TY - JOUR
T1 - A Simple Standard for Sharing Ontological Mappings (SSSOM)
AU - Matentzoglu, Nicolas
AU - Balhoff, James P.
AU - Bello, Susan M.
AU - Bizon, Chris
AU - Brush, Matthew
AU - Callahan, Tiffany J.
AU - Chute, Christopher G.
AU - Duncan, William D.
AU - Evelo, Chris T.
AU - Gabriel, Davera
AU - Graybeal, John
AU - Gray, Alasdair
AU - Gyori, Benjamin M.
AU - Haendel, Melissa
AU - Harmse, Henriette
AU - Harris, Nomi L.
AU - Harrow, Ian
AU - Hegde, Harshad B.
AU - Hoyt, Amelia L.
AU - Hoyt, Charles T.
AU - Jiao, Dazhi
AU - Jiménez-Ruiz, Ernesto
AU - Jupp, Simon
AU - Kim, Hyeongsik
AU - Koehler, Sebastian
AU - Liener, Thomas
AU - Long, Qinqin
AU - Malone, James
AU - McLaughlin, James A.
AU - McMurry, Julie A.
AU - Moxon, Sierra
AU - Munoz-Torres, Monica C.
AU - Osumi-Sutherland, David
AU - Overton, James A.
AU - Peters, Bjoern
AU - Putman, Tim
AU - Queralt-Rosinach, Núria
AU - Shefchek, Kent
AU - Solbrig, Harold
AU - Thessen, Anne
AU - Tudorache, Tania
AU - Vasilevsky, Nicole
AU - Wagner, Alex H.
AU - Mungall, Christopher J.
N1 - Funding Information:
This work was supported by the Office of the Director, National Institutes of Health (R24-OD011883); National Human Genome Research Institute (7RM1HG010860-02); The European Union's Horizon 2020 research and innovation programme [grant numbers 824087 (EOSC-Life) to Q.L., H.H., S.J. and 825575 (EJP-RD) to H.H., S.J.]; Director, Office of Science, Office of Basic Energy Sciences, of the US Department of Energy [DE-AC0205CH11231 to W.D.D., N.L.H., H.B.H., S.M. and C.J.M.]; DARPA Young Faculty Award [W911NF2010255 to C.T.H. and B.M.G.]; Chan- Zuckerberg Initiative award for the Human Cell Atlas Data Coordination Platform [J.A.M. and S.J.]; Open PHACTS [IMI-JU grant no. 115191]; and EMBL-EBI core funds.
Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press.
PY - 2022/5/25
Y1 - 2022/5/25
N2 - Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR).
AB - Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR).
KW - Data Management
KW - Databases, Factual
KW - Metadata
KW - Semantic Web
KW - Workflow
UR - http://www.scopus.com/inward/record.url?scp=85131107158&partnerID=8YFLogxK
U2 - 10.1093/database/baac035
DO - 10.1093/database/baac035
M3 - Article
C2 - 35616100
SN - 1758-0463
VL - 2022
JO - Database
JF - Database
M1 - baac035
ER -