Understanding and governing data ecosystems using a social architecture approach: a CSIRO research infrastructure case study

Paul Box1, Cynthia Love2, Jonathan Yu3

1CSIRO Land and Water, Sydney Australia, paul.j.box@csiro.au

2CSIRO Information Services, Melbourne Australia, cynthia.love@csiro.au

3CSIRO Land and Water, Melbourne, Australia, Jonathan.yu@csiro.au


Today, efforts to change how we work, requires the navigation of and negotiating change in, complex social, institutional and technical environments. Knowledge workers and especially those in data intensive environments such as science, directly use and are enabled by numerous information systems. Collectively, these information and technology resources (data, information systems, and technologies), together with social and institutional contexts in which they are embedded, (work routines, standards, culture, relationships, governance and norms) comprise information infrastructure (or data ecosystem).

Successful introduction into an existing installed base of systems, practices, and institutions, of new systems or approaches to improve the way we manage and use data, requires an understanding of data ecosystem. This includes and understanding of the system(s) which it replaces or interacts with; how users interact with these existing systems, and why; and the design of institutions (such as incentives, policies, standards and governance) that shape how users will interact with the new system. An inter-disciplinary approach to designing environments that are conducive to change, called ‘social architecture’,  will be presented in this paper.

Current approaches

Tradition systems development approaches take a technical perspective and apply limited social and institutional analysis to system design, typically undertaking rudimentary stakeholder analysis to identify uses cases and requirements, and putting in place ‘boilerplate’ change management, communication and governance mechanisms. This may be sufficient for smaller largely standalone systems. However, in many cases the systems we are trying to change are much more interconnected and complex and therefore require different approaches.

Although ‘users’ are brought increasingly into the systems design processes through user centered design (UCD) approaches, these tend to focus on the end users that interact with the systems and the ‘experience’ of using the system. UCD approaches have raised the profile and provide useful tool for exploring, understanding and designing information systems with cognizance of the social and institutional context within which they operate. However these approaches tend to be rather ad hoc, and limited in scope, often neglecting to engage with and understand users’ attitudes and practices as well as the institutional context that needs to be factored into the design process.

When attempting to implement larger, more complex, interconnected systems, the primary challenge lies in working with a wide range of stakeholders to influence behaviours and enable collective action across organisational boundaries. This requires a much deeper understanding of institutional arrangements, attitudes and behaviours and the often invisible hand of data economics – the costs, value generation and benefit flows inherent in data supply chains and data platforms.


Social architecture[1] is multi-disciplinary approach to the analysis, design and implementation of complex socio-technical systems. It takes a data ecosystem (information infrastructure) perspective viewing (social and technical) systems as being interconnected in networks. It draws on a range of inter-related disciplines organised in three inter-related themes of work:

  • Social – attitudes, behaviours and practices together with the social structures and mechanism through which people formally and informally collaborate, influence each other and affect change;
  • Institutions – the rules of the road (legislation, regulation, policy, standards and licensing) and how they are created (authority structures, roles and responsibilities and decision rights);
  • Economics – the costs, value generation, benefit flows in data ecosystems , together with an understanding of data market mechanisms

Using these three lens, the aim is to explore and understand current system dynamics and design a future state together with a plan for incremental change to achieve it. A critical element of the approach is the ability to measure progress and change in behavior and attitudes necessary to secure sustainable long term outcomes.

CSIRO Data governance program

Within CSIRO, a number of efforts are underway to improve the management and re-use of data at enterprise levels and within individual business units. There is a recognition of the federated nature of the CSIRO operating model and the need for solutions that meet the differing science business needs in various parts of the organization.

The CSRO data governance program aims to develop an integrated interoperable data ecosystem with established accountability for data at all levels, a default assumption of openness, whist ensuring that licensing, ethical and contractual obligations are honoured and supported by data management and data governance tools and infrastructure. The project is being led by CSIRO Information Management & Technology in partnership with CSIRO business units and other corporate functions.

In parallel, to this enterprise wide activity, within the CSIRO Land and Water business unit a Digital Asset Management improvement program (DAMbusters) is underway which aims to support improved data management and reuse practices through a range of technical and institutional interventions.

To maximize the value of CSIRO data assets through a range of interventions at CSIRO enterprise-wide and business unit scale, there is a need to understand prevailing attitudes and practices of a range of stakeholders within the organisation and the complex external (legislative, policy, economic, legal) and internal organisational (policy, contractual and IP) environment within which they work. All of these factors shape the systems and practices that we currently use and constrain and inform our ability to change.

A social architecture approach is being used to inform how both the enterprise wide and DAMbusters projects tackle what is a complex multi-dimensions challenge.

This paper will briefly describe the theoretical underpinnings of social architecture focusing on the value, practices and institutional aspects of data. It will describe how social architecture is being used in practice to inform CSIRO efforts at enterprise and business unit level, to understand the current installed base of practices, technology and institutions as well as to design a comprehensive and instrumented change program to guide and monitor the CSIRO data ecosystem improvement. The paper will conclude by offering some lessons learned and pointers for others engaged in similar data oriented improvement programs.


  1. Box, P. and Lemon, D. (2016). Social architecture – cultivating conditions for data sharing. SciDataCon2016, Denver Collorado USA. http://www.scidatacon.org/2016/sessions/37/paper/139/


Paul works in the Environmental Informatics Group in CSIRO Land and Water, building and leading a program of research into the social, institutional and economic aspects large scale distributed information platforms for government. The  ‘social architecture’ practice that he is currently developing, brings together social science, economics and institutional analysis to guide and inform the development of information infrastructures (or systems of systems) that underpin effective policy and decision making.

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