DIOWG Subgroup on BFO 2020: Difference between revisions
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The primary drawback of temporally unspecified relations is that they are massively ambiguous with respect to when they hold. Consider the following statement: | The primary drawback of temporally unspecified relations is that they are massively ambiguous with respect to when they hold. Consider the following statement: | ||
:::Liver01 part_of Lynn | :::Liver01 part_of Lynn | ||
If this appears in an ontology or dataset, it's impossible know whether Liver01 has been a part of Lynn as long as it has existed, whether it became of Lynn at some later point (say, through a transplant), or whether it is still part of Lynn. | If this appears in an ontology or dataset, it's impossible know whether Liver01 has been a part of Lynn as long as it has existed, whether it became of Lynn at some later point (say, through a transplant), or whether it is still part of Lynn. |
Revision as of 12:00, 24 February 2023
The purpose of this page is to provide a record of the thinking and consensus of the BFO 2020 Subgroup of the DIOWG and serve as a reference for those looking to better understand issues surrounding relations in BFO.
The BFO 2020 Subgroup is tasked with reviewing new features in the upcoming version of BFO, BFO 2020 and recommending a policy on relation reuse to the DIOWG. To that end, we have been developing an understanding of the strengths and drawbacks of the temporalized relations strategy compared to the RO relations widely in use in the community.
Relations
This section describes the BFO 2020 Subgroup's consensus on the drawbacks of Temporally Unspecified Relations and Temporalized Relations. In Background, we'll provide some background on the general problem both strategies address and a quick overview of each type of relations.
Background
- Many of the relationships we seek to model hold at some times, but not at others. For instance, someone may be a member of an organization for one year and not be a member of that organization before or after that year.
- We've reviewed two strategies to represent these three-place reference relations using binary OWL relations: temporally unspecified relations and temporalized relations.
- Temporally unspecified relations do not specify when the relation in question holds. The OBO Relations Ontology (RO) notably uses temporally unspecified relations:
- A part_of B
- A member_of B
- We'll refer to this style of relation with the more general 'temporally unspecified' relation because many ontologies within the DoD/IC, such as the Common Core Ontologies (CCO) Extended Relations Ontology and several modules from the Defense Intelligence Core Ontology, use non-RO temporally unspecified relations as well.
- The other strategy we've reviewed is temporalized relations (TRs). Temporalized relations specify whether the relation holds at all times or only at some time in the semantics of the relations:
- A 'has part at some time' B
- A 'has part at some time' B
Note that the at-all-times temporalized relations hold for all times at which A exists, not all times.
- There is a design pattern that allows for the creation of more specific TRs (eg., 'part of in March 20203' or 'part of while machine is operating'), but for current purposes we'll restrict our attention to the generic TRs.
Temporally Unspecified Relations (RO-Style)
Temporal Ambiguity
The primary drawback of temporally unspecified relations is that they are massively ambiguous with respect to when they hold. Consider the following statement:
- Liver01 part_of Lynn
If this appears in an ontology or dataset, it's impossible know whether Liver01 has been a part of Lynn as long as it has existed, whether it became of Lynn at some later point (say, through a transplant), or whether it is still part of Lynn.
This ambiguity poses a number of interoperability and reasoning problems, particularly when aggregating data from a number of sources:
- Failures of transitivity, which can introduce falsehoods during reasoning.
- Property chains will not work as expected, and can also introduce falsehoods.
The severity of these problems will depend on the use case. When aggregating data from multiple sources and using automated reasoning, especially data gathered at different times, these issues can be quite serious. On the other hand, there are common use cases for which these issues are trivial (e.g., where one is using ontology terms to specify a model or to tag data or when datasets are strictly segregated by temporal interval).