TY - GEN
T1 - Knowledge encapsulation framework for collaborative social modeling
AU - Cowell, Andrew J.
AU - Gregory, Michelle L.
AU - Marshall, Eric J.
AU - McGrath, Liam
PY - 2009
Y1 - 2009
N2 - This paper describes the Knowledge Encapsulation Framework (KEF), a suite of tools to enable knowledge inputs (relevant, domain-specific facts) to modeling and simulation projects, as well as other domains that require effective collaborative workspaces for knowledge-based task. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.
AB - This paper describes the Knowledge Encapsulation Framework (KEF), a suite of tools to enable knowledge inputs (relevant, domain-specific facts) to modeling and simulation projects, as well as other domains that require effective collaborative workspaces for knowledge-based task. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.
UR - http://www.scopus.com/inward/record.url?scp=70350528590&partnerID=8YFLogxK
M3 - Contribución a la conferencia
AN - SCOPUS:70350528590
SN - 9781577354161
T3 - AAAI Spring Symposium - Technical Report
SP - 12
EP - 19
BT - Technosocial Predictive Analytics - Papers from the AAAI Spring Symposium
T2 - 2009 AAAI Spring Symposium
Y2 - 23 March 2009 through 25 March 2009
ER -