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Session Track C Session 1
Duration 2 hour120 minute
7,200 second
0.0833 day
Date/Time Mar 22 2017 16:30 GMT
9:30am PDT/12:30pm EDT
4:30pm GMT/5:30pm CET
Convener DonnaFritzsche and RamSriram

Ontology Summit 2017 Track C Session 1     (2)

Note that in the US Daylight Savings Time is in effect but Europe is still on standard time     (3)

Ontologies and Reasoning     (4)

Meeting ID: 768423137     (6)

Please use the chatroom above. Do not use the video teleconference chat, which is only for communicating with the moderator.     (8)

When you use the Video Conference URL above, you will be given the choice of using the computer audio or using your own telephone. Some attendees had difficulties when using the computer audio choice. If this happens to you, please leave the meeting and reenter it using the telephone choice. You will be given a telephone number to call along with an access code.     (9)

Purpose To examine techniques for using ontologies to perform logical reasoning

Ontologies, especially those expressed using languages such as OWL, are logical theories. This track examines how one can use ontologies for logical reasoning. = Session 1, Track C: Ontologies and Reasoning     (11)


Co-Champions: Donna Fritzsche and Ram D. Sriram     (13)

Agenda     (14)

  • 12:30pm – 12:40pm     (14A)
  • 12:40pm – 1:10pm     (14B)
    • Reasoning with Ontologies in Ontohub Slides     (14B1)
    • Abstract: Reasoning with ontologies can be limited by the reasoners' resources, in particular time limits. These are often reached by reasoning problems inside large knowledge bases. The performance, however, can be increased significantly by omitting irrelevant premises when invoking the reasoner because often, only a fraction of the premises are needed for a proof. In my presentation I will show the web platform Ontohub that primarily serves as an ontology repository, but also allows to reason while utilising automated premise selection.     (14B2)
    • Bio: Eugen Kuksa is a PhD Student at the Faculty of Computer Science at the University of Magdeburg, Germany. He has a Master's degree in Computer Science and a Bachelor's degree in Mathematics from the University of Bremen, Germany. His research is on the automatic selection for automated reasoning to improve reasoning time and capability. He is developing the web platform Ontohub which is a repository for ontologies.     (14B3)
  • 1:10pm – 1:40 pm     (14C)
    • On the Roles of Logical Axiomatizations for Ontologies Slides     (14C1)
    • Abstract: Expressing ontologies by means of logical axioms serves multiple purposes. This includes inferential reasoning under the open world semantics, but is not restricted to this. Logical axioms can also be viewed as integrity constraints on the data and used for closed-world reasoning. They can serve for quality assurance purposes for ontology design, for data curation, or for generating implicit knowledge. At the same time, they also serve for disambiguation of the meaning of ontologies. In this talk, we will discuss the different roles logical axiomatizations can play and shed light on the state of the art regarding these aspects.      (14C2)
    • Bio: Pascal Hitzler is endowed NCR Distinguished Professor and Director of Data Science at the Department of Computer Science and Engineering at Wright State University in Dayton, Ohio, U.S.A. His research record lists over 350 publications in such diverse areas as semantic web, neural-symbolic integration, knowledge representation and reasoning, machine learning, denotational semantics, and set-theoretic topology. He is Editor-in-chief of the Semantic Web journal by IOS Press, and of the IOS Press book series Studies on the Semantic Web. He is co-author of the W3C Recommendation OWL 2 Primer, and of the book Foundations of Semantic Web Technologies by CRC Press, 2010 which was named as one out of seven Outstanding Academic Titles 2010 in Information and Computer Science by the American Library Association's Choice Magazine, and has translations into German and Chinese. He is on the editorial board of several journals and book series and is a founding steering committee member of the Neural-Symbolic Learning and Reasoning (NeSy) workshop series, and of the Association for Ontology Design and Patterns (ODPA). He also frequently acts as conference chair in various functions.     (14C3)
    • For more information, see     (14C4)
  • 1:40pm – 2:10pm     (14D)
    • Cognitive Probability Graphs need an Ontology Slides     (14D1)
    • Abstract: At Franz we are marketing a new concept called "the cognitive probability graph". Recently we have been involved in several semantic graph database projects where we dealt with similarity reasoning, uncertainty, probabilistic events, correlations and predictions. In this presentation, I will discuss examples from e-commerce and healthcare. I'll show how we take the results of statistics and machine learning and put it back in our semantic graph database and then visually explore the results. We believe that a more formal ontology is needed to express concepts like similarity and uncertainty. We hope that the discussions during the summit will provide additional insights into how to represent the output of various types of analytics and machine learning.     (14D2)
    • Bio: Jans Aasman started his career as an experimental and cognitive psychologist, earning his PhD in cognitive science with a detailed model of car driver behavior using Lisp and Soar. He has spent most of his professional life in telecommunications research, specializing in intelligent user interfaces and applied artificial intelligence projects. From 1995 to 2004, he was also a part-time professor in the Industrial Design department of the Technical University of Delft. Jans is currently the CEO of Franz Inc., the leading supplier of commercial, persistent, and scalable Graph Database products that provide the storage layer for powerful reasoning and ontology modeling capabilities for Cognitive Computing applications.     (14D3)
  • 2:10pm – 2:30pm     (14E)

Attendees     (15)

Proceedings     (16)

[12:29] Donna Fritzsche: welcome everyone!     (16A)

[12:33] Donna Fritzsche: Ram will speak first and the Eugen     (16B)

[12:34] Donna Fritzsche: followed by Pascal and Jans     (16C)

[12:39] FrankOlken: Any prospect of moving these sessions a little earlier, e.g. 9:00am pdt?     (16D)

[12:40] Donna Fritzsche: Hi Frank,     (16E)

[12:41] Donna Fritzsche: We moved to Wed. to better accommodate some schedules. We can reconsider next year.     (16F)

[12:42] KenBaclawski: @FrankOlken: The Summit Organizing Committee discussed this at length and also sought community feedback. We specifically considered 9:00am versus 9:30am PDT and the consensus was to stay at 9:30am PDT. We can reconsider days and times next year.     (16G)

[12:48] AndreaWesterinen: Will the slides be available?     (16H)

[12:49] Donna Fritzsche: yes, we asking that they be sent afterwards     (16I)

[12:49] Pascal Hitzler: I'll make my slides available after the talk. I've already sent mine to Ken.     (16J)

[12:49] gary berg-cross: @FrankOlken we actually tried some Summit organizing sessions at 9:00am PDT and it didn't attract any better attendance.     (16K)

[12:50] Pascal Hitzler: I can post a temporary (dropbox) link if it helps during the presentation.     (16L)

[12:51] AlexShkotin: no slides on BJN for me:-(     (16M)

[12:51] KenBaclawski: The slides are now on the meeting page. See     (16N)

[12:52] Pascal Hitzler: thanks, Ken     (16O)

[12:59] AndreaWesterinen: @Ken Thanks. I got them from the updated web page.     (16R)

[13:16] Donna Fritzsche: question for Eugen - how does the selection process/axiom narrowing relate (if at all) to the Rete Algorithm     (16S)

[13:19] Donna Fritzsche: welcome Jans!     (16T)

[13:32] Eugen Kuksa: Donna: I haven't heard of the Rete algorithm before, but as far as I can see from a quick overview, the selection process does not relate to it. In our premise selection, we use the ontology's analysis result (parsed axioms/conjectures and symbols) to pick some axioms and then write them back into a file (unchanged except for whitespace) along with the conjecture. The prover is then supplied this file.     (16U)

[13:33] MarkUnderwood: I guess Rete is too 80's :)     (16V)

[13:40] Jans Aasman: Hi: I can't start the blue jeans app, it basically totally kills my laptop     (16W)

[13:40] Jans Aasman: I'm listening via the phone and I could present via my colleagues laptop     (16X)

[13:43] Ram D. Sriram: Jans: Can you email us Ken the slides?     (16Y)

[13:45] Jans Aasman: I already did that ... can you check?     (16Z)

[13:46] Ram D. Sriram: Got it. I will ask Ken to take care of it.     (16AA)

[13:48] AndreaWesterinen: @Pascal Why wouldn't you use SPARQL Update to remove a conflicting axiom when new knowledge is added?     (16AB)

[13:49] MarkUnderwood: Would be interested in forwarding your comments to W3C if you have a position statement . . . or perhaps this is on our listserv?     (16AC)

[13:50] Ram D. Sriram: @Mark: Rete-based tools are still powerful.     (16AD)

[13:54] Pascal Hitzler: @Andrea - there are several issues with this. One is that you would have to know which axiom to remove - if the conflict comes out of a reasoning process, then it is usually a set of axioms which jointly produce the conflict. Which axiom do you want to remove then? Of course, in the particular example I gave, you'd only want to remove the moreBiodiverseThan relations, so your suggestion would be a work-around. But at the same time, it seems conceptually awkward, a "hack", to deal with it that way.     (16AE)

[13:55] Pascal Hitzler: @Mark were you refering to the SHACL comments?     (16AF)

[13:55] Pascal Hitzler: Ah no, it was part of the Rete discussion (forget my comment).     (16AG)

[13:56] Pascal Hitzler: I have to sign off at 2pm, feel free to contact me by email if there are any further questions.     (16AH)

[13:56] MarkUnderwood: @Pascal, ack'd. but would like to provide W3C feedback if you have not already done so.     (16AI)

[13:56] AndreaWesterinen: @Pascal I have been able to work around some of these issues by using named graphs to store the reasoning results (or perhaps different beliefs of different people/groups), and then analyzing the differences between the reasoning results.     (16AJ)

[13:57] AndreaWesterinen: @Ken The link to Jan's slides (on the call page) result in an access denied.     (16AK)

[13:58] Pascal Hitzler: @Andrea: yes that's a way how to do it while using current standards. So from that perspective it's a "practical" solution. As a researcher, though, I'd be happier if a more principled solution could be developed (and at some stage be standardized).     (16AL)

[13:59] KenBaclawski: @[13:32] Eugen Kuksa: One can easily constrain a Rete network to include only a subset of the rules. In fact, it is a normal practice to prioritize rules.     (16AM)

[14:00] KenBaclawski: @AndreaWesterinen: Jan's slides will be publicly released after the meeting.     (16AN)

[14:01] AndreaWesterinen: @Pascal Given current tools and simplicity of the solution, I have found this approach valuable but would be happy for a "more principled" solution - as long as it is still simple. :-)     (16AO)

[14:01] FabianNeuhaus: @Ken: Do you have a reference about constraining a Rete network in the way you describe?     (16AP)

[14:02] Pascal Hitzler: @Andrea - no objections here :)     (16AQ)

[14:06] FabianNeuhaus: @Donna: the axiom selection algorithm that Eugen presented is very different from Rete. The Rete algorithm is basically just an efficient way of executing simple rules and, thus, forward chaining. Eugens algorithm works on any monotonic logic (including higher-order logic) and it works backwards from the conjecture.     (16AR)

[14:24] gary berg-cross: Have to head off to an in town meeting. Will work on Track A synthesis in prep for next week's session.     (16AS)

[14:29] Donna Fritzsche: thankyou Fabian     (16AT)

[14:31] Donna Fritzsche: Thank-you to our speakers and audience.     (16AU)

Resources     (17)

Previous Meetings     (18)