Knowledge Encapsulation Framework for Collaborative Social Modeling
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.
- Publication Date:
- OSTI Identifier:
- Report Number(s):
- DOE Contract Number:
- Resource Type:
- Resource Relation:
- Conference: AAAI Spring Symposium: Technosocial Predictive Analytics, SS-09-09:12-19
- AAAI Press, Menlo Park, CA, United States(US).
- Research Org:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
- Sponsoring Org:
- Country of Publication:
- United States
- 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; MATHEMATICAL MODELS; SOCIOLOGY; KNOWLEDGE BASE; KNOWLEDGE MANAGEMENT; COMPUTER CODES semantic wiki, semantic web, automated discovery, knowledge elicitation, knowledge inputs