KFU. Card publication. ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources

KAZAN
FEDERAL UNIVERSITY

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ROBOKOP KG AND KGB: INTEGRATED KNOWLEDGE GRAPHS FROM FEDERATED SOURCES

Form of presentation

Articles in international journals and collections

Year of publication

2019

Язык

английский

Authors, employees of KFU

Tropsha Aleksandr , author

Other authors

Balkhof Dzheyms , author

Bizon Kris , author

Kebede Yafet , author

Koks Stiven , author

Bibliographic description in the original language

Tropsha A. ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources / Bizon C., Cox S., Balhoff J., Kebede Y., Wang P., Morton K., Fecho K., Tropsha A. // JOURNAL OF CHEMICAL INFORMATION AND MODELING. - 2019. - T. 59 (12). - p. 4968-4973.

Annotation

A proliferation of data sources has led to the notional existence of an implicit Knowledge Graph (KG) that contains vast amounts of biological knowledge contributed by distributed Application Programming Interfaces (APIs). However, challenges arise when integrating data across multiple APIs due to incompatible semantic types, identifier schemes, and data formats. We present ROBOKOP KG (http://robokopkg.renci.org), which is a KG that was initially built to support the open biomedical question-answering application, ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways) (http://robokop.renci.org). Additionally, we present the ROBOKOP Knowledge Graph Builder (KGB), which constructs the KG and provides an extensible framework to handle graph query over and integration of federated data sources.

Keywords

Pharmacology & Pharmacy; Chemistry; Computer Science

The name of the journal

Journal of Chemical Information and Modeling

URL

https://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=SourceByDais&qid=1&SID=E1yl6cKjP6VQawX9uwc&page=1&doc=1

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=220364&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Tropsha Aleksandr	ru_RU
dc.contributor.author	Balkhof Dzheyms	ru_RU
dc.contributor.author	Bizon Kris	ru_RU
dc.contributor.author	Kebede Yafet	ru_RU
dc.contributor.author	Koks Stiven	ru_RU
dc.date.accessioned	2019-01-01T00:00:00Z	ru_RU
dc.date.available	2019-01-01T00:00:00Z	ru_RU
dc.date.issued	2019	ru_RU
dc.identifier.citation	Tropsha A. ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources / Bizon C., Cox S., Balhoff J., Kebede Y., Wang P., Morton K., Fecho K., Tropsha A. // JOURNAL OF CHEMICAL INFORMATION AND MODELING. - 2019. - T. 59 (12). - p. 4968-4973.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=220364&p_lang=2	ru_RU
dc.description.abstract	Journal of Chemical Information and Modeling	ru_RU
dc.description.abstract	A proliferation of data sources has led to the notional existence of an implicit Knowledge Graph (KG) that contains vast amounts of biological knowledge contributed by distributed Application Programming Interfaces (APIs). However, challenges arise when integrating data across multiple APIs due to incompatible semantic types, identifier schemes, and data formats. We present ROBOKOP KG (http://robokopkg.renci.org), which is a KG that was initially built to support the open biomedical question-answering application, ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways) (http://robokop.renci.org). Additionally, we present the ROBOKOP Knowledge Graph Builder (KGB), which constructs the KG and provides an extensible framework to handle graph query over and integration of federated data sources.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources	ru_RU
dc.type	Articles in international journals and collections	ru_RU