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Integration of Knowledge and Task Management in an Evolving, Communication-intensive Environment

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

Digitalisation of knowledge work, especially in communicationintensive domains is one of the greatest challenges, but also one of the greatest opportunities to improve today’s working environments. This demands for a flexible system that supports both knowledge intensive creative work and highly individual processes. Smooth integration is hindered by the lack of the task context in knowledge management systems so far. Furthermore, a model to define and handle mental concepts, which are typically evolving during daily work, is missing, to allow for targeted use of appropriate knowledge in process tasks. In this paper, we propose a bottomup approach to model and store the static and dynamic aspects of knowledge in terms of data objects and tasks that are connected with each other. The proposed solution leverages the flexibility of a graph-based model to enable open and continuously evolving user-centred processes for knowledge work, but also predefined administrative processes. Besides our approach, we show results from testing a prototypical implementation in a real-life setting in the domain of intellectual property management applications.
OriginalspracheEnglisch
TitelProceedings of iiWAS 2020
Herausgeber*innenMaria Indrawan-Santiago, Eric Pardede, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Kotsis
ErscheinungsortNew York
VerlagACM
Seiten407-416
Seitenumfang10
ISBN (elektronisch)9781450389228
ISBN (Print)978-1-4503-8924-2
DOIs
PublikationsstatusVeröffentlicht - 30 Nov. 2020

Publikationsreihe

NameACM International Conference Proceeding Series

Wissenschaftszweige

  • 202007 Computer Integrated Manufacturing (CIM)
  • 102001 Artificial Intelligence
  • 102006 Computer Supported Cooperative Work (CSCW)
  • 102010 Datenbanksysteme
  • 102014 Informationsdesign
  • 102015 Informationssysteme
  • 102016 IT-Sicherheit
  • 102019 Machine Learning
  • 102022 Softwareentwicklung
  • 102025 Verteilte Systeme
  • 102028 Knowledge Engineering
  • 102033 Data Mining
  • 102035 Data Science
  • 502007 E-Commerce
  • 505002 Datenschutz
  • 506002 E-Government
  • 509018 Wissensmanagement

JKU-Schwerpunkte

  • Digital Transformation
  • KnoP-2D

    Auer, D. (Forscher*in), Mohamed, A. (Forscher*in) & Küng, J. (Projektleiter*in)

    01.03.201928.02.2022

    Projekt: Geförderte ForschungFFG - Österreichische Forschungsförderungsgesellschaft

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