I have been busy working on a statement that captures the essence of policy informatics. Here is my first-cut at the definition. I thank all those who have already provided comments on this version, especially Dr. Erik Johnston (Co-Director of the Center for Public Informatics at Arizona State University). Please do send me your comments, both positive and negative, and suggestions for improvement. Thanks.
Solving complex public policy problems, dilemmas, and challenges requires deliberate, and sophisticated, information analysis.
Policymakers often are faced with conflicting solutions to complex problems, thus making it necessary for them to test out their assumptions, interventions, and resolutions. Towards this end, it becomes critical for a policymaker to have an information-rich, interactive environment in which complex problems can be modeled, simulated, visualized, and studied.
Relevant information can range from being too abundant to hardly existent. In the former case, we face the challenge of leveraging large quantities of information under severe time and resource constraints. In the latter case, limited or incomplete information has to be used to make decisions on ambiguous solution spaces.
In deliberating, designing, and implementing policies, the policy makers and the public face a number of transactional and collaborative inefficiencies. Some of these inefficiencies arise from the simple reality that information held by both parties is difficult to articulate and even transfer, i.e. information is sticky. This makes it difficult for either party to collaborate as they do not fully empathize with the problems of the other.
In addition, advances in communication and computational technologies enable new pathways to solutions. Rather than trying to solve public problems, governments are able to empower its public to solve their own problems. Crowdsourcing and bottom-up, emergent, problem-solving are desirable as the public have a greater chance of taking charge of their own local problems, voicing their concerns, and arriving at locally relevant solutions. Designing and mobilizing platforms where citizen input is used effectively to solve local problems and collaborative forums improves the results, and therefore the relationships, for both the policy makers and the public.
Policy informatics is the study of how information is leveraged and efforts are coordinated towards solving complex public policy problems. Driven by the need to exploit information to tackle complex policy problems and to ensure efficient and efficient policy setting and implementation platforms, policy informatics seeks to
- enhance policy analysis and design through visualizing, modeling, and simulating complex policy scenarios,
- study the role of information systems and information-based governance platforms in policy planning, deliberation, and implementation,
- advance the management of information systems projects in the public sector,
- study how information analysis and management influences the design of participatory platforms, and
- arrive at theoretical and practical frameworks to advance our knowledge of the roles of information analysis in policy setting, the use of computational techniques in policy contexts, and how information-driven policy setting influences the nature of governance and governance platforms.
Policy informatics helps us advance evidence-driven policy design, wherein scientific models and analyses drive decision-making for resolution of complex policy challenges, dilemmas, and problems. Policy informatics is an emerging field of both research and a community of practice focusing on 1) advancing decision-making in the public sector through information-centric analysis of evidence that leverages computational and technological advances, and 2) designing, managing, and evaluating of information systems and infrastructures for policy construction, analysis, and implementation. Policy informatics expands to the multi-disciplinary nature of the public administration discipline by infusing it with the advances of information technology, management of information systems, and computational and informational science perspectives.