BUDA 2014 - Workshop on Big Uncertain Data (BUDA)

Workshop on Big Uncertain Data (BUDA)
Held in conjunction with ACM SIGMOD/PODS 2014
Sunday, June 22, 2014
Snowbird, Utah, USA
http://www.sigmod2014.org/buda
=== Background
Modern social and technological trends result in an enormous increase
in the amount of accessible data, with a significant portion of the
resources being massive and having inherent imprecision and uncertainty.
Such data, often referred to as "Big Data," typically features
substantial social and/or business value if become amenable to computing
machinery. Towards that, Computer Science has made a significant
progress over the years. The Artificial Intelligence (AI) community has
established principled and well practiced methodologies to model,
explore, and learn realistic knowledge within imprecise and uncertain
environments. The Database (DB) community has established fundamental
concepts and machinery for the management of data, with focus on
scaling to high volumes and intensive access. Albeit the complementary
focuses, these two communities share key features and often tackle
similar challenges. But until recently, research in them has progressed
independently with limited collaboration. It is then evident that time
has come to integrate the efforts of the two towards unified concepts
and methodologies that share the benefits of both worlds.
=== Goals
This workshop aims to bring together researchers and practitioners from
the AI community and the DB community, in order to highlight relevant
state of the art research, and to capture opportunities of collaboration
and mutual enhancement. The organizers believe that research
achievements from both communities provide a significant ground to
benefit from such an assembly. Examples include AI concepts such as
Markov Logic, lifted inference, and learning/mining of relational data,
and DB concepts such as probabilistic databases, query optimization and
descriptive complexity. With the synergy between the two communities,
the hope is for this workshop to serve as a stepping stone towards the
realization of the value in Big Data.
=== Format
The workshop will be a half day workshop centered around the following
highlights:
* Invited speakers:
- Lise Getoor (UCSC)
- Dan Olteanu (Oxford)
* Invited mini-tutorial:
Guy van den Broeck (UCLA) on
statistical relational learning and lifted inference
The workshop will conclude with a number of poster spotlights and a
poster session.
=== Important Dates
Submission: March 23, 2014
Notification: April 30, 2014
Camera-Ready: May 14, 2014
Workshop: June 22, 2014
=== Submissions
Those interested in attending should submit either a technical paper
(ACM SIG style, 6 pages maximum including references) or a position,
outrageous-idea or vision paper (ACM SIG style, 2 pages maximum) in PDF
format via EasyChair:
https://www.easychair.org/conferences/?conf=buda20...
All submitted papers will be carefully peer-reviewed by multiple
reviewers.
=== Organizing Committee
* Program Co-Chairs:
- Kristian Kersting (Technical University of Dortmund)
- Benny Kimelfeld (LogicBlox)
* Program Committee:
- Serge Abiteboul (INRIA-Saclay)
- Foto Afrati (National Technical University of Athens)
- Bogdan Cautis (University of Paris-Sud)
- Sara Cohen (The Hebrew University)
- James Cussens (University of York)
- Jesse Davis (KU Leuven)
- Luc De Raedt (Katholieke Universiteit Leuven)
- Amol Deshpande (University of Maryland at College Park)
- Daniel Deutch (Tel Aviv University)
- Vibhav Gogate (The University of Texas at Dallas)
- Fabian Hadiji
- Christopher Jermaine (Rice University)
- Kristian Kersting (Technical University of Dortmund, Fraunhofer IAIS)
- Roni Khardon (Tufts University)
- Benny Kimelfeld (LogicBlox)
- Daniel Lowd (University of Oregon)
- Martin Mladenov (Technical University of Dortmund, Fraunhofer IAIS)
- Mathias Niepert (University of Washington)
- Dan Olteanu (Oxford)
- Hoifung Poon (Microsoft Research)
- Christopher Ré (Stanford University)
- Oliver Schulte (Simon Fraser University)
- Pierre Senellart (Institut Mines?Télécom; Télécom ParisTech; CNRS LTCI)
- Dan Suciu (University of Washington)
- Guy Van Den Broeck (UCLA)
- Maurice Van Keulen (University of Twente)