TY - GEN
T1 - Discovering emergent virtual work processes in collaborative systems
AU - Simoff, Simeon J.
AU - Biuk-Aghai, Robert P.
PY - 2002
Y1 - 2002
N2 - The design of virtual workplaces that can support virtual work processes has traditionally been either ad-hoc, or has been influenced by the top-down approaches, such as 'virtual architecture' and requirements identification and analysis. There are several problems with the top-down approaches. We still lack knowledge about how people collaborate in distributed computer-mediated information environments, hence, the requirements in the top-down approach are usually derived from the expectation of how the business process will run in a face-to-face environment. Another problem with existing groupware support for such environments is the difficulty in obtaining, and subsequently retaining and reusing, ready-made configurations of collaborative work processes. Such configurations naturally occur during the actual use of collaborative system when conducting projects. These configurations reflect the actual dynamics of the process, adapting the environment to support emerging work processes. Can we learn more about the actual collaboration in a virtual environment (rather than the one derived from the face-to-face expectations)? Can we reuse this knowledge for better support of computer-mediated collaborative projects? Can we predict some elements of the evolution of a new collaborative process, based on similarities and analogies with processes formalised and supported before? Can we predict possible emergent processes and cater for them? Can we capture and utilise the evolutionary component in the workspace design process, so that we can provide better support to the developers of collaborative workspaces? The paper presents the latest developments of a new approach for supporting the design and redesign of collaborative virtual workplaces, based on combining data mining techniques for refining lower level models with a reverse engineering cycle to create upper level models. The methodology utilises an apriori knowledge about the data models in the systems and a visual language for formal process representation.
AB - The design of virtual workplaces that can support virtual work processes has traditionally been either ad-hoc, or has been influenced by the top-down approaches, such as 'virtual architecture' and requirements identification and analysis. There are several problems with the top-down approaches. We still lack knowledge about how people collaborate in distributed computer-mediated information environments, hence, the requirements in the top-down approach are usually derived from the expectation of how the business process will run in a face-to-face environment. Another problem with existing groupware support for such environments is the difficulty in obtaining, and subsequently retaining and reusing, ready-made configurations of collaborative work processes. Such configurations naturally occur during the actual use of collaborative system when conducting projects. These configurations reflect the actual dynamics of the process, adapting the environment to support emerging work processes. Can we learn more about the actual collaboration in a virtual environment (rather than the one derived from the face-to-face expectations)? Can we reuse this knowledge for better support of computer-mediated collaborative projects? Can we predict some elements of the evolution of a new collaborative process, based on similarities and analogies with processes formalised and supported before? Can we predict possible emergent processes and cater for them? Can we capture and utilise the evolutionary component in the workspace design process, so that we can provide better support to the developers of collaborative workspaces? The paper presents the latest developments of a new approach for supporting the design and redesign of collaborative virtual workplaces, based on combining data mining techniques for refining lower level models with a reverse engineering cycle to create upper level models. The methodology utilises an apriori knowledge about the data models in the systems and a visual language for formal process representation.
UR - http://www.scopus.com/inward/record.url?scp=84867289771&partnerID=8YFLogxK
U2 - 10.1007/3-540-36124-3_17
DO - 10.1007/3-540-36124-3_17
M3 - Conference Paper
AN - SCOPUS:84867289771
SN - 3540001069
SN - 9783540001065
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 286
EP - 303
BT - On the Move to Meaningful Internet Systems 2002
A2 - Meersman, Robert
A2 - Tari, Zahir
PB - Springer Verlag
T2 - 10th Int. Conference on Cooperative Information Systems, CoopIS 2002, Jointly with the 4th Int. Symp. on, DOA 2002 and the 1st Int. Conf. on Ontologies, Databases, and Applications of Semantics for Large-Scale Information Systems, ODBASE 2002
Y2 - 30 October 2002 through 1 November 2002
ER -