Motivation and Purpose

The Ontologies Mapping project has been set up to create better tools or services and to establish best practices for ontology management in the Life Sciences.

Ontologies can include hierarchical relationships; taxonomies; classifications and/or vocabularies which are becoming increasingly important for support of research and development. They have numerous applications such as knowledge management, data integration and text mining where researchers need to analyse large quantities of complex data as part of their daily work. The Ontologies Mapping Project will give users access to standardised tools, methodologies and service which will enable them to map and visualise ontologies, to understand ontology structure, potential overlaps and equivalence of meaning. The impact of this project will be to help users to better integrate, understand and analyse their data more effectively.

Recent Updates

Synergy between Allotrope’s taxonomies & Pistoia Alliance’s Ontologies Mapping work

What’s in a ‘word’, or a collection of them? The answer depends on how much you invest in that collection of words. Standardizing the vocabularies and knowledge collections of experimental data and biomedical concepts has emerged as an important and fundamental activity to allow our industry to fully leverage data and extract the greatest value from it.

Pistoia Alliance Announces Start of Ontologies Mapping Project

The Ontologies Mapping project has been set up to create better tools and establish best practices for ontology management in life sciences R&D. The project will see the Pistoia Alliance develop a set of standardized guidelines, tools and services to enable the universal application of ontologies.

Business case and Project Plan

The idea for the Ontologies Mapping project was proposed through the Pistoia Alliance Ideas Portfolio Platform (IP3) which was selected by the Operations Team and Pistoia Board for development of a formal business case as published in IP3. GSK, Merck & Co, Novartis, Roche and BIOVIA 3DS are funding the project throughout 2016, as shown in the Project Timeline and Deliverables figure.

Phase 1 of the project in 2015 delivered:- 1) the selection of disease, phenotype and experimental investigation domains as "test case" 2) guidelines for best practice and "checklist" to support the application and mapping of source ontologies and 3) requirements for an Ontologies Mapping tool. For phase 2 in 2016, we have 1) developed an RFI process to evaluate existing ontologies mapping tools; 2) organised a new track evaluation of ontology matching algorithms in OM-2016; 3) defined the requirements for an ontologies mapping service and 4) conducted a questionnaire to understand the demand for such a service, potentially for Phase 3 in 2017.

Project structure and Communication

The Project Steering committee (including the funders) is responsible for making decisions, informed by recommendations from the Project Team which executes tasks and makes recommendations. It comprises of Pistoia Alliance members (including the funders) and meets biweekly. The Project Team consults with the Community of Interest each month, which is open to any organisation or individual with relevant skills and experience. The relationship between the three groups is illustrated in the Project Structure and Communication figure.

Community of Interest and Ontologies Guidelines

The project has built a Community of Interest of considerable size and influence in the ontologies field. It has delivered a set of guidelines for best practice and a checklist to exemplify their value. The Ontologies Guidelines for Best Practice are available on a publicly accessible wiki:- https://pistoiaalliance.atlassian.net/wiki/display/PUB/Ontologies+Mapping+Resources

 

Evaluation of Ontologies Mapping Tools through RFI

 

The detailed requirements for an ontologies mapping tool, developed last year, enabled us to evaluate existing tools this year during phase 2 of the project. Seven tool providers participated in the request for information (RFI) to support our systematic evaluation. Details of this process are available on the public project resource wiki. Our RFI evaluation considered 1) tool capability against our requirements and 2) mapping performance for two mapping tasks between two pairs of ontologies in the disease and phenotype domain. Namely, Human Phenotype (HP) Ontology  vs. Mammalian Phenotype (MP) Ontology and Human Disease Ontology (DOID) vs. Orphanet and Rare Diseases Ontology (ORDO).

We identified the top performing tools able to substantially meet our requirements and to match equivalence and similarity. The anonymised results are publicly available, whereas individual tool identity is available only to Pistoia members for internal use. A summary of these results have been presented as poster papers at conferences:- for example ECCB 2016 (https://drive.google.com/open?id=0B7huAtP_riaGRmh5aEt6UnVrNTg) and ISWC 2016 (https://drive.google.com/open?id=0B7huAtP_riaGNzZzOGY0NFA1WWs).

 

Evaluation of Ontology Matching algorithms through OM-2016

Ontology Matching algorithms are fundamental components of any modern Ontologies Mapping tool. To get closer to this substantial community of algorithm developers in a meaningful way, the Ontologies Mapping project team sponsored and organised a new track for this year's annual challenge to evaluate such algorithms, called OM-2016 (website:- http://om2016.ontologymatching.org).

A prize was awarded to the three algorithms (AML, FCA-Map and PhenoNET) which produced the most complete results from automatic and manual evaluation of performance in the new disease and phenotype track. This track was based on the same tasks used for our own RFI evaluation. The track description and results are available (website:- http://oaei.ontologymatching.org/2016/phenotype/index.html). CONGRATULATIONS to the winners!

Ontologies Mapping Service and Questionaire

An important output from the OM project during 2016 has been to gather and develop our requirements for an Ontologies Mapping Service. While an Ontologies Mapping Tool finds matches of equivalence and similarity between ontologies which powers applications, such valuable mappings loose value as the source ontologies change. This requires a mapping service, as illustrated here, to maintain the ontologies mappings, which would otherwise consume valuable internal resource in any organisation using them. Our Ontologies Mapping Service requirements are reaching a mature state, ready for implementation in the next phase of the project.

We have devised an on-line questionnaire to determine the demand for an Ontologies Mapping service. If you are able to help us with this, please respond to the questionnaire:- http://goo.gl/forms/Odc3szwJjuXdk2un2

Contact Us

Please get in touch with the Ontologies Mapping project manager for further information.