Tagging for Process Models in Knowledge Management
Transcript
Semantic Integration of Process Models into Knowledge Management: A Social Tagging Approach Michael Prilla Information and Technology Management (IMTM) Institute für Applied Work Science (IAW) Ruhr University of Bochum IMTM – An interdisciplinary Team: Applied Work Science, Communication Science, Computer Science , Engineering Science, Pedagogy, Sociology, Social Science Focus areas: Process Modeling Knowledge Management Innovation and Creativity Initial Situation
- Process Models are useful...
- Essential tools in business and science
- Encoding of organizational knowledge
- ...but neglected in Knowledge Management
- KM dominated by textual content
- Limited access to available (PM) knowledge
- Lacking relations to other content
- Available support by isolated applications
- Observations
- Scarce usage in Organizations
- Lacking support for Work with Process Models (Knowledge Work)
- Solution: Integration into KM
- Promoting PMs as valuable information sources
- Supporting model related tasks
- Approach
- Social Tagging and Integration into Work Tasks
- Work In Progress
- Overcoming Complexity Gap: Semantic Description
- Low usage burden (high ceiling)
- Motivation for participation
- Integration of Stakeholders (KWs)
- Give everybody a voice
- Improve knowledge acquisition and distribution
- Integration into Work Tasks
- Linear and coherent structure
- Overview difficult (on first sight)
- Understanding needs subjection
- Ramifications and sub-procedures
- Quick overview (scanning)
- Understanding needs context
- Semantics to level out the Gap between heterogeneous content
- Analysis of available Technology
- Conclusion: (Starting from) Tagging suitable for task at hand
- Limited support limited content distribution and access
- Support for Knowledge Workers
- Freedom of choice for Tools
- Personal Information Management
- Implications
- Integrate support into available tools
- Embed group-related tasks into individual work
- Intertwine models and KM content
- Supporting functions:
- Sharing from modeling applications
- Intertwining of textual and model content
- KM support for modeling task
- Prototype
- Kolumbus 2 KM application
- SeeMe modeling editor
- Integration of Process Models into KM content
- Bottom-Up, Social Tagging
- Tight integration into Knowledge Work
- Remaining Work
- Continuation of Empirical Grounding
- Refinement of Prototypes
- Improvement of Tagging support (Clustering, …)
- Evaluation
- Integration of other Applications
- Support exchange:
- Integrate in KM content
- Contextualize
- Include corresponding information
- Support usage:
- Make use of encoded knowledge
- Reach relevant actors
- Support enrichment:
- Expatiate actors’ perspectives
- Add context
- Link content
- Support modelling:
- Show contextualized information
- Offer similar models
- Enable tagging support for applications
- Tags provide (semantic) glue for content linkage
- Prototype: SeeMe Model Editor and Kolumbus 2
- Receive content while modelling
- Tag based queries
- Stream content
- Share models from modelling application
- Basis: Tags
- XML exchange
- Include linked content
- Control by a few
- Anticipation of categorization
- Unidirectional information exchange
- Slowly changing
- Useful in slowly changing, precise information structures and vocabularies
- Control by all Users („Prosumers“)
- Emergence of categorization
- Bidirectional information exchange
- Flexibility
- Useful in quickly adapting, multi-perspective and fuzzy information structures
- Choice of semantic support depends on
- Task to be supported and overall goal
- Organizational culture (hierarchies, …)
- Present vocabulary
- People working with it