Information governance

Abstract: Adaptive governance is an emergent form of environmental governance that is increasingly called upon by scholars and practitioners to coordinate resource management regimes in the face of the complexity and uncertainty associated with rapid environmental change. Although the term "adaptive governance" is not exclusively applied to the governance of social-ecological systems, related research represents a significant outgrowth of literature on resilience, social-ecological systems, and environmental governance. We present a chronology of major scholarship on adaptive governance, synthesizing efforts to define the concept and identifying the array of governance concepts associated with transformation toward adaptive governance. Based on this synthesis, we define adaptive governance as a range of interactions between actors, networks, organizations, and institutions emerging in pursuit of a desired state for social-ecological systems. In addition, we identify and discuss ambiguities in adaptive governance scholarship such as the roles of adaptive management, crisis, and a desired state for governance of social-ecological systems. Finally, we outline a research agenda to examine whether an adaptive governance approach can become institutionalized under current legal frameworks and political contexts. We suggest a further investigation of the relationship between adaptive governance and the principles of good governance; the roles of power and politics in the emergence of adaptive governance; and potential interventions such as legal reform that may catalyze or enhance governance adaptations or transformation toward adaptive governance.

Abstract: IntroductionOrganizations are becoming increasingly serious about the notion of "data as an asset" as they face increasing pressure for reporting a "single version of the truth." In a 2006 survey of 359 North American organizations that had deployed business intelligence and analytic systems, a program for the governance of data was reported to be one of the five success "practices" for deriving business value from data assets. In light of the opportunities to leverage data assets as well ensure legislative compliance to mandates such as the Sarbanes-Oxley (SOX) Act and Basel II, data governance has also recently been given significant prominence in practitioners' conferences, such as TDWI (The Data Warehousing Institute) World Conference and DAMA (Data Management Association) International Symposium.The objective of this article is to provide an overall framework for data governance that can be used by researchers to focus on important data governance issues, and by practitioners to develop an effective data governance approach, strategy and design. Designing data governance requires stepping back from day-to-day decision making and focusing on identifying the fundamental decisions that need to be made and who should be making them. Based on Weill and Ross, we also differentiate between governance and management as follows:• Governance refers to what decisions must be made to ensure effective management and use of IT (decision domains) and who makes the decisions (locus of accountability for decision-making).• Management involves making and implementing decisions.For example, governance includes establishing who in the organization holds decision rights for determining standards for data quality. Management involves determining the actual metrics employed for data quality. Here, we focus on the former.Corporate governance has been defined as a set of relationships between a company's management, its board, its shareholders and other stakeholders that provide a structure for determining organizational objectives and monitoring performance, thereby ensuring that corporate objectives are attained. Considering the synergy between macroeconomic and structural policies, corporate governance is a key element in not only improving economic efficiency and growth, but also enhancing corporate confidence. A framework for linking corporate and IT governance (see Figure 1) has been proposed by Weill and Ross.Unlike these authors, however, we differentiate between IT assets and information assets: IT assets refers to technologies (computers, communication and databases) that help support the automation of well-defined tasks, while information assets (or data) are defined as facts having value or potential value that are documented. Note that in the context of this article, we do not differentiate between data and information.Next, we use the Weill and Ross framework for IT governance as a starting point for our own framework for data governance. We then propose a set of five data decision domains, why they are important, and guidelines for what governance is needed for each decision domain. By operationalizing the locus of accountability of decision making (the "who") for each decision domain, we create a data governance matrix, which can be used by practitioners to design their data governance. The insights presented here have been informed by field research, and address an area that is of growing interest to the information systems (IS) research and practice community.

Abstract: Sustainable natural resource use and management make novel demands on governance arrangements, the design of which requires normative guidance. Although governance principles have been developed for diverse contexts, their availability for sustainable natural resource governance is so far limited. In response, we present a suite of governance principles for natural resource governance that, while developed in an Australian multilevel context, has general applicability and significance at local, subnational, and national scales. The principles can be used to direct the design of governance institutions that are legitimate, transparent, accountable, inclusive, and fair and that also exhibit functional and structural integration, capability, and adaptability. Together, they can also serve as a platform for developing governance monitoring and evaluation instruments, crucial for both self-assessment and external audit purposes.

Abstract: Governance Networks in the Public Sector presents a comprehensive study of governance networks and the management of complexities in network settings. Public, private and non-profit organizations are increasingly faced with complex, wicked problems when making decisions, developing policies or delivering services in the public sector. These activities take place in networks of interdependent actors guided by diverging and sometimes conflicting perceptions and strategies. As a result these networks are dominated by cognitive, strategic and institutional complexities. Dealing with these complexities requires sophisticated forms of coordination: network governance. This book presents the most recent theoretical and empirical insights into governance networks. It provides a conceptual framework and analytical tools to study the complexities involved in handling wicked problems in governance networks in the public sector. The book also discusses strategies and management recommendations for governments, business and third sector organisations operating in and governing networks. Governance Networks in the Public Sector is an essential text for advanced students of public management, public administration, public policy and political science, and for public managers and policymakers.