Exploring Usage Patterns of a Large-Scale Digital Library

Barifah, Maram Hassan; Landoni, Monica

doi:10.1109/jcdl.2019.00020

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…Barifah et al. explore the hidden usage patterns of a large‐scale digital library by analysing log files and classifying them by using K‐Means [26]. Pettinato et al.…”

Section: Related Workmentioning

confidence: 99%

Bayesian Network analysis of software logs for data‐driven software maintenance

2023

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Software organisations aim to develop and maintain high-quality software systems. Due to large amounts of behaviour data available, software organisations can conduct datadriven software maintenance. Indeed, software quality assurance and improvement programs have attracted many researchers' attention. Bayesian Networks (BNs) are proposed as a log analysis technique to discover poor performance indicators in a system and to explore usage patterns that usually require temporal analysis. For this, an action research study is designed and conducted to improve the software quality and the user experience of a web application using BNs as a technique to analyse software logs. To this aim, three models with BNs are created. As a result, multiple enhancement points have been identified within the application ranging from performance issues and errors to recurring user usage patterns. These enhancement points enable the creation of cards in the Scrum process of the web application, contributing to its data-driven software maintenance. Finally, the authors consider that BNs within quality-aware and data-driven software maintenance have great potential as a software log analysis technique and encourage the community to deepen its possible applications. For this, the applied methodology and a replication package are shared. K E Y W O R D SBayes methods, software maintenance, software quality | INTRODUCTIONSoftware quality management is a key activity for the maintenance of software systems. Indeed, the budget that companies invest in software quality management is estimated to increase in the next years [1]. Software systems can generate large amounts of data both from its internal state and from how it is being used. The maintenance of such systems can benefit from the analysis of the available data to get better insights of the system, thus, performing data-driven software maintenance. For instance, companies can analyse the user experiences of their software systems [2] in order to detect possible defects, such as performance downgrades or unexpected errors. To improve the user experience, it is key to understand the users' usage patterns when navigating a software system. Understanding these patterns enables companies the ability to enhance the design of their software systems [3] as well as provide personalised information depending on the user [4]. In this regard, software logs are a popular resource to monitor.Developers place Application Programming Interface calls to a logging framework (e.g., SLF4J [5] or Log4J [6]) to record events that describe the internal state of the system as it runs in production. The analysis of software logs has been proved useful in improving system comprehension [7,8], performance analysis [9, 10], finding usage patterns [11,12], and anomaly detection [13,14]. Nevertheless, this analysis is not free from its own challenges [15].Regarding software logs analysis, the introduction of Bayesian Networks (BNs) based on behaviour data to improve performance and users' experience has not been ...

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“…Barifah et al. explore the hidden usage patterns of a large‐scale digital library by analysing log files and classifying them by using K‐Means [26]. Pettinato et al.…”

Section: Related Workmentioning

confidence: 99%

Bayesian Network analysis of software logs for data‐driven software maintenance

2023

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“…Bollen and Luce (2002) analysed the logs of digital libraries to identify user preferences and the profile of the user community of a digital library. Barifah and Landoni (2019) tried to explore the hidden use patterns of a large-scale digital library by analysing the log files. A data set of 28 million records obtained from the RERO Doc DL was adopted for the study which identified three main distinct use patterns: item seekers, navigators and searchers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The usage patterns were characterized by session duration, session starting points, discovering content actions, functions used and determination session points. Barifah and Landoni (2019) concluded that the analysis of log files revealed valuable information that might assist digital library developers and designers to improve user experiences. Villen-Rueda et al (2007) studied how different types of users affect queries in the catalogue of a university library.…”

Section: Literature Reviewmentioning

confidence: 99%

Use analysis of the digital library of PhD dissertations defended at the University of Novi Sad

Paskali

Ivanović

2021

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Purpose 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). Design/methodology/approach 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. Findings 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. Practical implications 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. Originality/value 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.

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