GATHERING KNOWLEDGE FROM SOCIAL KNOWLEDGE MANAGEMENT ENVIRONMENTS - PowerPoint PPT Presentation

GATHERING KNOWLEDGE FROM SOCIAL KNOWLEDGE MANAGEMENT ENVIRONMENTS Validation of an Anticipatory Standard René Peinl, Lars Hetmank, Markus Bick, Stefan Thalmann, Paul Kruse, Jan M. Pawlowski, Ronald Maier, Isabella Seeber

2 Gathering Knowledge from Social Knowledge Management Environments Current Team

3 Gathering Knowledge from Social Knowledge Management Environments Situation • Enhanced intensity of knowledge along the entire value chain concerning processes, products and services • Specialization of organizations regarding their core competencies [Gran96]; [RoFi97]; [Svei98] • Customer innovation, co-creation, open innovation • Shorter time-to-market as well as time- on-market [Gahl91]; [Stau92]; [Sydo92]; [Bron93]; [Font96] à Necessity for cooperative work

4 Gathering Knowledge from Social Knowledge Management Environments Knowledge Transfer Challenge Knowledge intensive Cooperation V.1 V.1 V.2 V.2 Linked Linked V.3 V.3 <creator>Muster</creator> <creator>Muster</creator> <date>11-01-2006</date> <date>11-01-2006</date> Metadata Metadata Document Document storage storage storage Storage Enterprise Knowledge Enterprise Knowledge Infrastructure A Infrastructure B 1 1 2 transfer User User User User desktop A1 desktop An desktop B1 desktop Bn Partner A Partner B Static, linear knowledge elements with Static, linear knowladge elements without

5 Gathering Knowledge from Social Knowledge Management Environments Motivation • foster knowledge exchange between social environments Knowledge Worker • increase the Perspective understandability of Knowledge knowledge objects through Activity Stream enriched contextual information Knowledge • support integration between Trace Knowledge Knowledge Knowledge Knowledge Activity diverse social software tools Bundle Process Perspective Perspective Object and knowledge management systems • better representation of social aspects of knowledge work Peinl, R., Thalmann, S., Hetmank, L., Kruse, P., Seeber, I., Pawlowski, J.M., Bick, M., Maier, R., Schoop, E.: Manifesto for a Standard on Knowledge Exchange in Social Knowledge Management Environments. 13th European Conference on Knowledge Management (ECKM) Cartagena (2012).

6 Gathering Knowledge from Social Knowledge Management Environments Concepts New Concepts Description Knowledge Activity (KA) Goal directed actions within a user's context Knowledge Activity Stream Time-ordered list of knowledge activities (user-centric (KAS) perspective) Knowledge Trace (KT) Codified representation of a user's action that captures contextual information Contextual Information Information, e.g. time, place, actions performed on knowledge objects as well as related people and their skills Knowledge Object (KO) Codified knowledge of externalized knowledge (e.g. paragraphs, tables, figures, mind maps) Knowledge Bundle (KB) Collection of knowledge traces that are affiliated to a knowledge object (object-centric perspective) Knowledge Container (KC) A set of knowledge objects and their corresponding knowledge bundles Bick, M., Hetmank, L., Kruse, P., Maier, R., Pawlowski, J.M., Peinl, R., Schoop, E., Seeber, I., Thalmann, S.: Manifesto for a Standard on Meaningful Representations of Knowledge in Social Knowledge Management Environments. Multikonferenz Wirtschaftsinformatik (MKWI). Braunschweig (2012).

7 Gathering Knowledge from Social Knowledge Management Environments Proposed KM Ontology hasGenerator license system rights knowledge topic dateAdded bundle hasProvider technical requirements hasGenerator rights knowledge keyword contributor readTimes activity stream title knowledge consistsOf consistsOf object target knowledge creator trace actor updated person hasLocation published organization latitude dtStart location partOf longitude worksFor subClassOf dtEnd alumniOf affiliated homeLocation city workLocation hasAction duration knowledge state worker name hasSkill skill activityState knows actor verb description memberOf colleague knowledge action partOf isBossOf activity community dependsOn Thalmann, S., Peinl, R., Hetmank, L., Kruse, P., Seeber, I., Maier, R., Pawlowski, J.M., Bick, M.: Manifesto for an Ontology-based Standard on Knowledge Exchange in Social Knowledge Management Environments. 12th International Conference on Knowledge Management and Knowledge Technologies (iKNOW). Graz (2012).

8 Gathering Knowledge from Social Knowledge Management Environments Architectural View of the KC* ZIP container manifest.rdf table of files together with file content types existing meta data in xml format meta.xml meta.owl new, additional meta data in OWL format content.xml contents, depending on type (odt, odp, …) styles.xml styles and formatting * based on OpenDocument file formats

9 Gathering Knowledge from Social Knowledge Management Environments Technical Implementation • Builds on existing standards, such as FOAF, schema.org , microformats, activitystrea.ms , LOM, SCORM, IMS LD, DC, MARC-21, TV-Anytime, MPEG7, UICO, TMO, UTO, ATOM, CAM, DITA, SIOC, Proton, HR XML, WS BPEL • activitystrea.ms standard served as a role model (actor, object, target) • Mapped own classes to elements of existing standards using the OWL equivalentClass concept • Instances conform to RDF/XML and references an OWL ontology • 18 classes, 30 object properties, and 15 data properties

10 Gathering Knowledge from Social Knowledge Management Environments OWL Ontology in Protége !

11 Gathering Knowledge from Social Knowledge Management Environments Initial Validation • Used assessment perspectives of the reference model analysis grid (RMAG) • suitability, conceptual support, tools, development and maintenance of further models and standards, business and management, dependence, openness, expressive power, completeness, technical interoperability, understandability, coherence and non-redundancy • Ontology characteristics: • Attribute richness AR=0.83 • Relationship richness IR=0.88

12 Gathering Knowledge from Social Knowledge Management Environments Scenario-based Evaluation Detailed scenarios are constructed to demonstrate the utility of the ontology as a first proof-of concept • Scenario 1 : illustrates the activity of finding new product ideas • Scenario 2 : illustrates the activity of developing a research idea collaboratively to achieve a common goal • Scenario 3 : illustrates the activity of creating a software specification and project proposal based on a requirement document

13 Gathering Knowledge from Social Knowledge Management Environments Lessons Learned #1 Aspects Lessons Learned Versioning RDF does not adequately support version control of different knowledge containers. Heterogeneous Identifiers other than URI have to be stored in a separate identifiers variable or aligned to the URN scheme. Human readability Human readability of the knowledge container may be restricted under the use of RDF. Integration of The integration of the various standards in a unified KM existing standards standard is challenging as their underlying schemes (XML Schema, RDF Schema, OWL, HTMLmicrodata) differ significantly. Filter mechanisms Filter mechanisms are required to address the specific needs of the knowledge worker.

14 Gathering Knowledge from Social Knowledge Management Environments Lessons Learned #2 Aspects Lessons Learned Aggregation Different levels of KT aggregations are needed to overcome information overload. Assigning KT to KO Not all KT may be automatically assigned to its corresponding KO. KM Current standards do not adequately focus on specific appropriateness aspects of KM. Handling of nested Future software applications have to consider the KT of KO referenced, linked and nested KOs sufficiently. Modeling of RDF OWL enforces flat structures, whereas XML and RDF containers in OWL allow encapsulating similar elements in a container.

15 Gathering Knowledge from Social Knowledge Management Environments Conclusion and Next Steps • our lessons learned show several deficits that should be addressed in future versions of the ontology • start a standardization process towards a broad consensus that takes relevant stakeholders into account • increase the semantics of our ontology by introducing a common shared set of object and action types represented as OWL individuals • further evaluation and refinement of the ontology through expert interviews, use cases, and prototype development

16 Gathering Knowledge from Social Knowledge Management Environments Contact Paul Kruse René Peinl rene.peinl@hof-university.de paul.kruse@tu-dresden.de Lars Hetmank Jan M. Pawlowski lars.hetmank@tu- jan.pawlowski@jyu.fi dresden.de Ronald Maier Markus Bick ronald.maier@uibk.ac.at mbick@escpeurope.eu Isabella Seeber Stefan Thalmann stefan.thalmann@uibk.ac.at isabella.seeber@uibk.ac.at