Data Infrastructures for Asset Management Viewed as Complex Adaptive Systems

Data infrastructures represent information about physical reality. As reality changes, data infrastructures might also be subject to change. Researchers have increasingly approached physical infrastructures as being complex adaptive systems (CAS). Although physical infrastructures are often approached as CAS, the underlying data infrastructures hardly are. Studying data infrastructures as CAS has significant implications for our understanding of them. A CAS lens will help us to identify and better understand their key elements and coordination mechanisms for their functioning and dealing with change. Accepting data infrastructures as CASs also means we need to understand the consequences for their development. On the basis of state of the art literature, and an explorative case study of Rijkswaterstaat in the Netherlands, an overview of known data infrastructural elements and the coordination mechanisms connecting them will be presented. The results show that successful development of data infrastructures requires consideration of a wide variety of elements that can be coordinated using various coordination mechanisms. We conclude that a more complete picture of what data infrastructures are and how they can be coordinated is needed.

[1]  Stuart E. Madnick,et al.  Special Section: Assuring Information Quality , 2004, J. Manag. Inf. Syst..

[2]  Kevin Crowston,et al.  A Coordination Theory Approach to Organizational Process Design , 1997 .

[3]  Wanda J. Orlikowski,et al.  Studying Information Technology in Organizations: Research Approaches and Assumptions , 1991, Inf. Syst. Res..

[4]  Douglas Nebert,et al.  Developing Spatial Data Infrastructures: The SDI Cookbook , 2001 .

[5]  W. H. Erik de Man Understanding SDI; complexity and institutionalization , 2006, Int. J. Geogr. Inf. Sci..

[6]  M.F.W.H.A. Janssen Designing electronic intermediaries: An agent-based approach for designing interorganizational coordination mechanisms , 2001 .

[7]  Cui Tao,et al.  Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: The SHARPn project , 2012, J. Biomed. Informatics.

[8]  Richard Y. Wang,et al.  Manage Your Information as a Product , 1998 .

[9]  Ying Su,et al.  Assuring information quality in e-Science , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[10]  Carol V. Brown,et al.  Designing data governance , 2010, CACM.

[11]  Henry Mintzberg,et al.  Structure in Fives: Designing Effective Organizations , 1983 .

[12]  Elinor Ostrom,et al.  A Framework to Analyze the Robustness of Social-ecological Systems from an Institutional Perspective , 2004 .

[13]  Andy Koronios,et al.  A Data Quality Model for Asset Management in Engineering Organisations , 2005, ICIQ.

[14]  Arnold Bregt,et al.  Spatial data infrastructures as complex adaptive systems , 2010, Int. J. Geogr. Inf. Sci..

[15]  Ian Brown,et al.  Providing an effective data infrastructure for the simulation of complex materials , 2006 .

[16]  Sharon S. Dawes,et al.  Stewardship and usefulness: Policy principles for information-based transparency , 2010, Gov. Inf. Q..

[17]  R. Yin Case Study Research: Design and Methods , 1984 .

[18]  P. Cilliers,et al.  Complexity and post-modernism: understanding complex systems , 1999 .

[19]  A. Rajabifard,et al.  Future directions for SDI development , 2002 .

[20]  Rob Procter,et al.  The Development of Data Infrastructures for eHealth: A Socio-Technical Perspective , 2009, J. Assoc. Inf. Syst..

[21]  Kalle Lyytinen,et al.  Theorizing about the Design of Information Infrastructures: Design Kernel Theories and Principles , 2008 .

[22]  Andy Koronios,et al.  Developing a data quality framework for asset management in engineering organisations , 2007, Int. J. Inf. Qual..

[23]  Paul Cilliers,et al.  Understanding Complex Systems , 2013 .

[24]  Derk Loorbach,et al.  Complexity and Transition Management , 2009 .

[25]  Nicholas R. Jennings,et al.  Coordination in software agent systems , 1996 .

[26]  Boris Otto,et al.  A Contingency Approach To Data Governance , 2007, ICIQ.

[27]  Daniela L. Nastasie,et al.  Integration Through Standards – An Overview of Internal Information Standards for Engineering Asset , 2010 .

[28]  Sue Holwell,et al.  Information, Systems and Information Systems: Making Sense of the Field , 1998 .

[29]  Paulien M. Herder,et al.  Designing infrastructures using a complex systems perspective , 2008 .

[30]  Kevin Crowston,et al.  What is coordination theory and how can it help design cooperative work systems? , 1990, CSCW '90.

[31]  P. Herder,et al.  Buying real options – Valuing uncertainty in infrastructure planning , 2011 .

[32]  James J. Thomas,et al.  Information visualization: data infrastructure architectures , 1994, Seventh International Working Conference on Scientific and Statistical Database Management.

[33]  Soon Ae Chun,et al.  Building the next generation of digital government infrastructures , 2009, Gov. Inf. Q..

[34]  M. Marcelli,et al.  Design and Methods , 2011 .

[35]  Diane M. Strong,et al.  Data quality in context , 1997, CACM.

[36]  H. Aalders,et al.  Spatial Data Infrastructure , 2001 .

[37]  Lin Ma,et al.  A conceptual data modelling methodology for asset management data warehousing , 2008, WCE 2009.

[38]  William J. Kettinger,et al.  The infological equation extended: towards conceptual clarity in the relationship between data, information and knowledge , 2010, Eur. J. Inf. Syst..