Heath Network Clinicians Use and Need for Clinical Information Sources: Results of a Survey

The Dana Medical Library, part of the University of Libraries system, with the support of the University of Vermont Health Network, assessed the needs of UVM Health Network clinicians for evidence-based clinical resources such as: medical databases, journal articles, topic summaries, or electronic/print textbooks. Results are compiled and discussed

Computer-supported analysis of scientific measurements

In the past decade, large-scale databases and knowledge bases have become available to researchers working in a range of scientific disciplines. In many cases these databases and knowledge bases contain measurements of properties of physical objects which have been obtained in experiments or at observation sites. As examples, one can think of crystallographic databases with molecular structures and property databases in materials science. These large collections of measurements, which will be called measurement bases, form interesting resources for scientific research. By analyzing the contents of a measurement base, one may be able to find patterns that are of practical and theoretical importance. With the use of measurement bases as a resource for scientific inquiry questions arise about the quality of the data being analyzed. In particular, the occurrence of conflicts and systematic errors raises doubts about the reliability of a measurement base and compromises any patterns found in it. On the other hand, conflicts and systematic errors may be interesting patterns in themselves and warrant further investigation. These considerations motivate the topic that will be addressed in this thesis: the development of systematic methods for detecting and resolving con icts and identifying\ud systematic errors in measurement bases. These measurement analysis (MA) methods are implemented in a computer system supporting the user of the measurement base

Happiness: Theoretical and Empirical Considerations

TOPIC. Although happiness is important in maintaining health, few studies of happiness can be found in the nursing literature. PURPOSE. This paper explicates the concept of happiness through examination of its defining attributes, antecedents, consequences, and measurement. SOURCES OF INFORMATION. Literature review using hand search, and databases were used as sources of information. CONCLUSION. The information provided can be used in clinical practice so that nursing strategies can be developed and tested to help people to become happy and healthy

Topic Map Generation Using Text Mining

Starting from text corpus analysis with linguistic and statistical analysis algorithms, an infrastructure for text mining is described which uses collocation analysis as a central tool. This text mining method may be applied to different domains as well as languages. Some examples taken form large reference databases motivate the applicability to knowledge management using declarative standards of information structuring and description. The ISO/IEC Topic Map standard is introduced as a candidate for rich metadata description of information resources and it is shown how text mining can be used for automatic topic map generation

Efficient Analysis of Pattern and Association Rule Mining Approaches

The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules. Numerous efficient algorithms have been proposed to do the above processes. Frequent pattern mining has been a focused topic in data mining research with a good number of references in literature and for that reason an important progress has been made, varying from performant algorithms for frequent itemset mining in transaction databases to complex algorithms, such as sequential pattern mining, structured pattern mining, correlation mining. Association Rule mining (ARM) is one of the utmost current data mining techniques designed to group objects together from large databases aiming to extract the interesting correlation and relation among huge amount of data. In this article, we provide a brief review and analysis of the current status of frequent pattern mining and discuss some promising research directions. Additionally, this paper includes a comparative study between the performance of the described approaches.Comment: 14 pages, 3 figures. arXiv admin note: text overlap with arXiv:1312.4800; and with arXiv:1109.2427 by other author

Issues in student training and use of electronic bibliographic databases

In an article in this journal Ottewill and Hudson (1997) raised a number of issues concerning students’ use of electronic bibliographic databases. They emphasized the need for co‐operation between academics and librarians in database training and in coursework where databases would be used. We report a project on students’ use of bibliographic databases. Our findings reveal that access to these databases, whilst solving many of the problems students experience in sourcing reference material for coursework and research, raises new intellectual problems due to the sheer breadth and depth of their coverage of subject matter. Typically database training programmes focus on search skills and the use of different interfaces. However, our findings demonstrate that students should be encouraged to develop a more critical perspective on databases since these can be seductive, time‐consuming and, in certain circumstances, counterproductive resources. Students would benefit from more guidance on the quality cues that academics and librarians employ when evaluating different databases and their contents

Topic Maps as a Virtual Observatory tool

One major component of the VO will be catalogs measuring gigabytes and terrabytes if not more. Some mechanism like XML will be used for structuring the information. However, such mechanisms are not good for information retrieval on their own. For retrieval we use queries. Topic Maps that have started becoming popular recently are excellent for segregating information that results from a query. A Topic Map is a structured network of hyperlinks above an information pool. Different Topic Maps can form different layers above the same information pool and provide us with different views of it. This facilitates in being able to ask exact questions, aiding us in looking for gold needles in the proverbial haystack. Here we discuss the specifics of what Topic Maps are and how they can be implemented within the VO framework. URL: http://www.astro.caltech.edu/~aam/science/topicmaps/Comment: 11 pages, 5 eps figures, to appear in SPIE Annual Meeting 2001 proceedings (Astronomical Data Analysis), uses spie.st

Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On