TY - GEN

T1 - EcoKnow

T2 - 22nd IEEE International Enterprise Distributed Object Computing Conference Workshops, EDOCW 2018

AU - Hildebrandt, Thomas Troels

PY - 2018/11/14

Y1 - 2018/11/14

N2 - The publication and implementation of national digitalisation strategies since 2002 has provided a solid foundation for the digitalisation of public and private services in Denmark, including nation wide solutions for digital identity, secure communication and access to public data. However, there is an unmet need for technology and methods for effective, user-centric, locally anchored and adaptable digitalisation of processes that ensures high quality and exploits the large amount of available public data, while remaining compliant with frequently changing legal regulations, including the cross-cutting EU General Data Protection Regulation. The Effective, Co-created & Compliant Adaptive Case Management for Knowledge Workers (EcoKnow.org) research project supported by Innovation Fund Denmark from 2017 to 2021 addresses these challenges. EcoKnow will focus on case management processes in local government, in particular processes involving services and benefits offered to young persons with special needs and unemployed citizens. These processes are characterised by having deep consequences for the lives of citizens, having high and unpredictable costs and being subject to complex, changing legal regulations. The basic hypothesis is that the challenges can be overcome by combining adaptive case management technologies based on declarative DCR Graph process notation with machine learning, informed by ethnographical studies of case work in practice and multi-modal empirical studies of the modelling of regulations by end-users.

AB - The publication and implementation of national digitalisation strategies since 2002 has provided a solid foundation for the digitalisation of public and private services in Denmark, including nation wide solutions for digital identity, secure communication and access to public data. However, there is an unmet need for technology and methods for effective, user-centric, locally anchored and adaptable digitalisation of processes that ensures high quality and exploits the large amount of available public data, while remaining compliant with frequently changing legal regulations, including the cross-cutting EU General Data Protection Regulation. The Effective, Co-created & Compliant Adaptive Case Management for Knowledge Workers (EcoKnow.org) research project supported by Innovation Fund Denmark from 2017 to 2021 addresses these challenges. EcoKnow will focus on case management processes in local government, in particular processes involving services and benefits offered to young persons with special needs and unemployed citizens. These processes are characterised by having deep consequences for the lives of citizens, having high and unpredictable costs and being subject to complex, changing legal regulations. The basic hypothesis is that the challenges can be overcome by combining adaptive case management technologies based on declarative DCR Graph process notation with machine learning, informed by ethnographical studies of case work in practice and multi-modal empirical studies of the modelling of regulations by end-users.

KW - Adaptive Case Management

KW - Co-creation

KW - Decision Support

KW - Declarative

KW - Machine Learning

UR - http://www.scopus.com/inward/record.url?scp=85058962967&partnerID=8YFLogxK

U2 - 10.1109/EDOCW.2018.00012

DO - 10.1109/EDOCW.2018.00012

M3 - Article in proceedings

AN - SCOPUS:85058962967

SP - 9

EP - 11

BT - Proceedings - 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference Workshops, EDOCW 2018

PB - IEEE

Y2 - 16 October 2018 through 19 October 2018

ER -