Dataset Information

A Simple Standard for Sharing Ontological Mappings (SSSOM).

ABSTRACT: 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). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec.

SUBMITTER: Matentzoglu N

PROVIDER: S-EPMC9216545 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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A Simple Standard for Sharing Ontological Mappings (SSSOM).

Matentzoglu Nicolas N Balhoff James P JP Bello Susan M SM Bizon Chris C Brush Matthew M Callahan Tiffany J TJ Chute Christopher G CG Duncan William D WD Evelo Chris T CT Gabriel Davera D Graybeal John J Gray Alasdair A Gyori Benjamin M BM Haendel Melissa M Harmse Henriette H Harris Nomi L NL Harrow Ian I Hegde Harshad B HB Hoyt Amelia L AL Hoyt Charles T CT Jiao Dazhi D Jiménez-Ruiz Ernesto E Jupp Simon S Kim Hyeongsik H Koehler Sebastian S Liener Thomas T Long Qinqin Q Malone James J McLaughlin James A JA McMurry Julie A JA Moxon Sierra S Munoz-Torres Monica C MC Osumi-Sutherland David D Overton James A JA Peters Bjoern B Putman Tim T Queralt-Rosinach Núria N Shefchek Kent K Solbrig Harold H Thessen Anne A Tudorache Tania T Vasilevsky Nicole N Wagner Alex H AH Mungall Christopher J CJ

Database : the journal of biological databases and curation 20220501

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 i ...[more]

PMID: 35616100

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Project description:BackgroundBiological databases store data about laboratory experiments, together with semantic annotations, in order to support data aggregation and retrieval. The exact meaning of such annotations in the context of a database record is often ambiguous. We address this problem by grounding implicit and explicit database content in a formal-ontological framework.MethodsBy using a typical extract from the databases UniProt and Ensembl, annotated with content from GO, PR, ChEBI and NCBI Taxonomy, we created four ontological models (in OWL), which generate explicit, distinct interpretations under the BioTopLite2 (BTL2) upper-level ontology. The first three models interpret database entries as individuals (IND), defined classes (SUBC), and classes with dispositions (DISP), respectively; the fourth model (HYBR) is a combination of SUBC and DISP. For the evaluation of these four models, we consider (i) database content retrieval, using ontologies as query vocabulary; (ii) information completeness; and, (iii) DL complexity and decidability. The models were tested under these criteria against four competency questions (CQs).ResultsIND does not raise any ontological claim, besides asserting the existence of sample individuals and relations among them. Modelling patterns have to be created for each type of annotation referent. SUBC is interpreted regarding maximally fine-grained defined subclasses under the classes referred to by the data. DISP attempts to extract truly ontological statements from the database records, claiming the existence of dispositions. HYBR is a hybrid of SUBC and DISP and is more parsimonious regarding expressiveness and query answering complexity. For each of the four models, the four CQs were submitted as DL queries. This shows the ability to retrieve individuals with IND, and classes in SUBC and HYBR. DISP does not retrieve anything because the axioms with disposition are embedded in General Class Inclusion (GCI) statements.ConclusionAmbiguity of biological database content is addressed by a method that identifies implicit knowledge behind semantic annotations in biological databases and grounds it in an expressive upper-level ontology. The result is a seamless representation of database structure, content and annotations as OWL models.

Dataset Information

A Simple Standard for Sharing Ontological Mappings (SSSOM).

Publications

A Simple Standard for Sharing Ontological Mappings (SSSOM).

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