Complex Adaptive Digital Ecosystems

Gerard Briscoe

doi:10.1145/1936254.1936262

Complex Adaptive Digital Ecosystems

Gerard Briscoe

School of Mathematical & Computer Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

56 Citations (Scopus)

Abstract

We investigate an abstract conceptualisation of Digital Ecosystems from a computer science perspective. We then provide a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive Systems (CAS) modelling. A framework to assist the cross-disciplinary collaboration of research into Digital Ecosystems, including Digital Business Ecosystems (DBEs) and Digital Knowledge Ecosystems (DKEs). So, we have defined the key steps towards a theoretical framework for Digital Ecosystems, that is compatible with the diverse theoretical views prevalent. Therefore, a theoretical edifice that can unify the diverse efforts within Digital Ecosystems research. Copyright 2010 ACM.

Original language	English
Title of host publication	Proceedings of the International Conference on Management of Emergent Digital EcoSystems, MEDES'10
Pages	39-46
Number of pages	8
DOIs	https://doi.org/10.1145/1936254.1936262
Publication status	Published - 2010
Event	International Conference on Management of Emergent Digital EcoSystems, MEDES'10 - Bangkok, Thailand Duration: 26 Oct 2010 → 29 Oct 2010

Conference

Conference	International Conference on Management of Emergent Digital EcoSystems, MEDES'10
Country/Territory	Thailand
City	Bangkok
Period	26/10/10 → 29/10/10

Keywords

Business ecosystems
Complex Adaptive Systemss
Knowledge ecosystems
Multi-agent systems

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10.1145/1936254.1936262

Cite this

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title = "Complex Adaptive Digital Ecosystems",

abstract = "We investigate an abstract conceptualisation of Digital Ecosystems from a computer science perspective. We then provide a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive Systems (CAS) modelling. A framework to assist the cross-disciplinary collaboration of research into Digital Ecosystems, including Digital Business Ecosystems (DBEs) and Digital Knowledge Ecosystems (DKEs). So, we have defined the key steps towards a theoretical framework for Digital Ecosystems, that is compatible with the diverse theoretical views prevalent. Therefore, a theoretical edifice that can unify the diverse efforts within Digital Ecosystems research. Copyright 2010 ACM.",

keywords = "Business ecosystems, Complex Adaptive Systemss, Knowledge ecosystems, Multi-agent systems",

author = "Gerard Briscoe",

year = "2010",

doi = "10.1145/1936254.1936262",

language = "English",

isbn = "9781450300476",

pages = "39--46",

booktitle = "Proceedings of the International Conference on Management of Emergent Digital EcoSystems, MEDES'10",

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T1 - Complex Adaptive Digital Ecosystems

AU - Briscoe, Gerard

PY - 2010

Y1 - 2010

N2 - We investigate an abstract conceptualisation of Digital Ecosystems from a computer science perspective. We then provide a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive Systems (CAS) modelling. A framework to assist the cross-disciplinary collaboration of research into Digital Ecosystems, including Digital Business Ecosystems (DBEs) and Digital Knowledge Ecosystems (DKEs). So, we have defined the key steps towards a theoretical framework for Digital Ecosystems, that is compatible with the diverse theoretical views prevalent. Therefore, a theoretical edifice that can unify the diverse efforts within Digital Ecosystems research. Copyright 2010 ACM.

AB - We investigate an abstract conceptualisation of Digital Ecosystems from a computer science perspective. We then provide a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive Systems (CAS) modelling. A framework to assist the cross-disciplinary collaboration of research into Digital Ecosystems, including Digital Business Ecosystems (DBEs) and Digital Knowledge Ecosystems (DKEs). So, we have defined the key steps towards a theoretical framework for Digital Ecosystems, that is compatible with the diverse theoretical views prevalent. Therefore, a theoretical edifice that can unify the diverse efforts within Digital Ecosystems research. Copyright 2010 ACM.

KW - Business ecosystems

KW - Complex Adaptive Systemss

KW - Knowledge ecosystems

KW - Multi-agent systems

UR - https://www.scopus.com/pages/publications/79952369459

U2 - 10.1145/1936254.1936262

DO - 10.1145/1936254.1936262

M3 - Conference contribution

SN - 9781450300476

SP - 39

EP - 46

BT - Proceedings of the International Conference on Management of Emergent Digital EcoSystems, MEDES'10

T2 - International Conference on Management of Emergent Digital EcoSystems, MEDES'10

Y2 - 26 October 2010 through 29 October 2010

ER -

Complex Adaptive Digital Ecosystems

Abstract

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Keywords

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