Part-whole relations and foundational ontologies

Part-whole relations seem like a never-ending story—and it still doesn’t bore me. In this case, the ingredients were the taxonomy of part-whole relations [1] and a couple of foundational ontologies and the aim was to link the former to the latter. But what started off with the intention to write just a short workshop note, for seemingly clear and just in need of actually doing it, turned out to be not so straightforward after all. The selected foundational ontologies were not as compatible as assumed, and creating the corresponding orchestration of OWL files was a ‘non-trivial exercise’.

What were (some of) the issues? On the one hand, there are multiple part-whole relations, which are typically named differently when they have a specific domain or range. For instance, to relate a process to a sub-process (e.g., eating involves chewing), to relate a region to a region it contains, relating portions of stuff, and so on. Those relations are fairly well established in the literature. What they do demand for, however, is clarity as to what those categories really are. For instance, with the process example, is that to be understood as Process as meant in the DOLCE ontology, or, say, Process in BFO? What if a foundational ontology does not have a category needed for a commonly used part-whole relation?

The first step to answer such questions was to assess several foundational ontologies on 1) which of the part-whole relations they have now, and which categories are present that are needed for the domain and range declarations for those common part-whole relations. I assessed that for DOLCE, BFO, GFO, SUMO, GIST, and YAMATO. This foundational ontology comparison is summarised in tables 1 and 2 in the paper that emanated from the assessment [2], entitled “A note on the compatibility of part-whole relations with foundational ontologies” that I recently presented at FOUST-II: 2nd Workshop on Foundational Ontology, Joint Ontology Workshops 2017 in Bolzano, Italy. In short: none fits perfectly for various reasons, but there are more and less suitable ontologies for a possible alignment. DOLCE and SUMO were evaluated to have the best approximations. It appeared at the workshops presentation’s Q&A session, where two of the DOLCE developers were present, that the missing Collective was an oversight, or: the ontology is incomplete and it was not an explicit design choice to exclude it. This, then, would make DOLCE the best/easiest fit.

I’ll save you the trials and tribulations creating the orchestrated OWL files. The part-whole relations, their inverses, and their proper parthood versions were manually linked to modules of DOLCE and SUMO, and automatically linked to BFO and GFO. That was an addition of 49 relations (OWL object properties) and 121 logical axioms, which were then extended further with another 11 mereotopological relations and its 16 logical axioms. These files are accessible online directly here and also listed with brief descriptions.

While there is something usable now and, by design at least, these files are reusable as well, what it also highlighted is that there are still some outstanding questions, as there already were for the top-level categories of previously aligned foundational ontologies [3]. For instance, some categories seem the same, but they’re in ‘incompatible’ parts of the taxonomy (located in disjoint branches), so then either not the same after all, or this happened unintentionally. Only GIST has been updated recently, and it may be useful if the others foundational ontologies were to be as well, so as to obtain clarity on these issues. The full interaction of part-whole relations with classical mereology is not quite clear either: there are various extensions and deviations, such as specifically for portions [4,5], but one for processes may be interesting as well. Not that such prospective theories would be usable as-is in OWL ontology development, but there are more expressive languages that start having tooling support where it could be an interesting avenue for future work. I’ll write more about the latter in an upcoming post (covering the K-CAP 2017 paper that was recently accepted).

On a last note: the Joint Ontology Workshops (JOWO 2017) was a great event. Some 100 ontologists from all over the world attended. There were good presentations, lively conversations, and it was great to meet up again with researchers I had not seen for years, finally meet people I knew only via email, and make new connections. It will not be an easy task to surpass this event next year at FOIS 2018 in Cape Town.

 

References

 

[1] Keet, C.M., Artale, A. Representing and Reasoning over a Taxonomy of Part-Whole Relations. Applied Ontology, 2008, 3(1-2):91-110.

[2] Keet, C.M. A note on the compatibility of part-whole relations with foundational ontologies. FOUST-II: 2nd Workshop on Foundational Ontology, Joint Ontology Workshops 2017, 21-23 September 2017, Bolzano, Italy. CEUR-WS Vol. (in print)

[3] Khan, Z.C., Keet, C.M. Foundational ontology mediation in ROMULUS. Knowledge Discovery, Knowledge Engineering and Knowledge Management: IC3K 2013 Selected Papers. A. Fred et al. (Eds.). Springer CCIS vol. 454, pp. 132-152, 2015. preprint

[4] Donnelly, M., Bittner, T. Summation relations and portions of stuff. Philosophical Studies, 2009, 143, 167-185.

[5] Keet, C.M. Relating some stuff to other stuff. 20th International Conference on Knowledge Engineering and Knowledge Management (EKAW’16). Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (Eds.). Springer LNAI vol. 10024, 368-383. 19-23 November 2016, Bologna, Italy.

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Updated ontology engineering lecture notes (2015)

It’s that time of the year again, in the southern hemisphere that is, where course preparations for the academic year are going on full steam ahead. Also this year, I’ll be teaching a CS honours course on ontology engineering. To that end, the lecture notes have been updated, though not in a major way like last year. Some sections have been shuffled around, there are a few new exercises, Chris’s update suggestion from last year on the OBO-OWL mapping has been included, and a couple of typos and odd sentences have been fixed.

Practically, this installment will be a bit different from previous years, as it has integrated a small project on Semantic Wikis, funded by CILT and OpenUCT. Set up, maintenance, and filling it with contents on ontology engineering topics will initially be done ‘in house’ by students enrolled in the course and not be generally available on the Web, but if all goes well, it’ll be accessible to everyone some time in April this year, and possibly included in the OER Commons.

Semantic MediaWiki’s features are fairly basic and there are a bunch of plugins and extensions I’ve seen listed, but I didn’t check whether they all worked with the latest SMW. If you have a particular suggestion, please leave a comment or send me an email. One thing I’m still wondering about particularly, but haven’t found a solution to, is whether there’s a plugin that lets you see the (lightweight) ontology when adding contents, so that it makes it easier to use terms in the text from the ontology’s vocabulary rather than find an having to process manually whatever (near)synonyms have been used throughout the pages (like, one contributor using ‘upper ontology’, another ‘foundational ontology’ and the third ‘top-level ontology’), and allow on-the-fly extensions of that ontology.

Zubeida Khan awarded with best Master’s thesis from CSIR

Zubeida Khan

I’m delighted to highlight here that Zubeida Khan (Dawood) was awarded with a “Best Master’s Thesis” from the CSIR (South Africa’s Council for Scientific and Industrial Research), where she was based when she did her Msc (cum laude) from UKZN, with a scholarship from the UKZN/CSIR-Meraka Centre for Artificial Intelligence Research, and yours truly as her supervisor.

Her thesis was about realising that library of foundational ontologies that had been proposed since late 2003 (in that WonderWeb deliverable D18). The concrete library is the online Repository for Ontologies of MULtiple Uses, ROMULUS, which was described briefly in the MEDI’13 paper [1], and she has a CSIR “technology demonstrator” about it (file) that received an overall panel evaluation of 90%. The theoretical foundations principally had to do with aligning and mapping the foundational ontologies that are included in the library, which are, to date, the OWL versions of DOLCE, GFO, and BFO, which has appeared in a KCAP’13 poster [2] and KEOD’13 full paper [3] and an extended version is due to appear in a best-papers-of-KEOD book [4]. In case you want to have more details: check Zubeida’s thesis, and I have a few blog posts that informally introduce the material: the first announcement of ROMULUS and the KCAP poster.

ROMULUS also contains an online and extended version of the foundational ontology recommender ONSET [5] (which was mostly her Bsc(hons) project, and whose integration into ROMULUS was part of her MSc), various documentation and browse and search features, and the new SUGOI tool for automated foundational ontology interchangeability [6].

Zubeida recently started her PhD at UCT with me as advisor, on ontology modularity, but in case you have feedback on the work, suggestions, or perhaps also new mappings to/from your favourite foundational ontology, feel free to contact her (or me)!

p.s.: Engineering news has an item about the awards, and so will CSIR have one.

p.p.s.: The minimum requirements for the award was:
-Published more than one paper in a peer reviewed publication
-Excellent behavioural attributes as attested by fellow team members such as work ethic and developing a good personal and professional relationships and an active contribution as a team member
-Above average performance score
-The studies must have been completed on a record time
-Excellent academic achievement

References

[1] Khan, Z., Keet, C.M. The foundational ontology library ROMULUS. 3rd International Conference on Model & Data Engineering (MEDI’13). A. Cuzzocrea and S. Maabout (Eds.) September 25-27, 2013, Amantea, Calabria, Italy. Springer LNCS 8216, 200-211.

[2] Khan, Z., Keet, C.M. Toward semantic interoperability with aligned foundational ontologies in ROMULUS. Seventh International Conference on Knowledge Capture (K-CAP’13), ACM proceedings. 23-26 June 2013, Banff, Canada. (poster/demo)

[3] Khan, Z., Keet, C.M. Addressing issues in foundational ontology mediation. 5th International Conference on Knowledge Engineering and Ontology Development (KEOD’13), Vilamoura, Portugal, 19-22 September. Filipe, J. and Dietz, J. (Eds.), SCITEPRESS, pp5-16.

[4] Khan, Z.C., Keet, C.M. Foundational ontology mediation in ROMULUS. invited extended version of the KEOD’13 paper, to be published in Springer CCIS.

[5] Khan, Z., Keet, C.M. ONSET: Automated Foundational Ontology Selection and Explanation. 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW’12), A. ten Teije et al. (Eds.). Oct 8-12, Galway, Ireland. Springer, Lecture Notes in Artificial Intelligence LNAI 7603, 237-251.

[6] Khan, Z.C., Keet, C.M. Feasibility of automated foundational ontology interchangeability. 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW’14). K. Janowicz et al. (Eds.). 24-28 Nov, 2014, Linkoping, Sweden. Springer LNAI 8876, 225-237.

On ‘swapping’ your foundational ontology to increase interoperability

Over the past few years, I’ve been putting some effort into methods and tools and some data collection and analysis that would aid the use of foundational (top-level) ontologies in ontology engineering, such as DOLCE, GFO, and BFO, and some of its relations (mainly part-whole relations). Tools include the Ontology Selection and Explanation Tool to choose the most suitable foundational ontology [1] and OntoPartS [2] and OntoPartS-2 [3] for software-supported modeling of part-whole relations, and experimentally validating using a foundational ontology does make a difference [4]. The latest addition is SUGOI—Software Used to Gain Ontology Interchangeability, initiated by Zubeida Khan’s idea mentioned in her (cum laude) MSc thesis, which I supervised.

In the meantime, SUGOI has been implemented, and we have used it to answer principally two questions:

  1. Is it feasible to automatically generate links between ontology Oa and foundational ontology Oy, given Oa is linked to Ox? Say, I have an ontology linked to BFO, then can I swap BFO for DOLCE?
  2. If there are issues with the former, what is causing it? Or: in praxis, which entities of Ox are typically used for mappings with domain ontologies that may not be present, or present in an incompatible way, in Oy? Or: if not, then why not?

We tested this with 16 ontologies that are linked to a foundational ontology, and the results have just been accepted at the 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW’14) [5].

Now, I already know that some of you will say (and, in fact, have said!), this is not feasible at all. Arguments on philosophical distinctions are there, yes, but not all of that appears in an OWL file and in the modeller’s view (see also an earlier post and references therein). Put differently: things are not that clear-cut and black-and-white as it initially may seem. We did observe a basic, or raw, ‘swapping success rate’ from 2% for the PID ontology from the GFO it was aligned to, to BFO, to up to a whopping 82% for the IDO ontology from BFO to either DOLCE or GFO (averaging at 36% for the real ontologies we tested with). Now, there.

So, what’s really happening? The success rate actually depends on several factors. Some entities in, say, BFO, while named differently, do have an equivalent in DOLCE or GFO, that may or may not be in a similar place in the ontology (if not, then you still end up with an inconsistency, which we removed as mapping), others do not. Those mappings have been investigated in detail [6], and, indeed, there aren’t many, but surely there are some. Several domain ontologies have alignments to only a few categories in a foundational ontology, others have more. If there aren’t many links, or predominantly to those for which there exists an equivalence assertion, then your ‘swapping success rate’ (called raw interchangeability in the paper) is high. Thus, it is not that it is not feasible at all.

sugoiscreen

The interface of the online desktop version of SUGOI.

Sounds obvious when one puts it like that. But what about my ontology, you may wonder. Use SUGOI to find out. The log file shows what’s been done in the process, and does compute those raw interchangeability metrics for you. SUGOI is ‘trivial’ to extend to include foundational ontologies other than DOLCE, BFO, and GFO—just the mapping files have to be added, but it doesn’t really change the algorithm.

We also looked at the data, especially for the ones with a low success rate, to figure out what causes it. It appeared that for those that use DOLCE, they probably do so because it has some nice knowledge about attributive properties that are not represented (BFO) or represented in an incompatible way (GFO) elsewhere. Likewise, those ontologies that were linked to BFO or GFO and for which there was a lower interchangeability to DOLCE, had quite a few links to aspects on roles, which aren’t in DOLCE proper, so that was causing a relatively lower success rate there (more details in the paper). We leave it up to the developers of the respective foundational ontologies to decide whether they wan to fill that ‘gap’ in their respective ontology.

We also checked SUGOI’s output against ontologies that had been aligned manually to more than one foundational ontology by the developers. We could find only two that were: BioTop and the Stuff Ontology. Mainly, we found the odd error in alignment and a few ones missed by manual alignment, but with n=2, those results are quite at the level of interesting anecdote (observing that the plural of anecdote is not data).

Whether you want to swap, or offer your ontology aligned to more than one foundational ontology to increase its interoperability with other ontologies, is, clearly, your choice to make. If you decide to do so, you could do that manually, but SUGOI automates that process for you as much as possible. Both Zubeida and I plan to be at EKAW’14, hopefully also with a demo, so that you not only can test it with your ontology (which you can do already on the SUGOI page already), but also gain some further detailed insights into the algorithm, the mapping files it used, and the consequences for your ontology.

References

[1] Khan, Z., Keet, C.M. ONSET: Automated Foundational Ontology Selection and Explanation. 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW’12), A. ten Teije et al. (Eds.). Oct 8-12, Galway, Ireland. Springer, LNAI 7603, 237-251.

[2] Keet, C.M., Fernandez-Reyes, F.C., Morales-Gonzalez, A. Representing mereotopological relations in OWL ontologies with OntoPartS. 9th Extended Semantic Web Conference (ESWC’12), Simperl et al. (eds.), 27-31 May 2012, Heraklion, Crete, Greece. Springer, LNCS 7295, 240-254.

[3] Keet, C.M., Khan, M.T., Ghidini, C. Ontology Authoring with FORZA. 22nd ACM International Conference on Information and Knowledge Management (CIKM’13). ACM proceedings, pp569-578. Oct. 27 – Nov. 1, 2013, San Francisco, USA.

[4] Keet, C.M. The use of foundational ontologies in ontology development: an empirical assessment. 8th Extended Semantic Web Conference (ESWC’11), G. Antoniou et al (Eds.), Heraklion, Crete, Greece, 29 May-2 June, 2011. Springer, Lecture Notes in Computer Science LNCS 6643, 321-335.

[5] Khan, Z.C., Keet, C.M. Feasibility of automated foundational ontology interchangeability. 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW’14). 24-28 Nov, 2014, Linkoping, Sweden. Springer LNAI. (accepted)

[6] Khan, Z., Keet, C.M. Addressing issues in foundational ontology mediation. 5th International Conference on Knowledge Engineering and Ontology Development (KEOD’13), Vilamoura, Portugal, 19-22 September. Filipe, J. and Dietz, J. (Eds.), SCITEPRESS, pp5-16.

KCAP13 poster on aligning and mapping foundational ontologies

I announced in an earlier post the realisation of the Repository of Ontologies for MULtiple USes ROMULUS foundational ontology library as part of Zubeida’s MSc thesis, as well as that a very brief overview describing it was accepted as a poster/demo paper [1] at the 7th International Conference on Knowledge Capture (KCAP’13) that will take place next week in Banff, Canada. The ‘sneak preview’ of the poster in jpeg format is included below. To stay in style, it has roughly the same colour scheme as the ontology library.

KCAP13romulusPoster

The poster’s content is slightly updated compared to the contents of the 2-page poster/demo paper: it has more detail on the results obtained with the automated alignments. On reason for that is the limited space of the KCAP paper, another is that a more comprehensive evaluation has been carried out in the meantime. We report on those results in a paper [2] recently accepted at the 5th International Conference on Knowledge Engineering and Ontology Development (KEOD’13). The results of the tools aren’t great when compared to the ‘gold standard’ of manual alignments and mappings, but there are some interesting differences due to—and thanks to—the differences in the algorithms that the tools use. Mere string matching generates false positives and misses ‘semantic [near-]synonyms’ (e.g., site vs. situoid, but missing perdurant/occurrent), and a high reliance on structural similarity causes a tool to miss alignments (compare, e.g., the first subclasses in GFO vs. those in DOLCE). One feature that surely helps to weed out false positives is the cross-check whether an alignment would be logically consistent or not, as LogMap does. That is also what Zubeida did with the complete set of alignments between DOLCE, BFO, and GFO, aided by HermiT and Protégé’s explanation feature.

The KEOD paper describes those ‘trials and tribulations’; or: there are many equivalence alignments that do not map due to a logical inconsistency. They have been analysed on the root cause (mainly: disjointness axioms between higher-level classes), and, where possible, solutions are proposed, such as subsumption instead of equivalence or proposing to make them sibling classes. Two such examples of alignments that do not map are shown graphically in the poster: a faltering temporal region that apparently means something different in each of the ontologies, and necessary-for does not map to generic-dependent due to conflicting domain/range axioms. The full list of alignments, mappings, and logical inconsistencies is now not only browsable on ROMULUS, as announced in the KCAP demo paper, but also searchable.

Having said that, it is probably worthwhile repeating the same caution made in the paper and previous blog post: what should be done with the inconsistencies is a separate issue, but at least now it is known in detail where the matching problems really are, so that we can go to the next level. And some mappings are possible, so some foundational ontology interchangeability is possible (at least from a practical engineering viewpoint).

References

[1] Khan, Z.C., Keet, C.M. Toward semantic interoperability with aligned foundational ontologies in ROMULUS. Seventh International Conference on Knowledge Capture (K-CAP’13), ACM proceedings. 23-26 June 2013, Banff, Canada. (poster &demo)

[2] Khan, Z.C., Keet, C.M. Addressing issues in foundational ontology mediation. Fifth International Conference on Knowledge Engineering and Ontology Development (KEOD’13). 19-22 September, Vilamoura, Portugal.

A new version of ONSET and more technical details are now available

After the first release of the foundational ONtology Selection and Explanation Tool ONSET half a year ago, we—Zubeida Khan and I—continued its development by adding SUMO, conducting a user evaluation, and we wrote a paper about it, which was recently accepted [1] at the 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW’12).

There are theoretical and practical reasons why using a foundational ontology improves the quality and interoperability of the domain ontology, be this by means of reusing DOLCE, BFO, GFO, SUMO, YAMATO, or another one, in part or in whole (see, e.g., [2,3] for some motivations). But as a domain ontology developer, and those who are potentially interested in using a foundational ontology in particular, do ask: which one of them would be best to use for the task at hand? That is not an easy question to answer, and hitherto required from a developer to pore over all the documentation, weighing the pros and cons for the scenario, make an informed decision, know exactly why, and be able to communicate that. This bottleneck has been solved with the ONSET tool. Or, at least: we claim it does, and the user evaluation supports this claim.

In short, ONSET, the foundational ONtology Selection and Explanation Tool helps the domain ontology developer in this task. Upon answering one or more questions and, optionally, adding any scaling to indicate some criteria are more important to you than others, it computes the most suitable foundational ontology for that scenario and explains why this is so, including reporting any conflicting answers (if applicable). The questions themselves are divided into five different categories—Ontology, representation language, software engineering properties, applications, and subject domain—and there are “explain” buttons to clarify terms that may not be immediately clear to the domain ontology developer. (There are a few screenshots at the end of this post.)

Behind the scenes is a detailed comparison of the features of DOLCE, BFO, GFO, and SUMO, and an efficient algorithm. The latter and the main interesting aspects of the former are included in the paper; the complete set of criteria is available in a file on the ONSET webpage. You can play with ONSET using your real or a fictitious ontology development scenario after downloading the jar file. If you don’t have a scenario and can’t come up with one: try one of the scenarios we used for the user evaluation (also online). The user evaluation consisted of 5 scenarios/problems that the 18 participants had to solve, half of them used ONSET and half of them did not. On average, the ‘accuracy’ (computed from selecting the appropriate foundatinal ontology and explaining why) was 3 times higher for those who used ONSET compared to those who did not. The ONSET users also did it slightly faster.

Thus, ONSET greatly facilitates in selecting a foundational ontology. However, I concede that from the Ontology (philosophy) viewpoint, the real research component is, perhaps, only beginning. Among others, what is the real effect of the differences between those foundational ontolgoies for ontology development, if any? Is one category of criteria, or individual criterion, always deemed more important than others? Is there one or more ‘typical’ combination of criteria, and if so, is there a single particular foundational ontology suitable, and if not, where/why are the current ones insufficient? In the case of conflicts, which criteria do they typically involve? ONSET clearly can be a useful aid investigating these questions, but answering them is left to future works. Either way, ONSET contributes to taking a scientific approach to comparing and using a foundational ontology in ontology development, and provides the hard arguments why.

We’d be happy to hear your feedback on ONSET, be this on the tool itself or when you have used it for a domain ontology development project. Also, the tool is very easy to extend thanks to the way it is programmed, so if you have your own pet foundational ontology that is not yet included in the tool, you may like to provide us with the values for the criteria so that we can include it.

Here are a few screenshots: of the start page, questions and an explanation, other questions, and the result (of a fictitious example):

Startpage of ONSET, where you select inclusion of additional questions that don’t make any difference right now, and where you can apply scaling to the five categories.

Section of the questions about ontological commitments and a pop-up screen once the related “Explain” button is clicked.

Another tab with questions. In this case, the user selected “yes” to modularity, upon which the tool expanded the question so that a way of modularisation can be selected.

Section of the results tab, after having clicked “calculate results” (in this case, of a fictitious scenario). Conflicting results, if any, will be shown here as well, and upon scrolling down, relevant literature is shown.

References

[1] Khan, Z., Keet, C.M. ONSET: Automated Foundational Ontology Selection and Explanation. 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW’12). Oct 8-12, Galway, Ireland. Springer, LNAI, 15p. (accepted)

[2] Keet, C.M. The use of foundational ontologies in ontology development: an empirical assessment. 8th Extended Semantic Web Conference (ESWC’11), G. Antoniou et al (Eds.), Heraklion, Crete, Greece, 29 May-2 June, 2011. Springer, Lecture Notes in Computer Science LNCS 6643, 321-335.

[3] Borgo, S., Lesmo, L. The attractiveness of foundational ontologies in industry. In: Proc. of FOMI’08, Amsterdam, The Netherlands, IOS Press (2008), 1-9.