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OWLED 2014: Day 1 LiveBlogging

Bijan here!

I’ll be liveblogging (as much as I can) the OWLED 2014 sessions in this post (so refresh often). Also trying to tweet it.

I’m such a social media butterfly!

Check out the programme! And the proceedings.


Opening (Bijan)
Key things:

  • Getting the community group active.
  • New specs!
  • Folding in ORE
  • Next OWLED

Session 1:


First talk, “Nicolas Matentzoglu and Bijan Parsia. The OWL Full/DL gap in the field” (Nico presenting).

Motivation: We were assembling a corpus for a(n OWL DL) reasoner competition. OWL Full is a “problem” for us.

(David: Current OBO is well within OWL DL now!)

Measuring the Gap: In our corpus: 81% OWL Full. <– prima facie odd! (For OWL DL folks :))
Nice tour of how things can be OWL Full in a “silly” way (lack of declarations, sub property of rdfs:label) with concrete examples.
After fixing the “silly” violations, we end up 40% OWL Full (50% reduction).
Declaration failures <– Ugh!
Reserved vocabulary “misuse”: Subpropertying rdfs:label seems harmless. SubClassOf(A, rdf:type) less so.

Procedure: Crawl based corpus. Load and get metrics (using OWL API profile check). Repair. Check metrics.
2/3s of the violations are Declaration Failures!!
(Chitchat about reserved vocabulary)

Point: Old OBO translator is suboptimal. Update to the latest OWL API.
Question: Can I get the fixed versions? Sure!
Question: Versions in corpus? We didn’t sanitise it beyond some minor automated stuff.


David Carral, Adila Krisnadhi, Sebastian Rudolph and Pascal Hitzler. All But Not Nothing: Left-Hand Side Universals for Tractable OWL Profiles presented by Adila.

Problems with universals (vacuous applicability).
If you say All X are Y, we normally assume that there’s at least one X.
“onlySome” R only C and R some C <–coupled! (Common “good practice”)
Called “witnessed universal”

Can be added to OWL EL (and horn-SROIQ) without compromising polynomiality but only on LHSs.
Shown by a rewriting into ELH.

Proposed some syntax extensions. (This doesn’t work for OWL RL or QL.)


Question: Doesn’t this destroy the “arbitrary use of contructs property”? Yes, but we don’t know how this affect modellers.
Question: Can we use this with ELK? yes.
Question: What entailments does this support? In EL we can’t see any? Dunno! Good question.


Nicolas Matentzoglu and Bijan Parsia. OWL/ZIP: Distributing Large and Modular Ontologies presented by Nico

How do we distribute large and modularised ontologies?

Even if people distribute ZIPPED archives…no standard “starting” point.
AutoModularized ontologies can have hundreds of modules.

Key results:

  • Compression rates of 80-90% with greater rates on larger ontologies
  • Load time: (Note, unzip to disk, so pessimal): up to 90% overhead, but dropping to 50% for ontologies that take >1sec to load.

We want to standardise this sort of thing!


Question: Carole Goble has been working on Research Objects and packaging them together so maybe look at that? (Also, they go further with ) There are some binary formats like this one HDT for RDF that adds indexing.
Question: What about versioning? Big general issue.
Question: Also collections.

Nico: apt-get for ontologies (ont-get).



David Osumi-Sutherland, Marta Costa, Robert Court and Cahir O’Kane. Virtual Fly Brain – Using OWL to support the mapping and genetic dissection of the Drosophila brain. presented by David.

Going to talk about the Fly Brain instead 🙂
~200,000 neurons (5-10,000 types?)

Neurons have many structural and behavioural properties used for classification.

Complicated literature for published neurone classes.

Drosophila anatomy ontology
42% on the nervous system
50% of >10,000 classifications inferred.

Following the Rector normalisation pattern.

Richly annotations and axiomatised. Imports a bit of GO.
Expressiveness is ~EL without explicit nested class expressions.

“Brain region classes are defined with reference to volumes in standard brain.”

“part of” not as helpful as “part in” for neurone (i.e., they have parts in lots of other things). Various specific specialisations of “overlaps”.

QUESTION: Michel had some issue with using role chains instead of generic part of (query issue).

Discussion of image queries (nested expressions! :))

Beyond EL!

“Complete knowledge of spatial information about neurone is common”


Question: Can you reconstruct the full neuron track information? Yes, we have all this low level microscopy and then [argble bio bargle].
Question: Do you need negation or epistemic negation? Our closure works except for scaling and it uses e.g., our role chains etc.


Chris Mungall, Heiko Dietze and David Osumi-Sutherland. Use of OWL within the Gene Ontology presented by David.

Historic conception of GO/OBO as DAG.
Then translation into FOL which was ditched.
New version of the translation by Horrocks et al.

Design patterns in GO (pre formalisation) which improved quality.

OBO(1.4) is OWL (yay!)
Roundtripping is effective.

Go comes in lots of versions and the default version is axiom-light.

TermGenie: Web based, templated term submission (with inference checking!) (Sounds supercool)

More about property chains and partonomy.

Nice discussion of “challenges of inputs”

OBO Relations Ontology

Spatial disjointness

Taxon constraints via macro expansions.

OBO format discussion: list of valuable properties (hackability important) Big ones: Readable diffs and easy stable VC.

QUESTION: What makes it VC friendly? Standard pretty printing of serialisation. R: So we could lift this to other syntaxes?

Moving all editing to Protege via plugins.

Managing inference. GO caches inferences in file. Very bad editing cycle at the moment.
Plans to speedup cycle.

Smuggling a Little EL into databases! Class expressions for annotators.

Rise of the ABoxes (standard conversion of GO annotations to ABox individuals.) Having links of annotations to give fuller narratives.


Question: Are the annotation structures related to research object or micro-/nano-publications? Offline!
Question: What’s up with the properties? (loads of discussion)


Keynote: Nicola Guarino. On the semantics of reified relationships

The intro is a bit weird. If you are going to explain how you’re different from the OWL community to have a reasonable understanding of the OWL community, e.g., we just had a two talks on content!

Relations vs. Relationships. Reification of relationships. Facts (true propositions) vs. episodes (truth makers). How episodes and events relate.

Relation is a class of tuples. Relationship is a tuple.
Both relation and relationships  can be reified.
Cardinality constraints are on relations.
We might have constraints on relationships. [[BJP: I didn’t understand the example of at most 1 spouse at a time]]

Common reifications: as assertions, as facts (situations/true propositions), as perdurants (events)

Propositions are true or false at certain times. Facts are true propositions. Events are world-bits that exemplify or instantiate a propositions. Situations are kinds of events. Events are time localised.

Episodes.  Endurants (entities persisting in time) and perdurants (entities that happen in time). Person vs. a talk.
Ordinary endurance are called objects
No standard term for ordinary perdurants (event, happening, situation, etc.)
Episode: a large class of relevant perdurants.

  • Relevants
  • unity criterion (maximality)
    • time and context

Episode are perception relevant (context is perceptually bound).

Kinds of relationships (a rough taxonomy)

  1. Permanent relationships
    1. Essential (greater(3,2))
    2. Contingent
      1. instrinsic: same-blood-group(John, Mary)
      2. extrinsic: born-in(John, Brazil)
  2. Temporary relationships
    1. Intrinsic: taller(John, Mary)
    2. Extrinsic: loves(John, Mary)

All temporary relationships require an episode as their truth maker
Some permanent relationships (extrinsic) require  an episode as their truth maker

Whenever there’s a time varying property, consider putting truth-making episodes in domain of discourse.

Episodes are better than events because events are too limited?


Matthew Horridge, Csongor I Nyulas, Tania Tudorache and Mark Musen. WebProtégé: a Web-based Development Environment for OWL Ontologies presented by Matthew.

Google Docs for OWL ontologies.
10,000 projects; 300_ users

“Horrified to find out that WebProtege has been around for quite a while.”

WebProtege 1.0 based on Protege 3. WebProtege 2 with new UI and based on the OWL API. Simplified UI plus better OWL 2 support for experts.

OpenSource usign GWT hosted on GitHub. Locally installable.


(In particular the reasoning architecture is awesome.)

Simple profile coverage (i.e., what the simplified interface can handle)

Custom form editor!

GitHub integration as a future option.


Ewa Kowalczuk, Jędrzej Potoniec and Agnieszka Lawrynowicz. Extracting Usage Patterns of Ontologies on the Web: a Case Study on GoodRelations Vocabulary in RDFa presented by Ewa.

Analysis of GoodRelation annotations published on the web in RDFa.

Try to show a bunch of stuff, including OWL usage, that our pattern tool works, etc.

Used Web Data Commons extracted from Common Crawl.

Fr-ONT-Qu example.

over 2.6 billion quads

They used recursive concise bounded descriptions (haven’t seen those in AGES).

(Ooops, I got caught up with playing with WebProtege! Bad liveblogger!)

We’re in a discussion of good vs. bad  patterns (expressed as sparql queries) found.

The OWL pattern is a bit odd! Seems to reference without using the ontology.

Results are online:



Alexander Šimko and Ondrej Zamazal. Towards Searching for Transformation Patterns in Support of Language Profiling

Automating of Ontology Analsyis something something (not in programme!)
Ontology summaries, roughly. Ultimately determine relation between features in ints and aspects of tools.

Catalina Martínez Costa and Stefan Schulz. An example of approximating DL reasoning by ontology-aware RDF querying
Motivated by semantic interoperability problem in diagnosis support systems.

Rafael Peñaloza and Aparna Saisree Thuluva. COBRA, a Demo
Sub-ontologies offered as views. Instead of materialising each subontologies, synthesise a single ontology. Context based stuff.

Zubeida Khan and C. Maria Keet. The ROMULUS resource for using foundational ontologies
FO are hard: philosophical notions, which one, link to which, scability.

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