Challenges and opportunities in the evolving digital preservation landscape: reflections from Portico

Authors: Kate Wittenberg, Sarah Glasser, Amy Kirchhoff, Sheila Morrissey, Stephanie Orphan

There has been tremendous growth in the amount of digital content created by libraries, publishers, cultural institutions and the general public. While there are great benefits to having content available in digital form, digital objects can be extremely short-lived unless proper attention is paid to preservation.

Reflecting on our experience with the digital preservation service Portico, we provide background on Portico’s history and evolving practice of sustainable preservation of the digital artifacts of scholarly communications.

We also provide an overview of the digital preservation landscape as we see it now, with some thoughts on current requirements for preservation, and thoughts on the opportunities and challenges that lie ahead.

URL : Challenges and opportunities in the evolving digital preservation landscape: reflections from Portico

DOI : http://doi.org/10.1629/uksg.421

Exploring the feasibility of applying data mining for library reference service improvement : a case study of Turku Main Library

Author : Ming Zhan

Data mining, as a heatedly discussed term, has been studied in various fields. Its possibilities in refining the decision-making process, realizing potential patterns and creating valuable knowledge have won attention of scholars and practitioners. However, there are less studies intending to combine data mining and libraries where data generation occurs all the time.

Therefore, this thesis plans to fill such a gap. Meanwhile, potential opportunities created by data mining are explored to enhance one of the most important elements of libraries: reference service. In order to thoroughly demonstrate the feasibility and applicability of data mining, literature is reviewed to establish a critical understanding of data mining in libraries and attain the current status of library reference service.

The result of the literature review indicates that free online data resources other than data generated on social media are rarely considered to be applied in current library data mining mandates. Therefore, the result of the literature review motivates the presented study to utilize online free resources. Furthermore, the natural match between data mining and libraries is established.

The natural match is explained by emphasizing the data richness reality and considering data mining as one kind of knowledge, an easy choice for libraries, and a wise method to overcome reference service challenges. The natural match, especially the aspect that data mining could be helpful for library reference service, lays the main theoretical foundation for the empirical work in this study.

Turku Main Library was selected as the case to answer the research question: whether data mining is feasible and applicable for reference service improvement. In this case, the daily visit from 2009 to 2015 in Turku Main Library is considered as the resource for data mining.

In addition, corresponding weather conditions are collected from Weather Underground, which is totally free online. Before officially being analyzed, the collected dataset is cleansed and preprocessed in order to ensure the quality of data mining.

Multiple regression analysis is employed to mine the final dataset. Hourly visits are the independent variable and weather conditions, Discomfort Index and seven days in a week are dependent variables. In the end, four models in different seasons are established to predict visiting situations in each season.

Patterns are realized in different seasons and implications are created based on the discovered patterns. In addition, library-climate points are generated by a clustering method, which simplifies the process for librarians using weather data to forecast library visiting situation. Then the data mining result is interpreted from the perspective of improving reference service.

After this data mining work, the result of the case study is presented to librarians so as to collect professional opinions regarding the possibility of employing data mining to improve reference services. In the end, positive opinions are collected, which implies that it is feasible to utilizing data mining as a tool to enhance library reference service.

URL : http://www.doria.fi/handle/10024/124215

Learning Analytics and the Academic Library: Professional Ethics Commitments at a Crossroads

Authors : Kyle M.L. Jones, Dorothea Salo

In this paper, the authors address learning analytics and the ways academic libraries are beginning to participate in wider institutional learning analytics initiatives. Since there are moral issues associated with learning analytics, the authors consider how data mining practices run counter to ethical principles in the American Library Association’s “Code of Ethics.”

Specifically, the authors address how learning analytics implicates professional commitments to promote intellectual freedom; protect patron privacy and confidentiality; and balance intellectual property interests between library users, their institution, and content creators and vendors.

The authors recommend that librarians should embed their ethical positions in technological designs, practices, and governance mechanisms.

URL : Learning Analytics and the Academic Library: Professional Ethics Commitments at a Crossroads

Alternative location : http://crl.acrl.org/index.php/crl/article/view/16603

The legal and policy framework for scientific data sharing, mining and reuse

Author : Mélanie Dulong de Rosnay

Text and Data Mining, the automatic processing of large amounts of scientific articles and datasets, is an essential practice for contemporary researchers. Some publishers are challenging it as a lawful activity and the topic is being discussed during European copyright law reform process.

In order to better understand the underlying debate and contribute to the policy discussion, this article first examines the legal status of data access and reuse and licensing policies. It then presents available options supporting the exercise of Text and Data Mining: publication under open licenses, open access legislations and a recognition of the legitimacy of the activity.

For that purpose, the paper analyses the scientific rational for sharing and its legal and technical challenges and opportunities. In particular, it surveys existing open access and open data legislations and discusses implementation in European and Latin America jurisdictions.

Framing Text and Data mining as an exception to copyright could be problematic as it de facto denies that this activity is part of a positive right to read and should not require additional permission nor licensing.

It is crucial in licenses and legislations to provide a correct definition of what is Open Access, and to address the question of pre-existing copyright agreements. Also, providing implementation means and technical support is key. Otherwise, legislations could remain declarations of good principles if repositories are acting as empty shells.

URL ; https://books.openedition.org/editionsmsh/9082

Big data et bibliothèques : traitement et analyse informatiques des collections numériques

Cette étude s’attache à présenter sous quels aspects les collections numériques des bibliothèques relèvent des problématiques propres aux données massives, et en quoi les techniques de fouille de données (text and data mining) représentent désormais une nécessité pour l’appropriation par les chercheurs des résultats de la littérature scientifique.

Ce travail, qui met au centre de son propos les techniques de fouille de données comme moyens de maîtriser la masse documentaire, identifie trois problématiques distinctes concernant les bibliothèques numériques et ces dispositifs de lecture algorithmiques : sont ainsi abordées successivement les démarches à mettre en oeuvre pour aider les chercheurs à faire usage de ces nouvelles méthodes de lecture, puis l’emploi de techniques de fouille de données sur les collections pour constituer de nouvelles formes d’instruments de recherche, et enfin l’usage de la fouille pour assister le traitement documentaire.

L’étude se conclut sur le détail des questions juridiques soulevées actuellement par la fouille de données, en rapport avec le droit de la propriété intellectuelle.

URL : Big data et bibliothèques : traitement et analyse informatiques des collections numériques

Alternative location : http://www.enssib.fr/bibliotheque-numerique/notices/66017-big-data-et-bibliotheques-traitement-et-analyse-informatiques-des-collections-numeriques

Data Policy Recommendations for Biodiversity Data. EU BON Project Report

There is a strong need for a comprehensive, coherent, and consistent data policy in Europe to increase interoperability of data and to make its reuse both easy and legal. Available single recommendations/guidelines on different topics need to be processed, structured, and unified. Within the context of the EU BON project, a team from the EU BON partners from Museum für Naturkunde Berlin, Plazi, and Pensoft has prepared this report to be used as a part of the Data Publishing Guidelines and Recommendations in the EU BON Biodiversity Portal.

The document deals with the issues: (i) Mobilizing biodiversity data, (ii) Removing legal obstacles, (iii) Changing attitudes, (iv) Data policy recommendations and is addressed to legislators, researchers, research institutions, data aggregators, funders, and publishers.

URL : Data Policy Recommendations for Biodiversity Data. EU BON Project Report

DOI : http://dx.doi.org/10.3897/rio.2.e8458

Is Europe Falling Behind in Data Mining? Copyright’s Impact on Data Mining in Academic Research

“This empirical paper discusses how copyright affects data mining (DM) by academic researchers. Based on bibliometric data, we show that where DM for academic research requires the express consent of rights holders: (1) DM makes up a significantly lower share of total research output; and (2) stronger rule-of-law is associated with less DM research. To our knowledge, this is the first time that an empirical study bears out a significant negative association between copyright protection and innovation.”

URL : http://dx.doi.org/10.2139/ssrn.2608513