OntologySummit2010 Communiqué: Creating the Ontologists of the Future    (25J5)

Lead Editors: FabianNeuhaus & BarrySmith    (2C79)

Co-Editors: ElizabethFlorescu, AntonyGalton, MichaelGruninger, NicolaGuarino, LeoObrst, ArturoSanchez, AmandaVizedom, and PeterYim    (2C7A)

Summary    (2C7F)

Increasingly, major national and international projects and systems centered on ontology technology are being developed and deployed by governments and by scientific and commercial organizations. This brings a growing need for ontology expertise and thus for new methods and organizations for the education and training of ontologists. The goal of the Ontology Summit 2010 was to develop a strategy for the education of ontologists. To achieve this goal we studied how ontologists are currently trained, the requirements by organizations that hire ontologists, and developments that might impact the training of ontologists in the future.    (2C7G)

The main findings and results of the Ontology Summit 2010 are:    (2C7H)

  1. There is already a large demand for trained ontologists, and the demand is expected to increase as ontology-based technologies become more successful and as the quantities and number of different types of data continues to expand.    (2C7I)
  2. There are very few formal training opportunities for ontologists, and they often do not meet the needs of trainees or of those who would hire them.    (2C7J)
  3. Organizations that want to hire ontologists often have difficulties in identifying qualified candidates since there are so few formal qualifications in ontology, and there is no professional organization that certifies ontologists.    (2C7K)

We developed recommendations for the body of knowledge that should be taught and the skills that should be developed by future ontologists; these recommendations are intended as guidelines for institutions and organizations that may consider establishing a program for training ontologists. Further, we recommend a number of specific actions for the community to pursue as a follow-up to the Ontology Summit 2010 that will improve the education of ontologists.    (2C7L)


Introduction    (2C7N)

Currently, data and information are often siloed, reflecting the fact that these have been collected in ways designed to address narrowly tailored local needs and in the context of specific applications. As a result data is difficult to reuse for new purposes; different bodies of data do not cumulate; and possible benefits of data integration are lost.    (2C7O)

Applied ontology is designed to counteract these effects by creating so-called 'ontologies' that are designed to facilitate more effective information exchange through machine-interpretable representations of reality of more global validity and scope. To this end, applied ontologists develop the theories, methods and formal tools to support the creation, use and evaluation of ontologies.    (2C7P)

Ontologies play a central role in the Semantic Web, the Linked Data movement, and in many other technological developments, for example in the areas of semantic services and the semantic enterprise. A variety of ontology-based approaches, loosely grouped under the heading 'semantic interoperability', have come to the fore as potential solutions to critical interoperability problems. Further, technologies that incorporate and rely on ontologies are used to increase transparency both within and across organizations, and to enhance communication not only between computers but also between human beings.    (2C7Q)

Major national and international ontology projects have been initiated by governmental, scientific and industrial organizations, for example to support exchange of information across scientific, organizational or linguistic boundaries. But the success of such efforts depends on the availability of well-trained ontologists, capable of designing and building the needed representations and of supporting their successful implementation and resultant integration of data and information.    (2C7R)

It is already clear that the resultant need for persons with ontology expertise goes far beyond the current availability of appropriately trained personnel. Organizations seeking to hire ontologists often face difficulties in identifying qualified candidates since there is no professional organization that certifies ontologists and very few educational institutions that offer formal education and training in ontology.    (2C7S)

Enhanced training of ontologists would at the same time provide a developing body of knowledge not only concerning the techniques of ontology but also concerning important successes and failures. In this way, it would help those working in semantic technology and related fields to recognize where ontology can be successfully used, and at the same time to avoid a variety of characteristic errors -- and resultant project failures -- that have affected ontology initiatives in recent years.    (2C7T)

To work effectively, the ontologist must command a specific set of skills, and it is important to examine how formal education and training can help us both to meet the increasing demand for those who have these skills, and to enable project managers to distinguish qualified ontologists from those who simply claim the title.    (2C7U)

The goal of the 2010 Ontology Summit was to develop a strategy for a more coherent approach to the education and training of ontologists. Our work builds on the results of previous Ontology Summits (http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit). To achieve our goals we conducted two surveys, a Delphi study, and several panel discussions to address the following questions:    (2C7V)

  1. How are ontologists currently trained?    (2C7W)
  2. What abilities do ontologists consider as necessary for their work?    (2C7X)
  3. What do employers expect from individuals that are hired as ontologists?    (2C7Y)
  4. What are the developments that might impact the training of ontologists in the future?    (2C7Z)

The responses to these and related questions allowed us to identify a number of different career paths for ontologists as well as the associated knowledge and skills. On this foundation we developed recommendations for the content that should be taught to future ontologists. In the following we will present the results of our findings as well as our recommendations.    (2C80)

Current State of Training -- Opportunities, Requirements, Expected Developments    (2C81)

Our key findings are:    (2C82)

More details on the surveys:    (2C8A)

Education of ontologists: http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit2010_PresentContent_Synthesis#nid25FP    (2C8B)

Requirements for ontologists: http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit2010_PresentRequirements_Synthesis    (2C8C)

Future developments: http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit2010_FutureDevelopments_Synthesis#nid25HJ    (2C8D)

Recommendations for the training of ontologists    (2C8E)

Based on our findings we present a list of the knowledge that a student should be taught and the skills that should be developed in an ontology program. Since ontology is a highly interdisciplinary field, it is unrealistic to expect students to learn everything that might be relevant. For this reason, one could characterize our task as being one of identifying the most important knowledge and skills that an ontologist needs to do his job. How this content should be taught is beyond the scope of this document -- this is something that needs to be decided by each individual educational institution on the basis of available resources. At least some of the content is likely to be covered by existing courses in other programs (e.g., in computer science, information studies, or philosophy). We stress, however, that benefits accrue from the maximal possible degree of coordination and of shared content between those offering ontology training programs.    (2C8F)

One challenge in creating recommendations for the education of ontologists is that ontology is a young discipline and thus has as yet no widely agreed upon body of shared knowledge, established methodologies, or a common terminology. Instead, multiple terminologies are used in the different subfields of ontology, ­ for example, deriving from specific programming environments, from database design and the conceptual modeling community, or from traditional philosophical ontology. This is a large obstacle for communication between ontologists and the users of ontologies, and we strongly recommend that all ontologist training programs include terminology survey modules designed to familiarize trainees with these multiple terminologies.    (2C8G)

Another challenge is that the careers of ontologists are diverse, as seen from the following examples.    (2C8H)

IT-oriented ontologists are actively engaged in the deployment of IT systems involving many components in addition to the ontology itself. For these ontologists it is essential to know how to integrate the ontology into the associated applications. For this purpose ontologists need some background in software engineering, information systems design, system development, object-oriented programming, and data analysis.    (2C8I)

Community-oriented ontologists specialize in developing ontologies within a given domain in collaboration with experts from diverse communities. One of their main tasks is to facilitate the resolution of ambiguities in such a way as to build consensus within these communities. To fulfill this role, ontologists need not only to know the scientific area covered by the ontologies (e.g., protein biology or infectious disease), but also need to possess the human-oriented skills that enable them to lead teams of domain experts or to build communities that will support the effective use of ontology resources.    (2C8J)

The core knowledge and skills that we list below cover the basics any ontologist will need. They are not of themselves sufficient to support a career as an ontologist; this will require either some additional background in systems development or domain specific knowledge in a relevant application environment.    (2C8K)

There is a strong consensus within the community that although much academic knowledge is relevant for ontologists, many important skills cannot be learned from lectures alone. Any education of ontologists has to involve hands-on training in the development and application of ontology. Ideally, academic programs should offer their students the opportunity to gain some of this experience by participating in projects that apply of ontologies to the solution of real and complex problems.    (2C8L)

In the following, we distinguish between skills (the ability of a student to do something) and knowledge (basic notions grasped). Since skills build on knowledge, they must be taught together. Because the careers of ontologists are diverse, it is not realistic to develop a single curriculum that fits all students. In the following we distinguish between core and elective skills and knowledge. The idea is that any student should be required to gain all of the core and some of the elective skills and knowledge.    (2C8M)

Core Skills    (2C8N)

Abilities required for developing, improving ontologies, and applying ontologies:    (2C8O)

  1. Clarifying the purpose of a given ontology, understanding potential deployment, performing requirements analysis    (2C8P)
  2. Analyzing existing legacy models and data that are relevant to a given project    (2C8Q)
  3. Judging what kinds of ontologies are useful for a given problem (including: know when ontologies are not useful)    (2C8R)
  4. Managing ontologies across their life cycle (requirements analysis and planning, managing a systematic update process, versioning, documentation, help desk ...)    (2C8S)
  5. Identifying, evaluating and using software tools that support ontology development    (2C8T)
  6. Choosing the appropriate representation language    (2C8U)
  7. Choosing the appropriate level of detail    (2C8V)
  8. Identifying existing content resources (e.g., existing ontologies, terminologies and related resources; relevant data; domain expertise, ontology expertise)    (2C8W)
  9. Assembling an ontology from reusable modules    (2C8X)
  10. Using (reading, writing) different representation languages    (2C8Y)
  11. Conducting ontological analysis, that is identifying entities and relationships; formulating definitions and axioms    (2C8Z)
  12. Evaluating and improving ontologies (finding errors via manual term-by-term inspection, solving interoperability problems, decomposing large ontologies into interconnected modules)    (2C90)
  13. Documenting ontologies (e.g., providing natural language definitions and providing concise explanations for axioms)    (2C91)
  14. Working in teams, including those which support the distributed development of ontologies    (2C92)
  15. Using at least one modern programming/scripting language    (2C93)
Elective Skills    (2C94)
  1. Coordinating ontology development efforts    (2C95)
  2. Creating meaningful visualizations of ontology structure for human beings    (2C96)
  3. Training people in the use of ontologies    (2C97)
Core Knowledge    (2C98)
  1. The basic terminology of ontology (relation of ontology to knowledge representation, conceptual modeling, data modeling, ...)    (2C99)
  2. Theoretical foundations    (2C9A)
    1. first-order logic, basics of description logic, modal logic, and second-order logic    (2C9B)
    2. set theory    (2C9C)
    3. basic notions of philosophical ontology (universals and particulars, mereology, essence and identity, unity and plurality, dependence, change in time...)    (2C9D)
    4. philosophy of language (the use-mention confusion, sense and reference, speech act theory, ...)    (2C9E)
    5. knowledge representation, conceptual modeling, data modeling; metadata    (2C9F)
  3. Representation languages Part 1: RDF, OWL; Common Logic    (2C9G)
  4. Building and editing ontologies    (2C9H)
    1. human aspects (application of classification principles, manual auditing, ...)    (2C9I)
    2. software tools (Protégé, ...)    (2C9J)
    3. addressing interoperability problems among ontologies    (2C9K)
  5. Ontology evaluation strategies and theories (Ontoclean, ...)    (2C9L)
  6. Examples of ontologies, illustrating different methodologies    (2C9M)
    1. upper-level ontologies (BFO, DOLCE, SUMO, ...)    (2C9N)
    2. mid-level, domain-spanning ontologies (PSL, ...)    (2C9O)
    3. domain ontologies (GO, Enterprise Ontology, ...)    (2C9P)
  7. Examples of ontology applications (successes and failures)    (2C9Q)
    1. as controlled vocabularies / standards, to achieve coordination among humans    (2C9R)
    2. to solve interoperability problems among external data resources    (2C9S)
    3. reasoning with ontology content    (2C9T)
    4. improve search and retrieval    (2C9U)
    5. Natural language processing    (2C9V)
    6. decision support, situational awareness, information fusion, anomaly detection    (2C9W)
  8. Ontology and the Web    (2C9X)
    1. general foundations (URIs, XML, etc.)    (2C9Y)
    2. Semantic Web initiative    (2C9Z)
    3. semantically enhanced publishing, literature annotation, data curation    (2CA0)
Elective Knowledge    (2CA1)

Underlying and related disciplines    (2CA2)

  1. Advanced logic (modal logic, temporal logic, default logic, ...)    (2CA3)
  2. Advanced philosophical ontology (mereotopology, tropes, ...)    (2CA4)
  3. Computer science    (2CA5)
    1. formal languages, formal machines, computability, complexity    (2CA6)
    2. automated reasoning    (2CA7)
    3. database theory    (2CA8)
    4. artificial intelligence    (2CA9)
    5. logic programming    (2CAA)
  4. Linguistics / cognitive sciences    (2CAB)
    1. distinction between syntax, semantics, and pragmatics    (2CAC)
    2. natural language processing, natural language generation    (2CAD)
    3. cognitive theories of categorization    (2CAE)

Supporting tools, technologies and methodologies    (2CAF)

  1. Representation languages Part 2 (SWRL, RIF, SKOS; OBO; UML; E-R, IKL, ...)    (2CAG)
  2. Ontology content acquisition (role of text mining, ...)    (2CAH)
  3. Achieving ontology interoperability    (2CAI)
  4. Principles for building ontology repositories    (2CAJ)
  5. Usability and user interface issues (visualization / usability, principles of meaningful arrangement, ...)    (2CAK)

Application domains    (2CAL)

Any domain could be an application domain for ontologists. Ontologies are already used and are being developed for use in many domains, including science, medicine, business, government, military, education and culture.    (2CAM)

Towards Better Education and Training of Ontologists    (2CAN)

This document identifies the skills and knowledge a student should possess after successfully completing an ontology program. These recommendations are based on extensive studies of the current training situation, the requirements ontologists face, and the developments that might impact the situation of ontologists in the future.    (2CAO)

To improve the training situation in applied ontology we recommend the following actions:    (2CAP)

Endorsement    (2CAX)

The above Communiqué has been endorsed by the individuals listed below. Please note that these people made their endorsements as individuals and not as representatives of the organizations they are affiliated with.    (2CAY)

An open invitation was made to the community at large by the co-organizers of this Summit for endorsements to this Communiqué after the document was finalized at the OntologySummit2010_Symposium on 16-Mar-2010. We thank all individuals listed above, who have confirmed their endorsements in writing, before the solicitation was closed 16-April-2010.    (2CUN)

see working draft at: /Draft    (25J7)

 This page is maintained by BarrySmith, FabianNeuhaus, SteveRay and PeterYim
 Please do not edit or modify yourself; send any editing request to any one of the individuals named above.    (25J8)