This research developed a comprehensive methodology to quickly monitor key technical intelligence areas, provided a method that cleanses and consolidates information into an understandable, concise picture of topics of interest, thus bridging issues of managing technology and text mining. This research evaluated and altered some existing analysis methods, and developed an overall framework for answering technical intelligence questions. A six-step approach worked through the various stages of the Intelligence and Text Data Mining Processes to address issues that hindered the use of Text Data Mining in the Intelligence Cycle and the actual use of that intelligence in making technology decisions. A questionnaire given to 34 respondents from four different industries identified the information most important to decision-makers as well as clusters of common interests. A bibliometric/text mining tool applied to journal publication databases, profiled technology trends and presented that information in the context of the stated needs from the questionnaire. In addition to identifying the information that is important to decision-makers, this research improved the methods for analyzing information. An algorithm was developed that removed common non-technical terms and delivered at least an 89% precision rate in identifying synonymous terms. Such identifications are important to improving accuracy when mining free text, thus enabling the provision of the more specific information desired by the decision-makers. This level of precision was consistent across five different technology areas and three different databases. The result is the ability to use abstract phrases in analysis, which allows the more detailed nature of abstracts to be captured in clustering, while portraying the broad relationships as well.

Many online retailers monitor visitor traffic as a measure of their storesâ success. However, summary measures such as the total number of visits per month provide little insight about individual-level shopping behavior. Additionally, behavior may evolve over time, especially in a changing environment like the Internet. Understanding the nature of this evolution provides valuable knowledge that can influence how a retail store is managed and marketed. This paper develops an individual-level model for store visiting behavior based on Internet clickstream data. We capture cross-sectional variation in store-visit behavior as well as changes over time as visitors gain experience with the store. That is, as someone makes more visits to a site, her latent rate of visit may increase, decrease, or remain unchanged as in the case of static, mature markets. So as the composition of the customer population changes (e.g., as customers mature or as large numbers of new and inexperienced Internet shoppers enter the market), the overall degree of visitor heterogeneity that each store faces may shift. We also examine the relationship between visiting frequency and purchasing propensity. Previous studies suggest that customers who shop frequently may be more likely to make a purchase on any given shopping occasion. As a result, frequent shoppers often comprise the preferred target segment. We find evidence supporting the fact that people who visit a store more frequently are more likely to buy. However, we also show that changes (i.e., evolution) in an individualâ s visit frequency over time provides further information regarding which customer segments are more likely to buy. Rather than simply targeting all frequent shoppers, our results suggest that a more refined segmentation approach that incorporates how much an individualâ s behavior is changing could more efficiently identify a profitable target segment.

The model developed by Bob Taylor for his book Value-Added Processes in Information Systems (1986) has been highly influential in the field of library and information science. Yet despite its impact on the broader field, the potential of the Value-Added Model has gone largely unexplored by knowledge organization researchers. Unraveling the history behind Taylorâ s development of the model highlights the significant role played by professional indexers. The Value-Added Model is thus reexamined for its potential as a flexible framework for evaluating knowledge organization systems.

This article examines selected economic and social indicators of our multiracial and multiethnic society at the end of the twentieth century to provide an information base for wise decisions about effective library services. The statistical profile describes the demography, economic well-being, and education attainment of the principal racial and Hispanic origin groups. The data show that progress in our nation's well-being has occurred, but a great deal remains to be done to achieve the goals of equity and equality of opportunity.

Law, mission, and information management practices inhibit access to computerized administrative records produced by state government. Research use or secondary analysis is not on the agenda of the agency administrator. Computerized records are not routinely maintained or preserved. Records managers and archivists for public records do not participate in decisions about retaining or destroying computerized records. These findings emerged from a recently completed cooperative study conducted by the University of Wisconsin-Madison and the State Historical Society of Wisconsin on the impact of automation on state agency records keeping practices. In addition, changes in rules for access, computer-based technologies, pressures to maintain routine administration in the face of high turnover in data processing staffs, reduced budgets, and legislation to reduce paperwork pose a threat to the retention of administrative records. This article discusses the implications of the findings and trends, provides examples of data delivery failures, and recommends changes in law and administrative behavior. The authors conclude that the social scientist has a role to play in assisting government agencies in improving access to computerized administrative records.

Public concern about personal privacy has recently focused on issues of Internet data security and personal information as big business. The scientific discourse about information privacy focuses on the crosspressures of maintaining confidentiality and ensuring access in the context of the production of statistical data for public policy and social research and the associated technical solutions for releasing statistical data. This article reports some of the key findings from a smallscale survey of organizational practices to limit disclosure of confidential information prior to publishing public use microdata files, and illustrates how the rules for preserving confidentiality were applied in practice. Explanation for the apparent deficits and wide variations in the extent of knowledge about statistical disclosure limitation (SDL) methods is located in theories of organizational life and communities of practice. The article concludes with suggestions for improving communication between communities of practice to enhance the knowledge base of those responsible for producing public use microdata files.

Statistics from the Health and Safety Executive show that the UK construction industry has approximately 80 fatalities per year, making the construction industry one of the most dangerous industries when compared to other industries. The reduction of construction accidents in the construction industry has led to the need for thoroughly analysed construction environment information which can be effectively utilised in formulating construction health and safety planning strategies, thus enabling the construction industry meet accident reduction targets. However, existing approaches to information analysis mainly focus on factors within construction health and safety information during analysis and do not shed light on the influencing socio-economic and spatially influenced issues within which the industry’s accident contributory factors are rooted. It is also clear that limitations of information usage in the construction industry are due to the fragmented nature in which health and safety information is availed to practitioners for ultimate utilisation in the construction process. There is, therefore, a need for more appropriate decision-support mechanisms that can take account of spatial contributory factors to accident occurrence. There is also a need for mechanisms that enhance the management, analysis and utilisation construction environment information from varied sources for integration in the construction process. The failure to utilise information from varied sources in the construction industry, means that adequately analysed information is lacking for integration in construction health and safety planning strategy formulation process. This study was initiated as a response to this challenge. This prompted further research into the utilisation of health and safety information and its integration in the construction process. A survey involving 215 construction stakeholders was conducted to establish the limitation and requirements of health and safety in the construction industry. Results derived through qualitative analysis further emphasised the need for enhanced health and safety information analysis and integration for use in decision making. The research explored how the spatial element present in all in construction environment information could be utilised to account for accident contributory factors. This led to the exploration Geographical Information System (GIS), a mechanism that takes into account spatial aspects of bodies of information of the phenomenon being explored, for its potential capabilities in management and analysis of construction environment information. The implementation of the GIS-based system known as Geographical Information System for Accident Prevention (GISAP) is then presented. The evaluation of the system by prospective end-users reveals the limitations and benefits of the system implementation and recommendations made for further research. In conclusion, it was clear from this study that this approach has the potential to provide a quick referencing GIS success that can link, organise, analyse and display accident data and other construction and non construction environment data. This can assist stakeholders in decision making during formulation of construction health and safety strategies. The approach can improve understanding of analyses and can enhance the handling of queries related to accident data and other data. This innovative approach can also offer an extra dimension of safety information management, identify trends and areas for effective accident preventive action and ultimately enable development and directions of future work and to engender wider debate.

This is a submission to the "Interrogating the social realities of information and communications systems pre-conference workshop, ASIST AM 2006." There is great potential in the utilization of existing clinical data to assist in decision support, epidemiology, and information retrieval. As we transition from evaluating systemsâ abilities to accurately capture the information in the record, to the clinical application of results, we must incorporate the contextual influences that affect such efforts. A methodology is proposed to assist researchers in identifying strengths and weaknesses of clinical data for application to secondary purposes. The results of its application to three ongoing clinical research projects are discussed.

“What does the global research environment look like?” This paper presents a summary look at the results of efforts to address this question using available indicators on global research production. It was surprising how little information is available, how difficult some of it is to access and how flawed the data are. The three most useful data sources were UNESCO (United Nations Educational, Scientific and Cultural Organization) Research and Development data (1996-2002), the Institute of Scientific Information publications listings for January 1998 through March 2003, and the World of Learning 2002 reference volume. The data showed that it is difficult to easily get a good overview of the global research situation from existing sources. Furthermore, inequalities between countries in research capacity are marked and challenging. Information science offers strategies for responding to both of these challenges. In both cases improvements are likely if access to information can be facilitated and the process of integrating information from different sources can be simplified, allowing transformation into effective action. The global research environment thus serves as a case study for the focus of this paper – the exploration of information science responses to challenges in the management, exchange and implementation of knowledge globally.

Grand challenges such as public health, security, genomics, environmental protection, education, and economics, are characterized by complexity, interdependence, globalization, and unpredictability. Although the unprecedented quantity of information surrounding these challenges can provide users with a new perspective on solutions, the data surrounding complex systems vary with respect to levels of structure and authority, and include vastly different contexts and vocabularies. To be successful in this domain we must extend our models of information science such that they operate successfully in environments where the quantity of relevant information far exceeds our human processing capacity. For example, the well-accepted precision and recall metrics break down when hundreds of thousands of documents are relevant. Solutions to grand challenges require that information scientists shift their focus from information retrieval towards information synthesis.