The CHOOSE executive board is pleased to invite you to a presentation by Karl Lieberherr
(Northeastern University) on 'SCG Court: A Crowdsourcing Platform for Driving
This event is free for all SI-CHOOSE members, even the drinks after the talk! Non-CHOOSE
members are also welcome, and are encouraged to fill out the membership application form
) before attending the meeting. If you want to
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SCG Court: A Crowdsourcing Platform for Driving Innovation
When: 2 August 2011, 17h15
Where: Institut fuer Wirtschaftsinformatik (IWI), Universitaet Bern,
Engehaldenstrasse 8, 3012 Bern, Hoersaal 001
Travel instructions: http://scg.unibe.ch/contact/maps/
A recent Communication of the ACM article on Crowdsourcing Systems (April 2011) points to
the importance of crowdsourcing platforms to simplify the development of crowdsourcing
systems. We present the Scientific Community Game Court (SCG Court) a crowdsourcing
platform (a web application) parameterized by a playground X and our experience in using
it for driving innovation in several domains. The Scientific Community Game involves
proposing and opposing claims related to a constructive domain (e.g., domains in computer
science, mathematics, engineering, etc.). Central to opposing claims is refuting claims
based on a refutation protocol. When playing the game, players make constructive claims
about the domain and oppose others’ claims. The players who are the most successful in
defending and opposing claims win the game and gain a high reputation in the community.
Adopting an SCG-centric research process has the following benefits:
1 it focuses researchers on a specific domain by defining a language for expressing claims
about that domain. Thus, reducing the amount of management effort. The numerous
contributions from the crowd of researchers are effectively combined by the game to build
a knowledge base through voting with justification.
2 it provides a structured framework for collaboration between researchers. The
researchers provide and receive frequent feedback on their claims from their peers.
Players who lose points gain knowledge to improve their game in the future. This makes
collaboration more effective.
3 it accumulates knowledge in playground X. The game produces both a knowledge base (the
social welfare coming from the game) as well as useful know-how to defend the claims in
the knowledge base. For some playgrounds, the know-how consists of a clever algorithm, if
the domain is well understood. For other playgrounds that are less understood, the
know-how is heuristic.
4 researchers are motivated towards proposing and opposing non-trivial claims in order to
gain reputation. They like to win and if they lose, they want to find out why.
5 managers get a fair comparison of the skills of their researchers through the
6 controlled teaching and learning through the game. Researchers who introduce new
knowledge entice other researchers to assimilate the same or better knowledge. Researchers
that don’t participate in this activity, lose reputation, as they would in a real
scientific community. The game is fun and adjusts to the skill levels of players.
The SCG can be played productively for: (1) developing reliable software for computational
problems, (2) evaluating potential employees, (3) developing new knowledge in the given
domain, (4) evaluating algorithmic innovations fairly, and (5) teaching software
development / problem solving techniques in a fun game environment.
More information on SCG is available from the SCG Home Page.
Karl Lieberherr started his research career in computer science as a theoretical computer
scientist, focusing on the theory of P-optimal algorithms for the generalized maximum
satisfiability problem (MAX-CSP), still an active area of research. This work has
motivated the development of a game platform for refutation-based, constructive scientific
domains, called the Scientific Community Game (SCG) also known as the Specker Challenge
Game, named after ETH Professor Emeritus Ernst Specker. He also invented, independently
and simultaneously on the other side of the Atlantic (at ETH Zurich), an early form of
non-chronological backtracking based on learned clauses (superresolution) which has become
a key feature of most state-of-the-art SAT and CSP solvers.
In the mid 1980s, he switched to his current research area: Object-Oriented and
Aspect-Oriented Software Development and focused on issues of software design and
modularity. He founded the Demeter research team, which studied the then-novel idea of
Adaptive Programming, also known as structure-shy programming and produced the Law of
Demeter ("talk only to your friends": an explicit form of coupling control) and
several systems for separating concerns in an object-oriented programming context: From
Demeter/Flavors to DemeterF. DemeterF is used in the implementation of SCG.
Dr. Lieberherr is a Professor in the College of Computer and Information Science at