The OAPEN Library and the origin of downloads – libraries & academic institutions – OAPEN – supporting the transition to open access for academic books

On a regular basis, we look at the download data of the OAPEN Library and where it comes from. While examining the data from January to August 2021, we focused on the usage originating from libraries and academic institutions. Happily, we found that more than 1,100 academic institutions and libraries have used the OAPEN Library.

Of course, we do not actively track individual users. Instead we use a more general approach: we look at the website from which the download from the OAPEN Library originated. How does that work? For instance, when someone in the library of the University of Leipzig clicks on the download link of a book in the OAPEN library, two things happen: first, the book is directly available on the computer that person is working on, and second, the OAPEN server notes the ‘return address’: https://katalog.ub.uni-leipzig.de/. We have no way of knowing who the person is that started the download, we just know the request originated from the Leipzig University Library. Furthermore, some organisations choose to suppress sending their ‘return address’, making them anonymous.

What is helpful to us, is the fact that aggregators such as ExLibris, EBSCO or SerialSolutions use a specific return address. Examples are “west-sydney-primo.hosted.exlibrisgroup.com” – pointing to the library of the Western City University – or “sfx.unibo.it”– coming from the library of the Università di Bologna. And in this way, many academic libraries can also be identified from their web address. Some academic institutions only display their ‘general’ address.

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The OAPEN Library and the origin of downloads – libraries & academic institutions

On a regular basis, we look at the download data of the OAPEN Library and where it comes from. While examining the data from January to August 2021, we focused on the usage originating from libraries and academic institutions. Happily, we found that more than 1,100 academic institutions and libraries have used the OAPEN Library.

Of course, we do not actively track individual users. Instead we use a more general approach: we look at the website from which the download from the OAPEN Library originated. How does that work? For instance, when someone in the library of the University of Leipzig clicks on the download link of a book in the OAPEN library, two things happen: first, the book is directly available on the computer that person is working on, and second, the OAPEN server notes the ‘return address’: https://katalog.ub.uni-leipzig.de/. We have no way of knowing who the person is that started the download, we just know the request originated from the Leipzig University Library. Furthermore, some organisations choose to suppress sending their ‘return address’, making them anonymous.

Next generation Open Access analytics: A case study – IOS Press

Abstract:  A critical component in the development of sustainable funding models for Open Access (OA) is the ability to communicate impact in ways that are meaningful to a diverse range of internal and external stakeholders, including institutional partners, funders, and authors. While traditional paywall publishers can take advantage of industry standard COUNTER reports to communicate usage to subscribing libraries, no similar standard exists for OA content. Instead, many organizations are stuck with proxy metrics like sessions and page views that struggle to discriminate between robotic access and genuine engagement.

This paper presents the results of an innovative project that builds on existing COUNTER metrics to develop more flexible reporting. Reporting goals include surfacing third party engagement with OA content, the use of graphical report formats to improve accessibility, the ability to assemble custom data dashboards, and configurations that support the variant needs of diverse stakeholders. We’ll be sharing our understanding of who the stakeholders are, their differing needs for analytics, feedback on the reports shared, lessons learned, and areas for future research in this evolving area.

IRUS-US: Institutional Repository Usage Statistics Service

“LYRASIS is partnering with Jisc to form and administer a new IRUS-US community of users. Institutions participating in IRUS-US install the IRUS tracker, allowing Jisc to collects raw download data for all item types and processes those raw data into COUNTER-conformant statistics. Those statistics are aggregated in open access statistical reports, allowing institutions to: share usage information with individual researchers; share usage information with administration; compare usage information with peer institutions; and use usage information to identify national trends.

IRUS-US functions as a small piece of code that is added to IR, enabling a ‘tracker protocol’ that allows Jisc to collect the raw data. Current compatible IR softwares include Dspace, Eprints, Fedora, Figshare, Haplo, Pure portal, Worktribe, Equella and Esploro. Any institution using a software not listed above should contact LYRASIS and indicate their interest, and we will do our best to encourage the software creators to add IRUS tracker functionality into their software capabilities.”

IRUS-US: Institutional Repository Usage Statistics Service

“LYRASIS is partnering with Jisc to form and administer a new IRUS-US community of users. Institutions participating in IRUS-US install the IRUS tracker, allowing Jisc to collects raw download data for all item types and processes those raw data into COUNTER-conformant statistics. Those statistics are aggregated in open access statistical reports, allowing institutions to: share usage information with individual researchers; share usage information with administration; compare usage information with peer institutions; and use usage information to identify national trends.

IRUS-US functions as a small piece of code that is added to IR, enabling a ‘tracker protocol’ that allows Jisc to collect the raw data. Current compatible IR softwares include Dspace, Eprints, Fedora, Figshare, Haplo, Pure portal, Worktribe, Equella and Esploro. Any institution using a software not listed above should contact LYRASIS and indicate their interest, and we will do our best to encourage the software creators to add IRUS tracker functionality into their software capabilities.”

Findings on COVID-19 Detailed by Investigators at Munzur University (Academicians’ Awareness, Attitude, and Use of Open Access During the Covid-19 Pandemic). – Document – Gale Academic OneFile

“A new study on Coronavirus – COVID-19 is now available. According to news reporting from Tunceli, Turkey, by NewsRx journalists, research stated, “The aim of this research is to reveal academics’ awareness, attitude, and use of open access. In line with the research purpose, the survey research design is adopted.”

The news correspondents obtained a quote from the research from Munzur University, “This research consists 151 academics from 12 basic research areas; eight of them being Professor Dr, 17 being Associate Professor Dr, 49 being Doctor Lecturer, and 77 being Research Assistant or Lecturer. A questionnaire consisting of 19 open access and five demographic information questions was used for the data collection tool. The research results show that 75% of the academics have open access awareness and that their awareness is generally created by information that they obtain through the Internet and their friends. In addition, most of the academics indicate that their awareness of open access has increased during the pandemic period.”…”

Dryad Data — Repository Analytics and Metrics Portal (RAMP) 2020 data

“The Repository Analytics and Metrics Portal (RAMP) is a web service that aggregates use and performance use data of institutional repositories. The data are a subset of data from RAMP, the Repository Analytics and Metrics Portal (http://rampanalytics.org), consisting of data from all participating repositories for the calendar year 2020. For a description of the data collection, processing, and output methods, please see the “methods” section below….”

Repository Analytics and Metrics Portal – Web analytics for institutional repositories

“The Repository Analytics and Metrics Portal (RAMP) tracks repository items that have surfaced in search engine results pages (SERP) from any Google property. RAMP does this by aggregating Google Search Console (GSC) data from all registered repositories.

RAMP data are collected from GSC in two separate sets: page-click data and country-device data. The page-click data include the handle (aka URL) of every item that appeared in SERP. This dataset creates significant possibilities for additional research if the metadata of those items were mined. RAMP data are as free of robot traffic as possible and they contain no personally identifiable information.

RAMP data include the following metrics:

Impressions – number of times an item appears in SERP
Position – location of the item in SERP
Clicks – number times an item URL is clicked
Click-Through Ratios – number of clicks divided by the number of impressions
Date – date of the search
Device – device used for the search
Country – country from which the search originated….”

Public draft: OA eBook Usage Data Analytics and Reporting Use-cases by Stakeholder. Feedback invited through July 10, 2021

Publishers, libraries, and a diverse array of scholarly communications platforms and services generate information about how OA books are accessed online. Since its launch in 2015, the OA eBook Usage Data Trust (@OAEBU_project) effort has brought together these thought leaders to document the barriers facing OA eBook usage analytics. To start addressing these challenges and to understand the role of a usage data trust, the effort has spent the last year studying and documenting the usage data ecosystem. Interview-based research led to the documentation of the OA book data supply chain, which maps related metadata and usage data standards and workflows. Dozens worldwide have engaged in human-centered design workshops and communities of practice that went virtual during 2020. Together these communities revealed how OA book publishers, platforms, and libraries are looking beyond their need to provide usage and impact reports. Workshop findings are now documented within use-cases that list the queries and activities where usage data analytics can help scholars and organizations to be more effective and strategic. Public comment is invited for the OA eBook Usage Data Analytics and Reporting Use Cases Report through July 10, 2021.

Recognition and rewards – Open Science – Universiteit Utrecht

“Open science means action. And the way we offer recognition and reward to academics and university staff is key in bringing about the transition that Utrecht University aims for. Over the course of the past year the working group on Recognition and Rewards, part of the Open Science Programme, has reflected and thoroughly debated a novel approach to ensuring that we offer room for everyone’s talent, resulting in a new vision (pdf)….

In the current system, researchers and their research are judged by journal impact factors, publisher brands and H-indices, and not by actual quality, real use, real impact and openness characteristics….

Under those circumstances, at best open science practices are seen as posing an additional burden without rewards. At worst, they are seen as actively damaging chances of future funding and promotion & tenure. Early career researchers are perhaps the most dependent on traditional evaluation culture for career progression, a culture held in place by established researchers, as well as by institutional, national and international policies, including funder mandates….”

 

 

Utrecht University Recognition and Rewards Vision

“By embracing Open Science as one of its five core principles1, Utrecht University aims to accelerate and improve science and scholarship and its societal impact. Open science calls for a full commitment to openness, based on a comprehensive vision regarding the relationship with society. This ongoing transition to Open Science requires us to reconsider the way in which we recognize and reward members of the academic community. It should value teamwork over individualism and calls for an open academic culture that promotes accountability, reproducibility, integrity and transparency, and where sharing (open access, FAIR data and software) and public engagement are normal daily practice. In this transition we closely align ourselves with the national VSNU program as well as developments on the international level….”

Data tracking in research: aggregation and use or sale of usage data by academic publishers

“This briefing paper issued by the Committee on Scientific Library Services and Information Systems (AWBI) of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) on the subject of data tracking in digital research resources describes options for the digital tracking of research activities. It outlines how academic publishers are becoming data analytics specialists, indicates the consequences for research and its institutions, and identifies the types of data mining that are being used. As such, it primarily serves to present contemporary practices with a view to stimulating discussion so that positions can be adopted regarding the consequences of these practices for the academic community. It is aimed at all stakeholders in the research landscape….

Potentially, research tracking of this kind can fundamentally contradict academic freedom and informational self-determination. It can endanger scientists and hinder the freedom of competition in the field of information provision. For this reason, scholars and academic institutions must become aware of the problem and clarify the legal, technical and ethical framework conditions of their information supply – not least so as to avoid involuntarily violating applicable law, but also to ensure that academics are appropriately informed and protected. AWBI’s aim in issuing this briefing paper is to encourage a broad debate within the academic community – at the level of academic decision-makers, among academics, and within information infrastructure institutions – so as to reflect on the practice of tracking, its legality, the measures required for compliance with data protection and the consequences of the aggregation of usage data, thereby enabling such measures to be adopted. The collection of data on research and research activity can be useful as long as it follows clear-cut, transparent guidelines, minimises risks to individual researchers and ensures that academic organisations are able to use such data if not have control over it.” 

Reporting Global Usage and Usage of Open Content Not Attributed to Institutions

“The COUNTER Code of Practice currently states about the Institution_Name in the report header that ‘For OA publishers and repositories, where it is not possible to identify usage by individual institutions, the usage should be attributed to “The World”’ (Section 3.2.1, Table 3.f). When this rule was added the focus was on fully Open Access publishers, and the expectation – which obviously was wrong and has caused some confusion – was that the fully OA publishers would not try to attribute usage to institutions. So, a report to “The World” was intended to include all global usage, whether attributed to institutions or not.

This document shows how usage could be reported to “The World” and how the global usage could be broken down and filtered.

Please note, that these reports would NOT be a mandatory requirement. Those content providers that wished to use them, could do so.

We are seeking your thoughts about how useful these reports might be, and more specifically on some of the technical details. Please provide your feedback at https://www.surveymonkey.co.uk/r/3CQZVH2  The survey questions are included at the end of this document, so that you can discuss them with colleagues before submitting your responses online….”

Science as a Public Good: Public Use and Funding of Science

Abstract:  Knowledge of how science is consumed in public domains is essential for a deeper understanding of the role of science in human society. While science is heavily supported by public funding, common depictions suggest that scientific research remains an isolated or ‘ivory tower’ activity, with weak connectivity to public use, little relationship between the quality of research and its public use, and little correspondence between the funding of science and its public use. This paper introduces a measurement framework to examine public good features of science, allowing us to study public uses of science, the public funding of science, and how use and funding relate. Specifically, we integrate five large-scale datasets that link scientific publications from all scientific fields to their upstream funding support and downstream public uses across three public domains – government documents, the news media, and marketplace invention. We find that the public uses of science are extremely diverse, with different public domains drawing distinctively across scientific fields. Yet amidst these differences, we find key forms of alignment in the interface between science and society. First, despite concerns that the public does not engage high-quality science, we find universal alignment, in each scientific field and public domain, between what the public consumes and what is highly impactful within science. Second, despite myriad factors underpinning the public funding of science, the resulting allocation across fields presents a striking alignment with the field’s collective public use. Overall, public uses of science present a rich landscape of specialized consumption, yet collectively science and society interface with remarkable, quantifiable alignment between scientific use, public use, and funding.

 

Open access book usage data – how close is COUNTER to the other kind?

Abstract:  In April 2020, the OAPEN Library moved to a new platform, based on DSpace 6. During the same period, IRUS-UK started working on the deployment of Release 5 of the COUNTER Code of Practice (R5). This is, therefore, a good moment to compare two widely used usage metrics – R5 and Google Analytics (GA). This article discusses the download data of close to 11,000 books and chapters from the OAPEN Library, from the period 15 April 2020 to 31 July 2020. When a book or chapter is downloaded, it is logged by GA and at the same time a signal is sent to IRUS-UK. This results in two datasets: the monthly downloads measured in GA and the usage reported by R5, also clustered by month. The number of downloads reported by GA is considerably larger than R5. The total number of downloads in GA for the period is over 3.6 million. In contrast, the amount reported by R5 is 1.5 million, around 400,000 downloads per month. Contrasting R5 and GA data on a country-by-country basis shows significant differences. GA lists more than five times the number of downloads for several countries, although the totals for other countries are about the same. When looking at individual tiles, of the 500 highest ranked titles in GA that are also part of the 1,000 highest ranked titles in R5, only 6% of the titles are relatively close together. The choice of metric service has considerable consequences on what is reported. Thus, drawing conclusions about the results should be done with care. One metric is not better than the other, but we should be open about the choices made. After all, open access book metrics are complicated, and we can only benefit from clarity.