2nd CFP: AAAI 2011 Fall Symposium on Open Government Knowledge: AI Opportunities and Challenges
Li Ding <[email protected]> Sat, 14 May 2011 00:47:12 -0400
| Newsgroups | gmane.comp.web.rdf,gmane.comp.web.rdf.logic,gmane.comp.web.services.general |
|---|---|
| Message-ID | <[email protected]> |
This is a multi-part message in MIME format.
--------------020508000900070503040401
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: 7bit
Please accept our apology for cross-posting and thank you for your time
------------------------------------------------------------------------------------------------
AAAI 2011 Fall Symposium
Open Government Knowledge: AI Opportunities and Challenges
4-6 November 2011 . Arlington, Virginia USA
submission site open now. paper due by June 3, 2011
------------------------------------------------------------------------------------------------
The 2011 AAAI Fall Symposium on Open Government Knowledge: AI
Opportunities and
Challenges (OGK2011) seeks papers on all aspects of publishing public
government data as reusable knowledge on the Web. Both long papers
presenting
research results and shorter papers describing late breaking work,
outlining
implemented systems, identifying new research challenges, or articulating a
position are invited. Submissions are due by June 3, notifications will
be sent
by July 15, and the final camera-ready copy must be provided by
September 9,
2011.
Background
Websites like data.gov, research.gov and USASpending.gov aim to improve
government transparency, increase accountability, and encourage public
participation by publishing public government data online. Although
industry and academia have used these for some intriguing applications,
the data in its present form is hard for citizens to understand and use.
Research and deployment challenges emerging from open government data
practices include the following.
* Scalability. How can we search, access and reuse the hundreds of
thousands of datasets from data.gov as well the much larger number of
datasets directly available at federal agencies' website? Is there an
organic way to dramatically increase the amount of open government data
in a distributed and collaborative fashion?
* Interoperability. Multi-scale open government data came from city
governments, state governments, and national governments. How can one
compare the GDP of the US and China, and later link to state-level
financial data? Open government data covers many domains. How can one
associate open government data with domain knowledge to build, e.g. a
cancer prevention application?
* Provenance and quality. How should provenance be leveraged to
facilitate high-quality data management interactions (e.g. reuse,
mash-up and feedback) and community participation between the government
and the public?
* Citizen Involvement. How can linked data application sites encourage
more citizen participation for comments and contributions, and then how
can these more diverse contributions be tracked, managed, validated, and
evaluated?
Several approaches have been proposed to address these challenges. Using
semantic technologies, especially Linked Data, to enrich the value of
such data and ultimately convey the data to the citizens is one
possibility. For example, linking together Justices' backgrounds, and
related supreme court decisions has the potential to provide a better
understanding of the working of the Supreme Court. Linked Open
Government Data are enabled by Semantic Web technologies such as RDF,
RDFS, SPARQL and RDFa. Once linked, the value of government data can be
greatly increased with a potential reduction of cost (i) applications
are no longer limited to one or several datasets but can use all the
inter-connected datasets (including non-government data) on the Web;
(ii) data-as-interface allow data curators, visualizers and analysts
incrementally work on a specific smaller part of data processing
independently, (iii) linked data enables transparent data mining and
generates detailed provenance traces that allow the study of trust,
privacy and policy issues. Using crowd-sourcing to distribute the task
of building parsers and visualizers for different data.gov datasets is
another possibility. Machine learning to find and explore relationships
between data is also a possible approach.
Secondly, for governments to be able to release high quality datasets,
they must be able to express usage access and restriction policies. To
achieve this, provenance mechanisms must be provided to keep track of
which datasets have been used and how these have been combined and
policy mechanisms must be used to ensure compliance with appropriate
usage restrictions. This involves several interesting areas of research:
machine understandable usage restrictions, provenance tracking and
maintenance, and scalable reasoners capable of verifying policy compliance.
Lastly, the techniques developed for extracting semantics, using, and
sharing open government datasets can also be applied to closed/secure
datasets for applications such as sharing private information
within/across agencies, and integrating electronic health records across
healthcare organizations. In this symposium, we invite input from
diverse communities including but not limited to: government data
publishers, developers, user communities who run real systems and
generate demand for new technologies, and the AI community who can
provide solutions and advance the research in the areas specified above.
The location of symposium is extremely attractive since a lot of open
government data practitioners are conveniently located in Washington, DC.
Suggested Topics include but are not limited to the following
* Automatic and semi-automatic creation of linked data resources
* General ontologies for open linked government data
* Entity linking and co-reference detection between linked data resources
* Adding temporal qualifications to government data
* Creating mash-ups with open government data
* Scalable solutions for linking open government data
* Linked open government data analysis
* Semantic technologies for government data and applications
* Representing and propagating provenance metadata
* Policies for information sharing, use, and privacy
* Managing usage restrictions and privacy of government data
* Metadata for certainty and trust in linked open government data
* Social networks in government data
* Publishing results of machine learning applied to open government data
* Visualization of open government data revealing underlying patterns
and relations
Symposium structure
This single track symposium will run from 9:00am Friday November 4 until
12:30pm Sunday November 6 and include a mixture of invited talks, paper
presentations, panels, system demonstrations, a poster session, and
discussions. We plan to have several invited speakers, e.g., a US
federal Government representative addressing the current status of the
US open government initiative, a researcher discussing open challenges
and a W3C staff member describing the role of current and future
standards in government knowledge. We will also have a panel to address
the emerging issue of health informatics, the potential nationwide
health information network, where private health data and public
governmental data are interconnected. We are also interested in running
a half-day tutorial/hack-a-thon to provide attendees hands-on
experiences in creating Linked Open Government Data and building mashups.
Submissions
We invite submissions of full papers (up to eight pages) presenting
research results and short papers (up to four pages) defining a
position, articulating a new problem or describing a working system.
Papers must be prepared in AAAI format and submitted using the ogk2011
easychair site (http://www.easychair.org/conferences/?conf=ogk2011). All
accepted papers will be published in a proceedings issued as a AAAI
technical report. Papers should be original material that has not been
previously published or under review for another venue. Late breaking
ideas are encouraged as the subject of a short papers.
Important dates
* 3 June 2011 Submit papers using the ogk2011 site
* 15 July 2011 Notifications sent to authors
* 9 Sept 2011 Camera ready papers due
* 16 Sept 2011 author registration deadline
* 14 Oct 2011 Open pre-registration deadline
* 3 Nov 2011 AI Funding seminar
* 4-6 Nov 2011 Fall Symposium
General symposium information
General information on the 2011 AAAI Fall Symposia will be available
from the 2011 AAAI FSS Website. This includes information about
deadlines, registration, location, transportation, and hotel
accommodations.
Organizers
* Li Ding, Rensselaer Polytechnic Institute
* Tim Finin, UMBC
* Lalana Kagal, MIT
* Deborah McGuinness, Rensselaer Polytechnic Institute
Program committee
* Hal Abelson, MIT, USA
* Quan Bai, CSIRO, Australia
* David Chadwick, Kent University, UK
* Vinay Chaudhri, SRI, USA
* Nick Gibbins, University of Southampton, UK
* Karthik Gomadam, Accenture Technology Labs, USA
* Stuart Graham, USPTO, USA
* Alon Halevy, Google, USA
* Andreas Harth, KIT, DE
* Michael Hausenblas, DERI Galway, Irland
* Sandro Hawke, W3C, USA
* Anupam Joshi, UMBC, USA
* David Karger, MIT, USA
* Gary Katz, MarkLogic, USA
* Qing Liu, CSIRO, Australia
* Ashok Malhotra, Oracle, USA
* Natasha Noy, Stanford University, USA
* Theresa Pardo, SUNY Albany, USA
* Vassilios Peristeras, European Commission, Belgium
* Alexander Pretschner, Karlsruhe Institute of Technology, Germany
* Alan Ruttenberg, SUNY Buffalo, USA
* Satya Sahoo, Case Western Reserve, USA
* Abdul Shaikh, NIH/NCI, USA
* Kavitha Srinivas, IBM Research, USA
* Joshua Tauberer, POPVOX, USA
* George Thomas, HHS, USA
* Curt Tilmes, NASA Goddard, USA
* Evelyne Viegas, Microsoft Research, USA
* David Wood, Talis, UK
* Peter Yeh, Accenture Technology Labs, USA
* Harlan Yu, Princeton, USA
--------------020508000900070503040401
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: 7bit
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<meta http-equiv="content-type" content="text/html; charset=ISO-8859-1">
</head>
<body text="#000000" bgcolor="#ffffff">
<div class="moz-text-html" lang="x-western"> Please accept our
apology for cross-posting and thank you for your time<br>
<br>
<div class="moz-text-flowed" style="font-family: -moz-fixed;
font-size: 14px;" lang="x-western">------------------------------------------------------------------------------------------------
<br>
AAAI 2011 Fall Symposium <br>
Open Government Knowledge: AI Opportunities and Challenges <br>
4-6 November 2011 • Arlington, Virginia USA <br>
<br>
submission site open now. paper due by June 3, 2011 <br>
------------------------------------------------------------------------------------------------
<br>
<br>
The 2011 AAAI Fall Symposium on Open Government Knowledge: AI
Opportunities and <br>
Challenges (OGK2011) seeks papers on all aspects of publishing
public <br>
government data as reusable knowledge on the Web. Both long
papers presenting <br>
research results and shorter papers describing late breaking
work, outlining <br>
implemented systems, identifying new research challenges, or
articulating a <br>
position are invited. Submissions are due by June 3,
notifications will be sent <br>
by July 15, and the final camera-ready copy must be provided by
September 9, <br>
2011. <br>
<br>
<br>
Background <br>
<br>
Websites like data.gov, research.gov and USASpending.gov aim to
improve government transparency, increase accountability, and
encourage public participation by publishing public government
data online. Although industry and academia have used these for
some intriguing applications, the data in its present form is
hard for citizens to understand and use. Research and deployment
challenges emerging from open government data practices include
the following. <br>
<br>
* Scalability. How can we search, access and reuse the hundreds
of thousands of datasets from data.gov as well the much larger
number of datasets directly available at federal agencies'
website? Is there an organic way to dramatically increase the
amount of open government data in a distributed and
collaborative fashion? <br>
* Interoperability. Multi-scale open government data came from
city governments, state governments, and national governments.
How can one compare the GDP of the US and China, and later link
to state-level financial data? Open government data covers many
domains. How can one associate open government data with domain
knowledge to build, e.g. a cancer prevention application? <br>
* Provenance and quality. How should provenance be leveraged to
facilitate high-quality data management interactions (e.g.
reuse, mash-up and feedback) and community participation between
the government and the public? <br>
* Citizen Involvement. How can linked data application sites
encourage more citizen participation for comments and
contributions, and then how can these more diverse contributions
be tracked, managed, validated, and evaluated? <br>
<br>
Several approaches have been proposed to address these
challenges. Using semantic technologies, especially Linked Data,
to enrich the value of such data and ultimately convey the data
to the citizens is one possibility. For example, linking
together Justices' backgrounds, and related supreme court
decisions has the potential to provide a better understanding of
the working of the Supreme Court. Linked Open Government Data
are enabled by Semantic Web technologies such as RDF, RDFS,
SPARQL and RDFa. Once linked, the value of government data can
be greatly increased with a potential reduction of cost (i)
applications are no longer limited to one or several datasets
but can use all the inter-connected datasets (including
non-government data) on the Web; (ii) data-as-interface allow
data curators, visualizers and analysts incrementally work on a
specific smaller part of data processing independently, (iii)
linked data enables transparent data mining and generates
detailed provenance traces that allow the study of trust,
privacy and policy issues. Using crowd-sourcing to distribute
the task of building parsers and visualizers for different
data.gov datasets is another possibility. Machine learning to
find and explore relationships between data is also a possible
approach. <br>
<br>
Secondly, for governments to be able to release high quality
datasets, they must be able to express usage access and
restriction policies. To achieve this, provenance mechanisms
must be provided to keep track of which datasets have been used
and how these have been combined and policy mechanisms must be
used to ensure compliance with appropriate usage restrictions.
This involves several interesting areas of research: machine
understandable usage restrictions, provenance tracking and
maintenance, and scalable reasoners capable of verifying policy
compliance. <br>
<br>
Lastly, the techniques developed for extracting semantics,
using, and sharing open government datasets can also be applied
to closed/secure datasets for applications such as sharing
private information within/across agencies, and integrating
electronic health records across healthcare organizations. In
this symposium, we invite input from diverse communities
including but not limited to: government data publishers,
developers, user communities who run real systems and generate
demand for new technologies, and the AI community who can
provide solutions and advance the research in the areas
specified above. The location of symposium is extremely
attractive since a lot of open government data practitioners are
conveniently located in Washington, DC. <br>
Suggested Topics include but are not limited to the following <br>
<br>
* Automatic and semi-automatic creation of linked data resources
<br>
* General ontologies for open linked government data <br>
* Entity linking and co-reference detection between linked data
resources <br>
* Adding temporal qualifications to government data <br>
* Creating mash-ups with open government data <br>
* Scalable solutions for linking open government data <br>
* Linked open government data analysis <br>
* Semantic technologies for government data and applications <br>
* Representing and propagating provenance metadata <br>
* Policies for information sharing, use, and privacy <br>
* Managing usage restrictions and privacy of government data <br>
* Metadata for certainty and trust in linked open government
data <br>
* Social networks in government data <br>
* Publishing results of machine learning applied to open
government data <br>
* Visualization of open government data revealing underlying
patterns and relations <br>
<br>
Symposium structure <br>
<br>
This single track symposium will run from 9:00am Friday November
4 until 12:30pm Sunday November 6 and include a mixture of
invited talks, paper presentations, panels, system
demonstrations, a poster session, and discussions. We plan to
have several invited speakers, e.g., a US federal Government
representative addressing the current status of the US open
government initiative, a researcher discussing open challenges
and a W3C staff member describing the role of current and future
standards in government knowledge. We will also have a panel to
address the emerging issue of health informatics, the potential
nationwide health information network, where private health data
and public governmental data are interconnected. We are also
interested in running a half-day tutorial/hack-a-thon to provide
attendees hands-on experiences in creating Linked Open
Government Data and building mashups. <br>
<br>
<br>
Submissions <br>
<br>
We invite submissions of full papers (up to eight pages)
presenting research results and short papers (up to four pages)
defining a position, articulating a new problem or describing a
working system. Papers must be prepared in AAAI format and
submitted using the ogk2011 easychair site (<a
class="moz-txt-link-freetext"
href="http://www.easychair.org/conferences/?conf=ogk2011">http://www.easychair.org/conferences/?conf=ogk2011</a>).
All accepted papers will be published in a proceedings issued as
a AAAI technical report. Papers should be original material that
has not been previously published or under review for another
venue. Late breaking ideas are encouraged as the subject of a
short papers. <br>
Important dates <br>
<br>
* 3 June 2011 Submit papers using the ogk2011 site <br>
* 15 July 2011 Notifications sent to authors <br>
* 9 Sept 2011 Camera ready papers due <br>
* 16 Sept 2011 author registration deadline <br>
* 14 Oct 2011 Open pre-registration deadline <br>
* 3 Nov 2011 AI Funding seminar <br>
* 4-6 Nov 2011 Fall Symposium <br>
<br>
General symposium information <br>
<br>
General information on the 2011 AAAI Fall Symposia will be
available from the 2011 AAAI FSS Website. This includes
information about deadlines, registration, location,
transportation, and hotel accommodations. <br>
Organizers <br>
<br>
* Li Ding, Rensselaer Polytechnic Institute <br>
* Tim Finin, UMBC <br>
* Lalana Kagal, MIT <br>
* Deborah McGuinness, Rensselaer Polytechnic Institute <br>
<br>
Program committee <br>
<br>
* Hal Abelson, MIT, USA <br>
* Quan Bai, CSIRO, Australia <br>
* David Chadwick, Kent University, UK <br>
* Vinay Chaudhri, SRI, USA <br>
* Nick Gibbins, University of Southampton, UK <br>
* Karthik Gomadam, Accenture Technology Labs, USA <br>
* Stuart Graham, USPTO, USA <br>
* Alon Halevy, Google, USA <br>
* Andreas Harth, KIT, DE <br>
* Michael Hausenblas, DERI Galway, Irland <br>
* Sandro Hawke, W3C, USA <br>
* Anupam Joshi, UMBC, USA <br>
* David Karger, MIT, USA <br>
* Gary Katz, MarkLogic, USA <br>
* Qing Liu, CSIRO, Australia <br>
* Ashok Malhotra, Oracle, USA <br>
* Natasha Noy, Stanford University, USA <br>
* Theresa Pardo, SUNY Albany, USA <br>
* Vassilios Peristeras, European Commission, Belgium <br>
* Alexander Pretschner, Karlsruhe Institute of Technology,
Germany <br>
* Alan Ruttenberg, SUNY Buffalo, USA <br>
* Satya Sahoo, Case Western Reserve, USA <br>
* Abdul Shaikh, NIH/NCI, USA <br>
* Kavitha Srinivas, IBM Research, USA <br>
* Joshua Tauberer, POPVOX, USA <br>
* George Thomas, HHS, USA <br>
* Curt Tilmes, NASA Goddard, USA <br>
* Evelyne Viegas, Microsoft Research, USA <br>
* David Wood, Talis, UK <br>
* Peter Yeh, Accenture Technology Labs, USA <br>
* Harlan Yu, Princeton, USA <br>
<br>
</div>
<br>
</div>
</body>
</html>
--------------020508000900070503040401--