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The purpose of this article is to present an overview of the history and development of transaction log analysis (TLA) in library and information science research. Organizing a literature review of the first twenty‐five years of TLA poses some challenges and requires some decisions. The primary organizing principle could be a strict chronology of the published research, the research questions addressed, the automated information retrieval (IR) systems that generated the data, the results gained, or even the researchers themselves. The group of active transaction log analyzers remains fairly small in number, and researchers who use transaction logs tend to use this method more than once, so tracing the development and refinement of individuals' uses of the methodology could provide insight into the progress of the method as a whole. For example, if we examine how researchers like W. David Penniman, John Tolle, Christine Borgman, Ray Larson, and Micheline Hancock‐Beaulieu have modified their own understandings and applications of the method over time, we may get an accurate sense of the development of all applications.

Introduction Since the earliest transaction monitoring studies, researchers have encountered the boundaries that define transaction log analysis as a methodology for studying the use of online information retrieval systems. Because, among other reasons, transaction log databases contain relatively few fields and lack sufficient retrieval tools, students of transaction log data have begun to ask as many questions about what transaction logs cannot reveal as they have asked about what transaction logs can reveal. Researchers have conducted transaction monitoring studies to understand the objective phenomena embodied in this statement: “Library patrons enter searches into online information retrieval systems.” Transaction log data effectively describe what searches patrons enter and when they enter them, but they don't reflect, except through inference, who enters the searches, why they enter them, and how satisfied they are with their results.

To provide a review of the log analysis studies of use and users of scholarly electronic journals.

The advantages and limitations of log analysis are described and then past studies of e‐journals' use and users that applied this methodology are critiqued. The results of these studies will be very briefly compared with some survey studies. Those aspects of online journals' use and users studies that log analysis can investigate well and those aspects that log analysis can not disclose enough information about are highlighted.

The review indicates that although there is a debate about reliability of the results of log analysis, this methodology has great potential for studying online journals' use and their users' information seeking behaviour.

This paper highlights the strengths and weaknesses of log analysis for studying digital journals and raises a couple of questions to be investigated by further studies.

This paper seeks to discuss measurement units by comparing the internet use and the traditional media use, and to understand internet use from the traditional media use perspective.

Benefits and shortcomings of two log file types will be carefully and exhaustively examined. Client‐side and server‐side log files will be analyzed and compared with proposed units of analysis.

Server‐side session time calculation was remarkably reliable and valid based on the high correlation with the client‐side time calculation. The analysis result revealed that the server‐side log file session time measurement seems more promising than the researchers previously speculated.

An ability to identify each individual user and low caching problems were strong advantages for the analysis. Those web design implementations and web log data analysis scheme are recommended for future web log analysis research.

This paper examined the validity of the client‐side and the server‐side web log data. As a result of the triangulation of two datasets, research designs and propose analysis schemes could be recommended.

The purpose of this paper is to determine the digital library usage patterns as a means of improving the system, as well as the user experience, to give appropriate recognition to the most popular dissertations’ authors and to measure the interest of non-academic users for dissertations defended at the University of Novi Sad (UNS).

A logging module of the digital library of theses and dissertations of University of Novi Sad (PHD UNS) application has been implemented. The module recorded the messages relating to the search queries and downloads over a three-year period from 2017–2019. These logs are analysed using the Elasticsearch, Logstash and Kibana (ELK) technology stack and the results are shown using graphs and tables.

The analysis determined the perfect time for weekly maintenance of the system, defined a recommendation for improving the system and revealed the most popular dissertations. A significant number of downloads and queries originated from citizens, i.e. users outside the academic community.

The conducted analysis defined recommendations for the system improvement which can be used by PHD UNS research and development (R&D) team and revealed the most popular dissertations which are used for the promotion of its authors through faculties’ websites.

To the best of the authors’ knowledge, this is the first study of ELK based log analysis of a Serbian language documents’ repository. Besides, the value of results for the PHD UNS R&D team and UNS rector team, the study proves that PhD digital library presents an important Open Science communication channel for presenting scientific results to the citizens.

This study explored spatial usage of a public library based on activity logs produced by real users. The purpose of this paper is to provide preliminary data for decision-making when establishing the library operation policy.

To achieve the goal, the author collected a variety of data including 274,242 seat reservations logs, 3,361,284 collection usage logs, and 96,098 user information for the four years in which the National Library of Korea, Sejong actually operated. The crawled data were analyzed statistically in terms of demography, month, day of week, time of day and room by room. The author conducted additional in-depth analysis according to the external factors such as weather or social demographic environment. Finally, the author discussed several issues and verified feasibility of the proposals to support decision-making in operating a library in conclusion with a secondary librarian interview.

The usage rate in all the spaces of the National Library of Korea, Sejong, has been increasing since its opening, and, in particular, the usage rate increases sharply in January, February, July and August. In addition, the usage rate during weekends was higher than that during weekdays, and all the four spaces had a high usage rate during the afternoon. These results seem to be related to weather, users’ life pattern, users’ age, and position of PCs and seats. Based on the circulation logs analysis of children’s collections, users in their 10s and 40s showed the same space usage pattern.

This study has significance in that it attempted to analyze logs produced by real users during the actual library operation period, which has not been frequently attempted in the previous studies on libraries. The findings will be provided as basic data to support decision-making for efficient operation of libraries.

To present the latest results of research conducted at University College London as part of the Virtual Scholar Research Programme, investigating the impact of the digital roll‐out of information services to academics and researchers. This is the second study to look at the information seeking behaviour of academics and researchers in regard to digital journal libraries, and concentrates on the users and usage of Blackwell Synergy.

Nearly a million users making ten million item requests were investigated employing deep log methods, developed by the authors to provide robust and big picture analyses of digital information consumers and their behaviour.

Usage data has been embellished with user data (for 500,000 people), so enabling comparisons to be made between the information seeking behaviour, for instance, of students and staff, academics and practitioners, scientists and social scientists. We believe this is the first time this type of analysis has been attempted with logs. Of particular note is the “repeat visitor” evaluation and the analysis of one and a quarter million search sessions which categorised sessions in terms of how “busy” they were for a whole range of user groups.

Demonstrates a powerful and new method, deep log analysis, for mapping and evaluating information seeking behaviour.

Important data for publishers to enable them to target their services more effectively

Probably the first analysis of its type, hence showing an aspect of information seeking not previously seen.

The purpose of this paper is to demonstrate a novel form of deep log analysis by linking questionnaire data with transactional server log data generated by the same users; and to provide a richer understanding of the information‐seeking behaviour of a strategic community of virtual scholars.

Usage statistics were obtained from logs for an 18‐month period: 16,865 sessions were covered and 110,029 pages were viewed. Searching behaviour was studied in regard to number of returned hits and number of searches in a session. A questionnaire survey was also conducted to identify ScienceDirect users according to the subject/discipline to which they belonged and attitude towards some scholarly communication issues. The answers of more than 750 ScienceDirect users to the questionnaire were linked to the usage logs of the same users through matching internet protocol (IP) addresses.

The study reveals large differences between scholars in different subjects in terms of information‐seeking behaviour and their interaction with electronic journal systems.

The findings can be utilised to improve electronic journal systems such as ScienceDirect in order to provide more suitable service for users in different subjects.

The originality of the paper lies in its methodology that links questionnaire attitudinal data to the web log data of the same users at individual level to gain a better understanding of users' behaviour.

This paper aims to analyze the pressure behavior in dual porosity reservoirs using different techniques in an attempt to correctly characterize reservoir properties. Pressure transient tests in naturally fractured reservoirs often exhibit non-uniform responses.

The pressure transient tests in naturally fractured reservoirs were analyzed using conventional semi-log analysis, type curve matching (using commercial software) and Tiab’s direct synthesis (TDS) technique. In addition, the TDS method was applied in case of a naturally fractured formation with a vertical hydraulic fracture. These techniques were applied to a single-layer, naturally fractured reservoir under pseudosteady state matrix flow. By studying the unique characteristics of the different flow regimes appear on the pressure and pressure derivative curves, various reservoir characteristics can be obtained such as permeability, skin factor and fracture properties.

For naturally fractured reservoirs, a comparison between the results semi-log analysis, software matching and TDS method is presented. In case of wellbore storage, early time flow regime can be obscured that lead to incomplete semi-log analysis. Furthermore, the type curve matching usually gives a non-uniqueness solution, as it needs all the flow regimes to be observed. However, the direct synthesis method used analytical equation to calculate reservoir and well parameters without type curve matching. For naturally fractured reservoirs with a vertical fracture, the pressure behavior of wells crossed by a uniform flux and infinite conductivity fracture is analyzed using TDS technique. The different flow regimes on the pressure derivative curve were used to calculate the fracture half-length in addition to other reservoir properties.

The results of different field cases showed that TDS technique offers several advantages compared to semi-log analysis and type curve matching. It can be used even if some flow regimes are not observed. Direct synthesis results are accurate compared to the available core data and the software matching results. It can be used to confirm the software matching results and to give reliable reservoir characteristics when there is lack of data.

To provide a background for this special section on transaction log analysis, the following discussion proposes a definition of transaction log analysis and briefly introduces some of the issues involved in the methodology.