IAOA Curricula Sub-committee wiki home-page (2XE4)
Sub-committee on Curricula, Certification & Accreditation - a part of the IAOA Education Committee (2XE5)
- Chair: FabianNeuhaus (2XE6)
- EC liaisons: MichaelGruninger & LeoObrst (2XE7)
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Extract from the Ontology Summit 2010: Creating the Ontologists of the Future: http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit2010_Communique#nid2C8E (2Z3D)
Recommendations for the training of ontologists (2Z3F)
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. (2Z3G)
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. (2Z3H)
Another challenge is that the careers of ontologists are diverse, as seen from the following examples. (2Z3I)
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. (2Z3J)
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. (2Z3K)
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. (2Z3L)
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. (2Z3M)
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. (2Z3N)
Core Skills (2Z3O)
Abilities required for developing, improving ontologies, and applying ontologies: (2Z3P)
- Clarifying the purpose of a given ontology, understanding potential deployment, performing requirements analysis (2Z3Q)
- Analyzing existing legacy models and data that are relevant to a given project (2Z3R)
- Judging what kinds of ontologies are useful for a given problem (including: know when ontologies are not useful) (2Z3S)
- Managing ontologies across their life cycle (requirements analysis and planning, managing a systematic update process, versioning, documentation, help desk ...) (2Z3T)
- Identifying, evaluating and using software tools that support ontology development (2Z3U)
- Choosing the appropriate representation language (2Z3V)
- Choosing the appropriate level of detail (2Z3W)
- Identifying existing content resources (e.g., existing ontologies, terminologies and related resources; relevant data; domain expertise, ontology expertise) (2Z3X)
- Assembling an ontology from reusable modules (2Z3Y)
- Using (reading, writing) different representation languages (2Z3Z)
- Conducting ontological analysis, that is identifying entities and relationships; formulating definitions and axioms (2Z40)
- Evaluating and improving ontologies (finding errors via manual term-by-term inspection, solving interoperability problems, decomposing large ontologies into interconnected modules) (2Z41)
- Documenting ontologies (e.g., providing natural language definitions and providing concise explanations for axioms) (2Z42)
- Working in teams, including those which support the distributed development of ontologies (2Z43)
- Using at least one modern programming/scripting language (2Z44)
Elective Skills (2Z45)
- Coordinating ontology development efforts (2Z46)
- Creating meaningful visualizations of ontology structure for human beings (2Z47)
- Training people in the use of ontologies (2Z48)
Core Knowledge (2Z49)
- The basic terminology of ontology (relation of ontology to knowledge representation, conceptual modeling, data modeling, ...) (2Z4A)
- Theoretical foundations (2Z4B)
- first-order logic, basics of description logic, modal logic, and second-order logic (2Z4C)
- set theory (2Z4D)
- basic notions of philosophical ontology (universals and particulars, mereology, essence and identity, unity and plurality, dependence, change in time...) (2Z4E)
- philosophy of language (the use-mention confusion, sense and reference, speech act theory, ...) (2Z4F)
- knowledge representation, conceptual modeling, data modeling; metadata (2Z4G)
- Representation languages Part 1: RDF, OWL; Common Logic (2Z4H)
- Building and editing ontologies (2Z4I)
- Ontology evaluation strategies and theories (Ontoclean, ...) (2Z4M)
- Examples of ontologies, illustrating different methodologies (2Z4N)
- Examples of ontology applications (successes and failures) (2Z4R)
- as controlled vocabularies / standards, to achieve coordination among humans (2Z4S)
- to solve interoperability problems among external data resources (2Z4T)
- reasoning with ontology content (2Z4U)
- improve search and retrieval (2Z4V)
- Natural language processing (2Z4W)
- decision support, situational awareness, information fusion, anomaly detection (2Z4X)
- Ontology and the Web (2Z4Y)
Elective Knowledge (2Z52)
Underlying and related disciplines (2Z53)
- Advanced logic (modal logic, temporal logic, default logic, ...) (2Z54)
- Advanced philosophical ontology (mereotopology, tropes, ...) (2Z55)
- Computer science (2Z56)
- Linguistics / cognitive sciences (2Z5C)
Supporting tools, technologies and methodologies (2Z5G)
- Representation languages Part 2 (SWRL, RIF, SKOS; OBO; UML; E-R, IKL, ...) (2Z5H)
- Ontology content acquisition (role of text mining, ...) (2Z5I)
- Achieving ontology interoperability (2Z5J)
- Principles for building ontology repositories (2Z5K)
- Usability and user interface issues (visualization / usability, principles of meaningful arrangement, ...) (2Z5L)
Application domains (2Z5M)
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. (2Z5N)
Towards Better Education and Training of Ontologists (2Z5O)
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. (2Z5P)
To improve the training situation in applied ontology we recommend the following actions: (2Z5Q)
- While the list of requisite knowledge and skills for ontologists above is a valuable first step, it is desirable to describe each knowledge area and each skill in more detail. (2Z5R)
- We recommend the development of a registry, allowing members of the community to add information about ontology-centered educational and training initiatives. (2Z5S)
- We recommend including more ontology-related content into model curricula for computer science (e.g., those of ACM/IEEE http://www.acm.org/education/curricula-recommendations). (2Z5T)
- The requirements survey revealed a surprising non-alignment between the training available to ontologists and the kind of training they need. As the field of ontology continues to evolve and training demand shifts in tandem, we recommend conducting similar surveys at regular intervals. This will enable training providers to ensure that their courses meet the needs of their students. (2Z5U)
- Applied ontology has no accepted body of shared knowledge, techniques, and criteria for evaluation. It is in part for this reason that so few ontology training programs in universities have been developed. We recommend taking advantage of the need for trained ontologists, and thus for improved ontology training, as an argument for investing effort in establishing the requisite shared body of knowledge. (2Z5V)
- We recommend the creation of a wiki to collect descriptions of case studies demonstrating the importance of certain ontology engineering decisions. These might include examples of bad decisions, the problems they caused, the associated costs, and how the problems were corrected. (2Z5W)
- Most importantly, we strongly encourage educational institutions to establish programs that address the growing need for ontologists based on the guidelines set forth in this document. (2Z5X)
End Extract from the Ontology Summit 2010 Communique (2Z3E)