Apologies for cross-posting.
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CALL FOR PAPERS
20th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2016)
19-23 November 2016, Bologna, Italy
Abstract submission: July 8, 2016
Paper submission: July 15, 2016
Web site: http://ekaw2016.cs.unibo.it/ <http://ekaw2016.cs.unibo.it/>
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The 20th International Conference on Knowledge Engineering and Knowledge Management is concerned with the impact of time and space on the representation of knowledge. Knowledge engineering has mostly been about creating static, universal representations. Yet the world is rarely static: everything changes, including the models, and real world systems need to evolve along with the surrounding world. Also, what makes some representations valid in some contexts may make them invalid elsewhere (e.g., jurisdiction for laws).
The special focus of this year's EKAW is "evolving knowledge", which concerns all aspects of the management and acquisition of knowledge representations of evolving, contextual, and local models. This includes change management, trend detection, model evolution, streaming data and stream reasoning, event processing, time-and space dependent models, contextual and local knowledge representations, etc.
EKAW 2016 will put a special emphasis on the evolvability and localization of knowledge and the correct usage of these limits.
== PROCEEDINGS ==
The proceedings of the research and in-use track will be published by Springer Verlag in the LNCS series.
== TOPICS OF INTEREST ==
EKAW 2016 welcomes papers dealing with theoretical, methodological, experimental, and application-oriented aspects of knowledge engineering and knowledge management.
In particular, but not exclusively, we solicit papers about methods, tools and methodologies relevant with regard to the following topics:
Knowledge in evolving and local contexts
Model evolution
Ontology evolution
Ontology debugging
Ontology change management and versioning
Ontology usage trends
Methods and methodologies for time awareness
Modelling of time-indexed knowledge
Ontology design patterns for time-indexed knowledge
Reasoning over time-indexed knowledge
Stream processing and stream reasoning
Event processing
Methods and methodologies for context awareness
Modelling of contextualised knowledge
Ontology design patterns for representing context
Reasoning with context
Context-aware knowledge-based applications
Lessons learned from case studies
Knowledge management in large organisations
Adoption of semantic web technologies
Maintenance of corporate knowledge repositories
Applications in specific domains domains such as
eGovernment and public administration
Life sciences, health and medicine
Humanities and Social Sciences
Automotive and manufacturing industry
Cultural heritage
Digital libraries
Geosciences
ICT4D (Knowledge in the developing world)
Knowledge Management
Methodologies and tools for knowledge management
Knowledge sharing and distribution, collaboration
Best practices and lessons learned from case studies
Provenance and trust in knowledge management
Methods for accelerating take-up of knowledge management technologies
Corporate memories for knowledge management
Evolution, maintenance and preservation of knowledge
Web 2.0 technologies for knowledge management
Incentives for human knowledge acquisition (e.g. games with a purpose)
Knowledge Engineering and Acquisition
Tools and methodologies for ontology engineering
Ontology design patterns
Ontology localisation
Ontology alignment
Knowledge authoring and semantic annotation
Knowledge acquisition from non-ontological resources (thesauri, folksonomies etc.)
Semi-automatic knowledge acquisition, e.g., ontology learning
Mining the Semantic Web and the Web of Data
Ontology evaluation and metrics
Uncertainty and vagueness in knowledge representation
Dealing with dynamic, distributed and emerging knowledge
Social and Cognitive Aspects of Knowledge Representation
Similarity and analogy-based reasoning
Knowledge representation inspired by cognitive science
Synergies between humans and machines
Knowledge emerging from user interaction and networks
Knowledge ecosystems
Expert finding, e.g., by social network analysis
Trust and privacy in knowledge representation
Collaborative and social approaches to knowledge management and acquisition
Crowdsourcing in knowledge management
== TYPE OF PAPERS ==
We will accept different types of papers. The papers will all have the same status and follow the same formatting guidelines in the proceedings but will receive special treatment during the reviewing phase. In particular, each paper type will be subject to its own evaluation criteria. The Programme Committee will also make sure that there is a reasonable balance of the paper types accepted. At submission time the paper has to be clearly identified as belonging to one of the following categories.
Research papers: These are "standard" papers presenting a novel method, technique or analysis with appropriate empirical or other types of evaluation as a proof-of concept. The main evaluation criteria here will be originality, technical soundness and validation.
In-use papers: Here we are expecting papers describing applications of knowledge management and engineering in real environments. Applications need to address a sufficiently interesting and challenging problem on real-world datasets, involving many users etc. The focus is less on the originality of the approach and more on presenting systems that solve a significant problem while addressing the particular challenges that come with the use of real-world data. Evaluations are essential for this type of paper and should involve a representative subset of the actual users of the system.
Position papers: We invite researchers to also publish position papers, which describe novel and innovative ideas. Position papers may also comprise an analysis of currently unsolved problems, or review these problems from a new perspective, in order contribute to a better understanding of these problems in the research community. We expect that such papers will guide future research by highlighting critical assumptions, motivating the difficulty of a certain problem or explaining why current techniques are not sufficient, possibly corroborated by quantitative and qualitative arguments.
== IMPORTANT DATES ==
Abstract deadline: July 8, 2016
Submission deadline: July 15, 2016
Notification of acceptance: September 8, 2016
Camera-ready paper: September 26, 2016
Conference days: November 19-23, 2016
== SUBMISSIONS ==
Pre-submission of abstracts is a strict requirement. All papers and abstracts have to be submitted electronically via http://www.easychair.org/conferences/?conf=ekaw2016 <http://www.easychair.org/conferences/?conf=ekaw2016>.
All research and in-use submissions must be in English, and no longer than 15 pages. Papers that exceed this limit will be rejected without review.
Submissions must be either in PDF or in HTML, formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). For details on the LNCS style, see Springer's Author Instructions (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0 <http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>). For details on the HTML format, see the HTML submission guide (http://ekaw2016.cs.unibo.it/?q=html-submission-guide <http://ekaw2016.cs.unibo.it/?q=html-submission-guide>).
== ORGANIZATION ==
General chair
Paolo Ciancarini (University of Bologna, Italy)
Program chairs
Eva Blomqvist (Linköping University, Sweden)
Fabio Vitali (University of Bologna, Italy)
Hi Stas, hi all,
I just noted that BlazeGraph seems to contain a few erroneous triples.
The following query, for example, returns a blank node "t7978245":
SELECT ?superClass WHERE {
<http://www.wikidata.org/entity/Q595133> p:P279/ps:P279 ?superClass
}
https://query.wikidata.org/#SELECT%20%3FsuperClass%20WHERE%20{%0A%20%20%3Ch…
I stumbled upon six cases like this (for P279): Q595133 (shown above),
Q1691488, Q11259005, Q297106, Q1293664, and Q539558. This would be less
than 0.001% of the 623,963 P279 statements, but it's still enough to
have application code trip over the unexpected return format ;-).
Best
Markus
--
Markus Kroetzsch
Faculty of Computer Science
Technische Universität Dresden
+49 351 463 38486
http://korrekt.org/
Hoi,
I added a book that is very notable in the Netherlands to Wikidata. It has
several authors and most of them do not have Wikipedia articles. There were
no photos available either. I did ask one of the authors for pictures and
now there are four.
The point is very much that exactly in the same way as it can be done for
Wikipedia articles we can seek pictures to illuminate our work. Reasonator
does show the pictures [1] wherever these people are mentioned.
PS I am also seeking pictures of all the authors together to add to the
book itself.
Thanks,
GerardM
[1] https://tools.wmflabs.org/reasonator/?&q=22070167
Hi Tom,
Thanks for your message, you are touching upon a very crucial point, the
justification of completeness. For several properties, completeness is
clearly impossible ("SignificantEvent", "Occupation", "AwardsReceived" -
what is significant, what counts as an occupation, and didn't everyone once
win something like the 2nd place in the school chess tournament?).
Still, for some properties, we believe stating completeness to be
justified, or at least no more unjustified than entering data. Are Malia
and Sasha all children of Obama? To the best of common knowledge yes, and
if we are to doubt this, we might similarly doubt whether Malia is a child
of Obama at all, so stating completeness looks to me no less justified than
stating that Malia is a child of Obama.
Regarding the other aspect you mention, the time variance of data, the best
we can think of is to qualify completeness statements with an "as-of"
timestamp.
"Malia and Sasha are all children of Obama, as of 2nd of March, 2016".
Besides that there may be a portion of well-known history that is not going
to change any more, such as "founders of Apple", "Kings of the Italian
Monarchy", "Participant nations in the 2012 Olympics" and similar, where
time does not play a role.
Deciding and agreeing for which properties completeness assertions make
sense and for which not would probably require a significant effort by the
domain experts (i.e. you, the Wikidata authors), the above examples are
only guessed.
Do you know potentially of any guidelines/agreements in Wikidata to decide
which properties ("child") are more well defined, and which ones
("significantEvent") are not?
Thanks and best wishes,
Simon
Hello Wikidata community!
Wikidata is a great platform for collecting information, and the high
quality work of many authors yields very reliable information.
Still, a challenge for users of Wikidata is that there is no way to see
whether *all* data on a certain topic is in Wikidata.
For instance, it is easy to see that Malia and Sasha are children of Obama,
but there is no way to specify that these are all his children.
More generally, Wikidata stores many facts, but it stores no information
about which topic it contains all facts.
Today we are happy to share with you a prototype that allows to add and
manage such completeness information,
and would be happy to get your feedback on how useful you consider this
tool, or where you see space for improvements.
With our prototype, called COOL-WD (Completeness Tool for Wikidata), one
can:
1. See completeness statements for Wikidata facts
2. Add, remove, aggregate and filter completeness statements
3. See how completeness statements allow conclusions about the completeness
of SPARQL queries over Wikidata.
COOL-WD is available at http://cool-wd.inf.unibz.it/ and a 3-min demo video
can be found at http://cool-wd.inf.unibz.it/coolwd-hd.mp4
It employs various libraries, most importantly GWT, Apache Jena, SQLite and
the Wikidata API.
The formal background and description of the tool including an indexing
technique for completeness statements
have been accepted as a research paper at ICWE 2016 (
http://icwe2016.inf.usi.ch/) available to download at: http://bit.ly/1VOsRCH
Below are some naive ideas of how completeness could be useful to users:
> Use Case 1: Rido is a geographer who would like to contribute to Wikidata
about the administrative divisions of regions.
He cares so much about data quality, especially data completeness, and is
collaborating with Simon, another geographer.
However, when completing data on Wikidata, there is currently no way to
mark which data is complete.
Rido and Simon must make these notes about completeness manually in, say, a
Google Doc.
Worse still, the effort from Rido and Simon to complete data could not be
appreciated by Wikidata users since to the users’ eyes,
there is no difference between complete data and incomplete data on
Wikidata.
Demo: Wikidata is complete for all administrative divisions of Saxony (
http://cool-wd.inf.unibz.it/?p=Q1202)
> Use Case 2: Jen is a developer of a moviegoer application. She usually
integrates data between multiple sources including Wikidata.
If some movies on Wikidata have completeness statements, she might optimize
her application
to not search in other data sources for those movies.
Demo: So, when her app is asking on COOL-WD at
http://cool-wd.inf.unibz.it/?p=query
for cast and screenwriters of the movie Before Sunset (
http://cool-wd.inf.unibz.it/?p=Q652186):
SELECT * WHERE { wd:Q652186 wdt:P161 ?c . wd:Q652186 wdt:P58 ?s }
Her app gets not only query answers but also the completeness information
of her query.
We are looking forward to your feedback!
Best,
Fariz, Simon, Rido, and Werner
Free University of Bozen-Bolzano, Italy
(Cross-posting)
For Wikimedia folks who are interested in possible collaborations with OSM,
now seems like a good time to start thinking about possible presentations.
Staff from the Wikimedia Foundation, and/or Wikimedia volunteers from
around the US outside of the Seattle area, may want to start thinking about
travel plans.
For Wikimedia volunteers outside of Cascadia Wikimedians territory, you
might consider applying for WMF Travel and Participation Support grants [1].
If you're inside of Cascadia Wikimedians territory and would like to attend
the conference, we may have funds in our budget that can support your
attendance. Contact me off-list for details.
Regards,
Pine
[1] https://meta.wikimedia.org/wiki/Grants:TPS
---------- Forwarded message ----------
From: Clifford Snow <clifford(a)snowandsnow.us>
Date: Tue, Mar 1, 2016 at 5:18 PM
Subject: [opensource-107] Seattle to host the 2016 OpenStreetMap State of
the Map US Conference
To: opensource-107-announce(a)meetup.com
I am excited to announce that Seattle was chosen to host the OpenStreetMap
2016 State of the Map US Conference. The conference will take place July
23-25 on SeattleU's campus. We chose SeattleU for their low cost, proximity
to Seattle and access to public transit. The food trucks near by didn't
hurt either.
We are looking for help! Let us know if you want to help. Request for
presentation proposals should be coming fairly soon. Start thinking about
what you want to present or teach.
The formal announcement can be found at:
https://openstreetmap.us/2016/02/sotmus-2016/
Clifford