ConferenceCall 2022 01 26 and OntologySummit2023/Theme: Difference between pages
Ontolog Forum
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Open community ontologies are increasingly important for science, driven in part by the FAIR data principles which rely on semantic technologies and ontologies and growing commitment to data sharing from granting agencies and publishers. | |||
To a large degree the 15 FAIR guiding principles require enhanced semantics for machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data). Often the semantic aspects of FAIR are particularly difficult for scientists. In practice the development, maintenance, coordination, and use of ontologies (along with other semantic resources) in science can be complex involving an interconnected web of tools, methodologies, standards, various knowledge artifacts and community practices, at the intersection of science, software development, and information management. However the semantic community understands how to handle some of these challenges and is actively engaged in making the use of semantic resources, especially ontologies easier to use. | |||
In this Summit we will ask how to help scientists & researchers make better use of ontologies, and look for answers from a variety of perspectives. The first half of the Summit will draw examples from the [https://obofoundry.org/ Open Bio Ontologies] (OBO) community, followed by a panel to discuss and help digest issues raised in the first half. Following this the second half branches out to other communities, disciplines and practices such as modular approaches to ontology development. Along the way we will consider: specific tools, and associated methods and standards, including: | |||
* Upper level domain reference models such as [https://github.com/OBOFoundry/COB COB] in the BioMedical area; | |||
* | * [http://robot.obolibrary.org/ ROBOT] and [https://github.com/INCATools/ubergraph Ubergraph] (knowledge graph); aided by standards such as [https://mapping-commons.github.io/sssom/ SSSOM]; | ||
* | * General approaches such as ontology design patterns; | ||
** | * Points of convergence such as the [https://github.com/INCATools/ontology-development-kit Ontology Development Kit]; | ||
* | * "Carrots and sticks" such as automated quality metrics and dashboards; | ||
* Making the use of multiple ontologies easier through improved integration; | |||
* The [https://comodide.com/ Comprehensive Modular Ontology IDE] (CoModIDE) and more. | |||
Along with best practices and lessons learned, we will have a panel to discuss current pain points and opportunities for improvement, with an overall goal to share knowledge across the larger ontology community. | |||
Latest revision as of 20:23, 16 December 2022
Open community ontologies are increasingly important for science, driven in part by the FAIR data principles which rely on semantic technologies and ontologies and growing commitment to data sharing from granting agencies and publishers.
To a large degree the 15 FAIR guiding principles require enhanced semantics for machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data). Often the semantic aspects of FAIR are particularly difficult for scientists. In practice the development, maintenance, coordination, and use of ontologies (along with other semantic resources) in science can be complex involving an interconnected web of tools, methodologies, standards, various knowledge artifacts and community practices, at the intersection of science, software development, and information management. However the semantic community understands how to handle some of these challenges and is actively engaged in making the use of semantic resources, especially ontologies easier to use.
In this Summit we will ask how to help scientists & researchers make better use of ontologies, and look for answers from a variety of perspectives. The first half of the Summit will draw examples from the Open Bio Ontologies (OBO) community, followed by a panel to discuss and help digest issues raised in the first half. Following this the second half branches out to other communities, disciplines and practices such as modular approaches to ontology development. Along the way we will consider: specific tools, and associated methods and standards, including:
- Upper level domain reference models such as COB in the BioMedical area;
- ROBOT and Ubergraph (knowledge graph); aided by standards such as SSSOM;
- General approaches such as ontology design patterns;
- Points of convergence such as the Ontology Development Kit;
- "Carrots and sticks" such as automated quality metrics and dashboards;
- Making the use of multiple ontologies easier through improved integration;
- The Comprehensive Modular Ontology IDE (CoModIDE) and more.
Along with best practices and lessons learned, we will have a panel to discuss current pain points and opportunities for improvement, with an overall goal to share knowledge across the larger ontology community.