  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? Are they associated in some other
way? Such relationships between the mapped terms are often not documented,
leading to incorrect assumptions and making them hard to use in scenarios that
require a high degree of precision (such as diagnostics or risk prediction).
Also, the lack of descriptions of how mappings were done makes it hard to
combine and reconcile mappings, particularly curated and automated ones.
  The Simple Standard for Sharing Ontological Mappings (SSSOM) addresses these
problems by: 1. Introducing a machine-readable and extensible vocabulary to
describe metadata that makes imprecision, inaccuracy and incompleteness in
mappings explicit. 2. Defining an easy to use 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 standards. 3.
Implementing open and community-driven collaborative workflows designed to
evolve the standard continuously to address changing requirements and mapping
practices. 4. Providing reference tools and software libraries for working with
the standard.
  In this paper, we present the SSSOM standard, describe several use cases, and
survey some existing work on standardizing the exchange of mappings, with the
goal of making mappings Findable, Accessible, Interoperable, and Reusable
(FAIR). The SSSOM specification is at http://w3id.org/sssom/spec.
