Teaching another two courses on ontology engineering

As follow up on the Comprehensive introduction to ontology engineering I taught at the University of Havana (UH) last April, Diego Calvanese taught a more in-depth course on ontology-based data access in June, and I will go again to Cuba next week to teach at the University of Computer Science (UCI) in Havana and visit UH for research activities.

Some of the tidbits of information about UCI: they were established in 2002, have 11000 (yes, eleven thousand!) students in computing and IT, and a brand new campus with a range of facilities right at the outskirts of Havana. As UCI is more engineering-oriented than UH, some more foundations are added to the course topics and a few application-oriented slides have been added. This time, the intention is to teach the whole course in Spanish. There are already many more people who signed up for the course (>=80) than I’d be able to teach (in particular, doing a lab on your own with 80 motivated students is physically not feasible unless you ignore about 75% of the participants, which would seriously affect the quality of the course).

After that, I will go almost straight onward to the Knowledge Representation and Reasoning group at Meraka Institute, CSIR, Pretoria, South Africa for two months as part of the EU FP7 Net2 project “Network for Enabling Networked Knowledge” and the “Technologies for Conceptual Modelling and Intelligent Query Formulation” project within the Executive Programme of Scientific and Technological Co-Operation between the Italian Republic and Republic of South Africa. One of the activities will be to teach about ontology engineering as well, but then a bit more focussed on Semantic Web technologies and taking representation & reasoning challenges as elective topic (which is a result of the SWT course that has generated the request). As course syllabus, I have reorganized, brushed up, and extended the blog posts of the SWT course in to a single HTML page: Introduction to ontology engineering, with emphasis on Semantic Web Technologies. The course itself is part of KRR’s Masters Ontology Winter School 2010.

Notwithstanding the demonstrated interest, the powers that be have decided to reorganize the course contents of the SWT course into something more hands-on and practical that is not a part of the European Masters Programme in Computational Logic anymore (until and including this academic year it is). And, while still being named “Semantic Web Technologies”, there is not going to be a substantial ontology engineering component in it… So, after teaching the course about ontology engineering at Meraka, its likely future is to just gather dust—until there is another request. I have the slides, can update them, extend them, and fiddle with the focus and storyline etc., and I am willing to travel; feel free to inquire about possibilities :).

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Rough ontologies from an ontology engineering perspective

Somewhere buried in the blogpost about the DL’10 workshop, I mentioned the topic of my paper [1] at the 23rd International Description Logics Workshop (DL’10), which concerned the feasibility of rough DL knowledge bases. That paper was focussed on the theoretical assessment (result: there are serious theoretical hurdles for rough DL KBs) and had a rather short section where experimental results were crammed into the odd page (result: one can squeeze at least something out of the extant languages and tools, but more should be possible in the near future). More recently, my paper [2] submitted to the 17th International Conference on Knowledge Engineering and Knowledge Management (EKAW’10) got accepted, which focuses on the ontology engineering side of rough ontologies and therefore has a lot more information on how one can squeeze something out of the extant languages and tools; if that is not enough, there is also supplementary material that people can play with.

Ideally, they ought to go together in on paper to get a good overview at once, but there are page limits for conference papers and anyhow the last word has not been said about rough ontologies. For what it is worth, I have put the two together in the slides for the weekly KRDB Lunch Seminar that I will present tomorrow at, well, lunch hour in the seminar room on the first floor of the POS building.

References

[1] Keet, C. M. On the feasibility of Description Logic knowledge bases with rough concepts and vague instances. Proc. of DL’10, 4-7 May 2010, Waterloo, Canada. pp314-324.

[2] Keet, C. M. Ontology engineering with rough concepts and instances17th International Conference on Knowledge Engineering and Knowledge Management (EKAW’10). 11-15 October 2010, Lisbon, Portugal.  Springer LNCS.

More ontology design parameters and dependencies between them

Following up on the MTSR’09 short paper on ontology design parameters [1] for agri-ontologies (blogged about earlier), I received an invitation to write an extended version of it for the International Journal on Metadata, Semantics and Ontologies. This much extended version—20 pages double column vs the earlier 6 page LNCS-format—got accepted recently and is currently in print [2]. Reading the small print of the author agreement, I seem not to be allowed to put either the abstract or the paper online (but clearly, emailing the preprint to interested people does not constitute publishing it), so here goes an informal rendering of the abstract.

Anyone in the ontologies arena is well-aware of the fact that the development, adoption, extension, and use of ontologies is increasing, yet at the same time such efforts are hampered by the new challenges wider uptake generates, such as determining which ontologies to reuse, if any, and which language to use. Several ontology development methodologies are available, such as Methontology and the emerging NeOn methodology, which provide scenarios but do not yet address the dependencies between the permutations at the different stages in the development process. In an attempt to improve the efficiency and effectiveness of this endeavour, I have grouped the myriad of inputs into types of parameters and examined the dependencies between them. The types of parameters that were considered are: purpose(s) of the ontology, reuse of different types of ontologies, different ways for bottom-up ontology development, ontology languages (mainly the DL-based OWL species and several proposed extensions), and reasoning services (grouped into four types).

Subsequently, all dependencies between these parameters have been assessed on their feasibility of combination and useful combinations are motivated (e.g., why ontologising thesauri with OWL 2 DL and further extensions may not be such a good idea, but representing a scientific theory is, and using OntoClean with a bare taxonomy is also a good idea, but not DOLCE with Ontology-Based Data Access). The dependencies between the assessed parameters are due to, primarily, computational challenges and types of subject domain of the ontologies (motivated more extensively in the paper). In addition to the review and theoretical assessment, the analysis was assessed against a set of randomly selected ontologies and a survey among ontology developers; the results obtained concur with the theoretical assessment.

At some point in the future, it could be nice to have this integrated in software-supported ontology development environments (ODEs) as some sort of decision procedure. At least it will be able to suggest sensible combinations and discourage upfront combinations that will be tedious and overly resource-consuming to implement, thereby making the ontology engineering process more easily accessible and efficient by proposing combinations that lead to feasible implementation scenarios.

References

[1] Keet, C.M. Ontology design parameters for aligning agri-informatics with the Semantic Web. 3rd International Conference on Metadata and Semantics (MTSR’09) — Special Track on Agriculture, Food & Environment, Oct 1-2 2009 Milan, Italy. Springer CCIS 46, 239-244.

[2] Keet, C.M. Dependencies between ontology design parameters. International Journal on Metadata, Semantics and Ontologies. In print.