Application of Data Mining for improving Participative Librarianship: a Brief Study

Data mining helps in analyzing and summarizing different elements of information. Data mining process is a form where in which all the data and information can be extracted for the purpose of future benefit. The data mining system has been designed for librarians to help them manage the library easily. It is relatively new term in the field of library science though it is being used in business organization for a long time. This paper gives an overview of data mining and its use in the field of library science; a process of data mining; advantages of data mining and also the implication of data mining in participative librarianship. Also, discuss the process of bibliomining which is very much useful for analyzing library service

Aplicación del proceso de KDD en el contexto de bibliomining: El caso Elogim

Access to scientific information in the world has traditionally been exclusive to selected groups, including professors, researchers, and students in higher education. In Latin America, the situation has had a few other variables: such as the cost of subscriptions and the lack of Spanish content in scientific journals. Fortunately current advancements in Information Technology and Communication are positively changing the way digital information is disseminated in the world. For the access to scientific information, the emergence of the Open Access (OA) model is enabling positive changes in the creation and dissemination of scientific information. This article presents the results of an analysis of the current situation and the expectations that the OA movement can mean for the Latin America countries

Data Mining in Digital Spaces: Introduction to the Basics

Former URI: http://hdl.handle.net/10125/43562Data mining is looking for information on large datasets to find trends in information needs. This poster gives a brief introduction to the definition of data mining and big data. Examples of data mining types and the ways that data mining techniques can be used to provide access to information are discussed

Facilitating resource allocation decision through bibliomining: the case of UTM's library

Library has vastly developed and demand from the users, institutions, international organization needs and technology advancement has changed the library planning and decision making approach in many ways including library budgeting, human resource and infrastructure allocations. This research described (a) the investigation undertaken to examine the characteristics of data from data reservoirs regarding user/patron information and circulation information. (b) The information seeking to explore the patterns and trends among these data reservoirs using data mining analysis with about 957,224 borrowing history and overall 31,052 registered readers and 139,195 title author of books from the Universiti Teknologi Malaysia library since 2008 to 2010. (c) To study how constructed patterns and trends generate informed decisions on resource allocation for circulation function by using cluster analysis, frequency statistics, averages and aggregates and market basket analysis algorithm. This thesis highlights the finding of a research using data mining technique (CRISP-DM) to explore the potentials of the bibliographic data of an academic library. With nearly 1 million records of collection in various formats, the Library of Universiti Teknologi Malaysia has been chosen as the case study for the research. The data mining technique was adopted to explore the relationship among statistically patterned and clustered bibliographic data. Bibliomining are tools that can visualize how libraries manage their costs, staff activity, customer service, user needs, marketing, popular books, circulation, reference transaction, quality of collection, educational programs etc. Similar data mining techniques are suggested to be employed in different library settings and even enterprises as to make more effective use of organizational resources

Bibliomining – o zastosowaniu eksploracji danych w badaniach bibliotek

Zagadnienia omawiane w artykule stanowią novum w polskiej literaturze. Termin „bibliomining” został wspomniany dotychczas jedynie w kilku krajowych publikacjach, a przydatność technik eksploracji danych do analizy bibliotek nie została również dogłębnie oceniona w literaturze światowej. Autor podkreśla, że „bibliomining” może być znaczącym zagadnieniem badawczym i zarazem obiecującym narzędziem pozyskiwania nowej wiedzy o bibliotekach również w Polsce.Udostępnienie publikacji Wydawnictwa Uniwersytetu Łódzkiego finansowane w ramach projektu „Doskonałość naukowa kluczem do doskonałości kształcenia”. Projekt realizowany jest ze środków Europejskiego Funduszu Społecznego w ramach Programu Operacyjnego Wiedza Edukacja Rozwój; nr umowy: POWER.03.05.00-00-Z092/17-00. Publikacja wydana dzięki wsparciu finansowemu Uniwersytetu Łódzkiego

Integrated Decision Support System – iDSS for Library Holistic Evaluation

The decision-making process in academic libraries is paramount; however highly complicated due to the large number of data sources, processes and high volumes of data to be analyzed. Academic libraries are accustomed to producing and gathering a vast amount of statistics about their collection and services. Typical data sources include integrated library systems, library portals and online catalogues, systems of consortiums, quality surveys and university management. Unfortunately, these heterogeneous data sources are only partially used for decision-making processes due to the wide variety of formats, standards and technologies, as well as the lack of efficient methods of integration. This article presents the analysis and design of an integrated decision support system for an academic library. Firstly, a holistic approach documented in a previous study is used for data collection. This holistic approach incorporates key elements including process analysis, quality estimation, information relevance and user interaction that may influence a library’s decision. Based on the mentioned approach above, this study defines a set of queries of interest to be issued against the integrated system proposed. Then, relevant data sources, formats and connectivity requirements for a particular example are identified. Next, data warehouse architecture is proposed to integrate, process, and store the collected data transparently. Eventually, the stored data are analyzed through reporting techniques such as on-line analytical processing tools. By doing so, the article provides the design of an integrated solution that assists library managers to make tactical decisions about the optimal use and leverage of their resources and services

Usefulness and Applications of Data Mining in Extracting Information from Different Perspectives

Discusses the concept of data mining, its applications, benefits and the standard tasks involved in the process are explained. Such pattern-seeking techniques usually performed with a wide range of related areas (viz. statistics, neural networks, genetic algorithms, machine learning, pattern recognition, knowledge-based systems, etc.) are described. Also focuses on bibliomining opportunities to be useful to information retrieval, semantic analysis of unstructured texts, web-usage mining and to make proactive as well as knowledge-driven decision across library services Suggests use of data mining in combination with other techniques of evaluation, exploiting large data warehouses by skilled specialists, and advises for ethical uses without privacy invasion

The Digital Reference Electronic Warehouse (DREW) Project: Creating the Infrastructure for Digital Reference Research through a Multi-Disciplinary Knowledge Base

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. This schema will also allow researchers to develop tools that practitioners can employ; this will 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 (DREW).Informatio

Big data-driven investigation into the maturity of library research data services (RDS)

Research data management (RDM) poses a significant challenge for academic organizations. The creation of library research data services (RDS) requires assessment of their maturity, i.e., the primary objective of this study. Its authors have set out to probe the nationwide level of library RDS maturity, based on the RDS maturity model, as proposed by Cox et al. (2019), while making use of natural language processing (NLP) tools, typical for big data analysis. The secondary objective consisted in determining the actual suitability of the above-referenced tools for this particular type of assessment. Web scraping, based on 72 keywords, and completed twice, allowed the authors to select from the list of 320 libraries that run RDS, i.e., 38 (2021) and 42 (2022), respectively. The content of the websites run by the academic libraries offering a scope of RDM services was then appraised in some depth. The findings allowed the authors to identify the geographical distribution of RDS (academic centers of various sizes), a scope of activities undertaken in the area of research data (divided into three clusters, i.e., compliance, stewardship, and transformation), and overall potential for their prospective enhancement. Although the present study was carried within a single country only (Poland), its protocol may easily be adapted for use in any other countries, with a view to making a viable comparison of pertinent findings

Using Lessons from Health Care to Protect the Privacy of Library Users: Guidelines for the De-Identification of Library Data based on HIPAA

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