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Apresenta uma metodologia operacional integrada, utilizando técnicas de repositórios de dados (data warehousing) e mineração de dados (data mining), e combinando ferramentas estatísticas com reconhecimento de padrões. Tendo em vista a utilização de recursos, o objetivo principal é chegar a um entendimento melhor do comportamento de comunidades de usuários. O anonimato dos usuários fica inteiramente assegurado na aplicação do modelo, pelo qual são processados os dados oriundos de arquivos transacionais da biblioteca. O próprio processo da bibliomineração consiste basicamente em coletar, depurar e anonimizar os dados, visando, precipuamente, a descoberta de padrões subjacentes. Os resultados podem ser combinados com diferentes variáveis, antes de sua utilização na tomada de decisão pela Administração da biblioteca. In order to get a better understanding of library user communities and to improve resource utilization, the author proposes an integrated operational application of data warehousing and datamining, combining statistical and pattern recognition tools, both integrated under a new concept named bibliomining. With the application of this model to transactional records of the library, patron privacy is fully respected through the creation of an anonymized version of the operational data, before reformatting them for bibliomining analysis. The bibliomining process itself consists mainly of collecting, cleaning and anonymizing the data, in order to discover underlying behavior patterns. The results can be combined with several variables, before being used to improve decision-making by the library administration.

For decades, the corporate sector has exploited technological advances to better market and deliver products and services to customers via the techniques of data mining. The technique was not widely used in libraries. However, with the current emphasis on evidence-based decision making, libraries are beginning to utilize their system- and user- generated data. Data mining usually involves a significant endeavor to extract embedded and potentially useful information from large undiscovered data sets (Mitra & Acharya, 2003; Hand, Mannila & Smyth, 2001; Frawley, Piatetsky-Shapiro, & Matheus 1992; Piatetsky-Shapiro & Frawley 1991). These data mining techniques are being used by librarians to improve both internal decision-making and external user services by extracting information from operational datasets of both bibliographic and user data. OCLC Research has taken advantage of the WorldCat database, which includes more than 95 million bibliographic records and 1.2 billion holdings records, as well as data provided by other major library systems and consortia to develop user-oriented collections and services (http://www.oclc.org/research/projects/mining/).

The goal of the technology brief is to familiarize library decision-makers with the opportunities and challenges of participatory networks. In order to accomplish this goal the brief is divided into four sections (excluding an overview and a detailed statement of goal):a conceptual framework for understanding and evaluating participatory networks;a discussion of key concepts and technologies in participatory networks drawn primarily from Web 2.0 and Library 2.0;a merging of the conceptual framework with the technological discussion to present a roadmap for library systems development; anda set of recommendations to foster greater discussion and action on the topic of participatory networks and, more broadly, participatory librarianship.This summary will highlight the discussions in each of these four topics. For consistency, the section numbers and titles from the full brief are used.

One of the valuable offerings of librarians in the digital age is the human intermediation of information needs. In physical libraries, these reference questions are answered, and few artifacts remain from the transaction; therefore, the knowledge created through the work of the librarian leaves with the patron. Due to the medium of communication, digital reference transactions capture the knowledge of information professionals. There are hundreds of digital reference services generating knowledge every day; however, the lack of a schema for archiving reference transactions from multiple services makes it difficult to create a fielded, searchable knowledge base. The development of such a schema would allow researchers to develop tools that practitioners can employ. In turn, this would create a collaborative environment for digital reference evaluation. The goal of this work is to outline the steps needed to develop this schema, present the results of a survey of digital reference services, explore some of the pitfalls in the process, and envision the future uses of this Digital Reference Electronic Warehouse.

This series of questions and answers is designed to help you take the first steps toward the successful production of a scholarly article in librarianship. You may find yourself in a library position that requires writing or you may have just decided that you are ready to share your findings, experiences, and knowledge with the current and future generations of librarians. While following the guidelines listed here will not guarantee that you will be successful, these steps will take you closer to discovering the thrill of seeing your name in print and making a difference in the field.

Over the past few years, data mining has moved from corporations to other organizations. This paper looks at the integration of data mining in digital library services. First, bibliomining, or the combination of bibliometrics and data mining techniques to understand library services, is defined and the concept explored. Second, the conceptual frameworks for bibliomining from the viewpoint of the library decision-maker and the library researcher are presented and compared. Finally, a research agenda to resolve many of the common bibliomining issues and to move the field forward in a mindful manner is developed. The result is not only a roadmap for understanding the integration of data mining in digital library services, but also a template for other cross-discipline data mining researchers to follow for systematic exploration in their own subject domains.

This conceptual piece presents a framework to aid libraries in gaining a more thorough and holistic understanding of their users and services. Through a presentation of the history of library evaluation, a multidimensional matrix of measures is developed that demonstrates the relationship between the topics and perspectives of measurement. These measurements are then combined through evaluation criteria, and then different participants in the library system view those criteria for decision making. By implementing this framework for holistic measurement and cumulative evaluation, library evaluators can gain a more holistic knowledge of the library system and library administrators can be better informed for their decision‐making processes.

While libraries have employed policies to protect the data about use of their services, these policies are rarely specific or standardized. Since 1996 the U.S. healthcare system has been grappling with the Health Insurance Portability and Accountability Act (HIPAA), which is designed to provide those handling personal health information with standardized, definitive instructions as to the protection of data. In this work, the authors briefly discuss the present situation of privacy policies about library use data, outline the HIPAA guidelines to understand parallels between the two, and finally propose methods to create a de-identified library data warehouse based on HIPAA for the protection of user privacy.

The final published version of this article is available at: https://doi.org/10.1016/S0306-4573(02)00085-7, This paper describes a study conducted to determine the paths digital reference services take through a general process model of asynchronous digital reference. A survey based on the general process model was conducted; each decision point in this model provided the basis for at least one question. Common, uncommon, and wished-for practices are identified, as well as correlations between characteristics of services and the practices employed by those services. Identification of such trends has implications for the development of software tools for digital reference. This study presents a snapshot of the state of the art in digital reference as of late 2001 – early 2002, and validates the general process model of asynchronous digital reference.

Bibliomining is the combination of data mining, bibliometrics, statistics, and reporting tools used to extract patterns of behavior-based artifacts and item-based metadata from library systems. The bibliomining process involves the identification of problem areas, the collecting and anonymizing of data into a data warehouse, the exploration of the data with data mining tools, and the analysis, validation, and implementation of the results. This panel will introduce the topic of bibliomining and present ways in which data warehousing and data mining are currently being used in library settings.