mark Davies and Daniela Digles and Ian Dunlop and Evelo, {Chris T.} and Anna Gaulton and Carole Goble and Gray, {Alasdair J.G.} and Paul Groth and Lee Harland and Karen Karapetyan and Antonis Loizou and Overington, {John P.} and Steve Pettifer and Jon Steele and Robert Stevens and Valery Tkachenko and Andra Waagmeester and Antony Williams and Willighagen, {Egon L.}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 13th International Semantic Web Conference, ISWC 2014 ; Conference date: 19-10-2014 Through 23-10-2014",

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doi = "10.1007/978-3-319-11964-9",

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Batchelor, C, Brenninkmeijer, CYA, Chichester, C, Davies, M, Digles, D, Dunlop, I, Evelo, CT, Gaulton, A, Goble, C, Gray, AJG, Groth, P, Harland, L, Karapetyan, K, Loizou, A, Overington, JP, Pettifer, S, Steele, J, Stevens, R, Tkachenko, V, Waagmeester, A, Williams, A & Willighagen, EL 2014, Scientific lenses to support multiple views over linked chemistry data. in T Tudorache, C Knoblock, P Groth, C Goble, C Welty, A Bernstein, P Mika, D Vrandečić, N Noy & K Janowicz (eds), The SemanticWeb - ISWC 2014 - 13th International SemanticWeb Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8796, Springer Verlag, pp. 98-113, 13th International Semantic Web Conference, ISWC 2014, Riva del Garda, Italy, 10/19/14. https://doi.org/10.1007/978-3-319-11964-9

Scientific lenses to support multiple views over linked chemistry data. / Batchelor, Colin; Brenninkmeijer, Christian Y.A.; Chichester, Christine et al.
The SemanticWeb - ISWC 2014 - 13th International SemanticWeb Conference, Proceedings. ed. / Tania Tudorache; Craig Knoblock; Paul Groth; Carole Goble; Chris Welty; Abraham Bernstein; Peter Mika; Denny Vrandečić; Natasha Noy; Krzysztof Janowicz. Springer Verlag, 2014. p. 98-113 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8796).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Brenninkmeijer, Christian Y.A.

AU - Chichester, Christine

AU - Davies, Mark

AU - Digles, Daniela

AU - Dunlop, Ian

AU - Evelo, Chris T.

AU - Gaulton, Anna

AU - Goble, Carole

AU - Gray, Alasdair J.G.

AU - Groth, Paul

AU - Harland, Lee

AU - Karapetyan, Karen

AU - Loizou, Antonis

AU - Overington, John P.

AU - Pettifer, Steve

AU - Steele, Jon

AU - Stevens, Robert

AU - Tkachenko, Valery

AU - Waagmeester, Andra

AU - Williams, Antony

AU - Willighagen, Egon L.

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PY - 2014

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N2 - When are two entries about a small molecule in different datasets the same? If they have the same drug name, chemical structure, or some other criteria? The choice depends upon the application to which the data will be put. However, existing Linked Data approaches provide a single global view over the data with no way of varying the notion of equivalence to be applied.In this paper, we present an approach to enable applications to choose the equivalence criteria to apply between datasets. Thus, supporting multiple dynamic views over the Linked Data. For chemical data, we show that multiple sets of links can be automatically generated according to different equivalence criteria and published with semantic descriptions capturing their context and interpretation. This approach has been applied within a large scale public-private data integration platform for drug discovery. To cater for different use cases, the platform allows the application of different lenses which vary the equivalence rules to be applied based on the context and interpretation of the links.

AB - When are two entries about a small molecule in different datasets the same? If they have the same drug name, chemical structure, or some other criteria? The choice depends upon the application to which the data will be put. However, existing Linked Data approaches provide a single global view over the data with no way of varying the notion of equivalence to be applied.In this paper, we present an approach to enable applications to choose the equivalence criteria to apply between datasets. Thus, supporting multiple dynamic views over the Linked Data. For chemical data, we show that multiple sets of links can be automatically generated according to different equivalence criteria and published with semantic descriptions capturing their context and interpretation. This approach has been applied within a large scale public-private data integration platform for drug discovery. To cater for different use cases, the platform allows the application of different lenses which vary the equivalence rules to be applied based on the context and interpretation of the links.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 113

BT - The SemanticWeb - ISWC 2014 - 13th International SemanticWeb Conference, Proceedings

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A2 - Knoblock, Craig

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A2 - Goble, Carole

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A2 - Vrandečić, Denny

A2 - Noy, Natasha

A2 - Janowicz, Krzysztof

PB - Springer Verlag

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Batchelor C, Brenninkmeijer CYA, Chichester C, Davies M, Digles D, Dunlop I et al. Scientific lenses to support multiple views over linked chemistry data. In Tudorache T, Knoblock C, Groth P, Goble C, Welty C, Bernstein A, Mika P, Vrandečić D, Noy N, Janowicz K, editors, The SemanticWeb - ISWC 2014 - 13th International SemanticWeb Conference, Proceedings. Springer Verlag. 2014. p. 98-113. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-11964-9

Scientific lenses to support multiple views over linked chemistry data

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