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Beneath the problem of achieving digital convergence in the heritage sector is a problem of deeply entrenched discourses generated in a physical paradigm where objects kept in heritage sector institutions were treated as goods to be divided, and where notions about the nature of those goods, their use, and practices facilitating their use, were imagined in terms of the norms for each institution type. The digital paradigm provides new opportunities, amongst them the possibility of creating intersecting digital knowledge spaces designed to aid processes of enquiry and meaning-making and to maximise possibilities for rational and justifiable knowledge formation about predictable and still to be imagined topics of enquiry. Achieving that vision calls for research that seeks to understand the process of knowledge formation, that hunts out the strengths and weaknesses in existing bodies of thought, and that works, through its modes of transmission, to instil the understanding necessary for a shared knowledge-oriented body of theory and practice to emerge. The research reported in this thesis responds to these needs. It was conducted by a former archives practitioner taking a fresh look at her own discipline's body of thought, and reflecting on its utility across the whole heritage sector. An open and exploratory research question was posed: What can be learnt about archives domain thinking, heritage objects and their evidentiality, and the design of knowledge enabling systems by exploring how evidence emerges during a historical research process? The research design combined close examination of the archives domain's explicit and implicit thinking with a case study in the form of a deeply reflective historical enquiry that was committed to tracking down and tracing seemingly relevant objects (both physical and digital), and their meaningful ways of being related, across institutional and conceptual boundaries.

This thesis explores and investigates the process of cross-boundary information sharing by knowledge brokers (KB) during a disaster using lenses of knowledge management and naturalistic decision making. The study integrated interpretivist and positivist stances, conducted using qualitative methods. It used a multiple case embedded research design and in-depth face-to-face interviews as the method of inquiry and an inductive process of theory generation. The cases were in the context of disasters that occurred in New Zealand. The unit of analysis was the scenarios that KB experienced during disasters. Based on a four stage analysis of the data, there were two phases that KB went through in assessing the veracity of the information they received and deciding to whom the information is relevant. In each phase, KB were relying on different cognitive resources to filter and to match the information. It was also found that there were different types of boundary, information and disasters. Interestingly, it was found that KB used different tactics to make the decision on the information's veracity and to whom it is relevant. The primary contribution of this thesis is the generation and explanation of the theoretical model of cross-boundary information sharing by KB during a disaster. This theory can also be used by practitioners as a guide to improve disaster management training and for the community to prepare stronger resilience plans.

Purpose: The purpose of this study was to assess the healthcare information needs of decision-makers in a local US healthcare setting in efforts to promote the translation of knowledge into action. The focus was on the perceptions and preferences of decision-makers regarding usable information in making decisions as to identify strategies to maximize the contribution of healthcare findings to policy and practice., Methods: This study utilized a qualitative data collection and analysis strategy. Data was collected via open-ended key-informant interviews from a sample of 37 public and private-sector healthcare decision-makers in the Houston/Harris County safety net. The sample was comprised of high-level decision-makers, including legislators, executive managers, service providers, and healthcare funders. Decision-makers were asked to identify the types of information, the level of collaboration with outside agencies, useful attributes of information, and the sources, formats/styles, and modes of information preferred in making important decisions and the basis for their preferences., Results: Decision-makers report acquiring information, categorizing information as usable knowledge, and selecting information for use based on the application of four cross-cutting thought processes or cognitive frameworks. In order of apparent preference, these are time orientation, followed by information seeking directionality, selection of validation processes, and centrality of credibility/reliability. In applying the frameworks, decision-makers are influenced by numerous factors associated with their perceptions of the utility of information and the importance of collaboration with outside agencies in making decisions as well as professional and organizational characteristics., Conclusion: An approach based on the elucidated cognitive framework may be valuable in identifying the reported contextual determinants of information use by decision-makers in US healthcare settings. Such an approach can facilitate active producer/user collaborations and promote the production of mutually valued, comprehensible, and usable findings leading to sustainable knowledge translation efforts long-term.

State transportation agencies deal with numerous technical and organizational challenges in building integrated data and information systems to provide high-quality information for supporting analysis, control and decision making in asset management. There is a need to identify the approaches that work and to develop guidelines for agencies working to achieve data integration. This project seeks to identify relevant metrics for performance measurement and the underlying factors and best practices that contribute to successful approaches. The research was comprised of six tasks: literature review; design of data collection instruments; pilot testing of data collection instruments; collection of data - interviews; identification and analysis of key success factors, best practices, and performance measures; and preparation of the guidelines document. Comprehensive case studies on data integration issues and best practices regarding asset management and information systems development were conducted on the Wisconsin, Michigan and Ohio Departments of Transportation. All data integration efforts must be business driven. Without a business imperative for investing in systems development, there is no incentive for people to learn or implement the new system. Successful development of asset management systems require constant involvement of both business and technology people and a great deal of communication with both end users and users of the business systems being integrated.