OTTR : Reasonable Ontology Template

OTTR

Reasonable Ontology Templates (OTTR) is a framework and language for representing ontology modelling patterns, and is designed to support interaction with OWL or RDF knowledge bases at a higher level of abstraction, using modelling patterns rather than OWL axioms or RDF triples. This includes:

  • building knowledge bases by instantiating templates;
  • communicating (presenting, transferring and visualising) the knowledge base as a set of template instances at different levels of abstraction; and
  • securing and improving the quality and sustainability of the knowledge base via structural and semantic analysis of the templates used to construct the knowledge base.

Read more in https://ottr.xyz/

Our Approach

We have yet to properly specify and formally evaluate a tool-supported methodology for the development and maintenance of knowledge bases using OTTR templates. However, we believe the abstraction mechanism that OTTR templates provide can work in a similar manner as application programming interfaces (APIs) work for programming and software engineering. We anticipate the following roles for such a methodology:

Template library designer

This is the designer and maintainer of the basic and core template libraries. The job of the library designer is to construct well-designed interfaces, i.e., capture modelling patterns using OTTR templates, for basic RDF and OWL vocabularies, such as the RDF and OWL vocabularies themselves, but also other vocabularies like SKOSDublin CoreBFO, and possibly also special purpose vocabularies like Galen where ontological expertise is required to correctly understand the vocabulary. Hence, this role requires good insight into the underlying logical languages, i.e., RDF and OWL, and the OTTR language. There is currently no special-purpose editor for this role; we recommend that you use your favourite text-editor to create templates “by hand” in stOTTR syntax, and use Lutra to check the correctness of your templates.

Template programmer

The job of the template programmer is to bridge the abstractions over the logical vocabulary created by the template library designer with the conceptualisation of domain experts. The is achieved by creating user-facing templates that combine and restrict already existing templates available in template libraries, to create new templates that capture specific modelling patterns for given tasks. The programmer must have a firm grasp on the users’ needs and task, but need “only” to understand the templates in the library and to lesser extent understand the formal logic that underlies these templates. This requires that the templates in the library are well-documented. The user-facing templates form the interface for data input (and possibly output) that is presented to the domain expert. There is currently no tool support for this role, other than what is available to the library designer. We have ideas for a standalone tool to support the template programmer.

Domain expert

The domain expert is equipped by the template programmer with a well-designed set of user-facing templates. However, for the domain expert these templates present themselves only in the form of structurally simple spreadsheet formats, i.e., tabular forms with column headers and explanations. We assume that it is possible to create such formats that lie close to the domain experts existing conceptualisation of the domain. This would make them easy to understand and use. “Using” means here 1) creating template instances by filling in data row in the tabular format, or 2) using the format as a query, in which the results of the query will be presented as data rows in the same format. The tabOTTR specification and Lutra provide support for this user role.

An input format prepared by the template programmer and filled with data by the domain expert can, using the template expansion mechanism, be consistently translated into a knowledge base using the vocabulary prescribed by the templates. The separation of responsibility between the roles allows a single template library designer to serve multiple template programmers, which in turn can serve multiple domain experts. This fits the skill and tools sets that information modelling projects typically have available, e.g., domain experts are used to working with spreadsheets and rarely have the competence required for working with ontology editors, while there are usually fewer people that have the required logical background and competence for building and maintaining semantic knowledge bases.

Figure 1: Responsibilities and competencies of methodology roles

Results

The technology surrounding and theory underlying OTTR is under active development, and the use of OTTR templates for construction of sustainable knowledge bases is gaining industrial interest.

Different theoretical foundations for OTTR templates have been examined:

  • OTTR templates as RDF macros [4]
  • OTTR templates as parameterised description logic knowledge bases [8

 

Demo

All our publicly available development is available at GitLab: gitlab.com/ottr, where our work is organised into different subgroups and repositories:

For the implemented version of OTTR templates, which is the version presented throughout these webpages, we consider OTTR templates as RDF macros: The OTTR template functionality is implemented as a recursive, non-cyclic macro mechanism for RDF statements, where OTTR template instances are unfolded into a regular RDF or RDF/OWL knowledge base by recursively replacing template instances with their definition. This process terminates with a set of base templates that directly represent a knowledge base on RDF or RDF/OWL format.

Source Code

[Github]

Read more in https://ottr.xyz/

Publications​

  1. Martin G. Skjæveland, Daniel P. Lupp, Leif Harald Karlsen, Johan W. Klüwer: OTTR: Formal Templates for Pattern-Based Ontology Engineering. 349-377. In “Advances in Pattern-based Ontology Engineering”, Studies on the Semantic Web 51, IOS Press 2021, ISBN 978-1-64368-174-0.
  2. Martin G. Skjæveland. The OTTR Template Library. In “Advances in Pattern-based Ontology Engineering”, Studies on the Semantic Web 51, IOS Press 2021, ISBN 978-1-64368-174-0. Presented at the 11th Workshop on Ontology Design and Patterns – WOP2020, co-located with 19th International Semantic Web Conference (ISWC 2020).
  3. Daniel P. Lupp, Melinda Hodkiewicz, and Martin G. Skjæveland. Template Libraries for Industrial Asset Maintenance: A Methodology for Scalable and Maintainable Ontologies. In: Thorsten Liebig, Achille Fokoue, Zhe Wu (eds) Proceedings of the 13th International Workshop on Scalable Semantic Web Knowledge Base Systems co-located with 19th International Semantic Web Conference (ISWC 2020). CEUR. http://ceur-ws.org/Vol-2757/. 2020.
  4. Martin G. Skjæveland, Daniel P. Lupp, Leif Harald Karlsen, and Henrik Forssell. Practical Ontology Pattern Instantiation, Discovery, and Maintenance with Reasonable Ontology TemplatesIn: Vrandečić D. et al. (eds) The Semantic Web—ISWC 2018. ISWC 2018. LNCS vol 11136. Springer. 2018. Nominated for best research paper award.
  5. Martin G. Skjæveland, Daniel P. Lupp, Leif Harald Karlsen, and Henrik Forssell. Practical Ontology Pattern Instantiation, Discovery, and Maintenance with Reasonable Ontology Templates—Demo paper. International Semantic Web Conference (P&D/Industry/BlueSky) 2018
  6. Martin G. Skjæveland, Henrik Forssell, Johan Wilhelm Klüwer, Daniel P. Lupp, Evgenij Thorstensen and Arild Waaler. Pattern-Based Ontology Design and Instantiation with Reasonable Ontology Templates. Research paper presented at 8th Workshop on Ontology Design and Patterns – WOP2017. 2017.
  7. Martin G. Skjæveland, Henrik Forssell, Johan W. Klüwer, Daniel P. Lupp, Evgenij Thorstensen, Arild Waaler. Reasonable Ontology Templates: APIs for OWL. Poster paper presented at International Semantic Web Conference. 2017
  8. Henrik Forssell, Daniel P. Lupp, Martin G. Skjæveland, Evgenij Thorstensen. Reasonable Macros for Ontology Construction and Maintenance. Poster paper presented at the Description Logics workshop. 2017
  9. Christian Kindermann, Martin G. Skjæveland. A Survey of Syntactic Modelling Structures in Biomedical Ontologies In: Monin P. et al. (eds) The Semantic Web—ISWC 2022. ISWC 2022. LNCS to appear.
  10. Christian Kindermann, Daniel P. Lupp, Martin G. Skjæveland, Leif Harald Karlsen: Formal Relations over Ontology Patterns in Templating Frameworks. 120-133. In “Advances in Pattern-based Ontology Engineering”, Studies on the Semantic Web 51, IOS Press 2021, ISBN 978-1-64368-174-0.
  11. Daniel P. Lupp, Leif Harald Karlsen, and Martin G. Skjæveland. Making a Case for Formal Relations over Ontology Patterns. Short paper presented at 9th Workshop on Ontology Design and Patterns – WOP2018. 2018.
  12. Christian Kindermann, Daniel P. Lupp, Uli Sattler, Evgenij Thorstensen. Generating Ontologies from Templates: A Rule-Based Approach for Capturing Regularity In: Description Logics 2018. 2018.

Partners

The framework is available as open source specifications and applications which are in active use by several industrial partners in and outside of SIRIUS, including DNV GL, Aibel, Grundfos and CapGemini.

Acknowledgements

This work was partially supported by the SIRIUS Centre for Scalable Data Access (Research Council of Norway, project 237889)