| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2019 |
| Язык | английский |
|
Тропша Александр , автор
|
|
Балхоф Джеймс , автор
Бизон Крис , автор
Кебеде Яфет , автор
Кокс Стивен , автор
|
| Библиографическое описание на языке оригинала |
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. |
| Аннотация |
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. |
| Ключевые слова |
Pharmacology & Pharmacy; Chemistry; Computer Science |
| Название журнала |
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 |
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=220364 |
Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Тропша Александр |
ru_RU |
| dc.contributor.author |
Балхоф Джеймс |
ru_RU |
| dc.contributor.author |
Бизон Крис |
ru_RU |
| dc.contributor.author |
Кебеде Яфет |
ru_RU |
| dc.contributor.author |
Кокс Стивен |
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/?p_id=220364 |
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 |
Статьи в зарубежных журналах и сборниках |
ru_RU |
|
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