Documentation and Dissemination of Indigenous Knowledge by Library Personnel in Selected Research Institutes in Nigeria

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Authors : Adebola Aderemi Adeyemo, John Oluwaseye Adebayo

Indigenous Knowledge (IK) and practices are usually unwritten; relying on oral transmission and human memory. As a result, this study investigated the documentation and dissemination of Indigenous Knowledge by library personnel at five selected research institutes in Ibadan, Nigeria.

Using the descriptive survey design, six (6) questions raised to achieve the stated objectives. Structured questionnaire and interview were used for data collection. The population comprised of professionals and para-professionals library staff at Nigeria Institute of Social and Economic Research (NISER), Institute of African Studies (IFRA), Forestry Research Institute of Nigeria (FRIN), Cocoa Research Institute of Nigeria (CRIN), and International Institute of Tropical Agriculture (IITA).

Purposive sampling method was used to select samples considering the resources to be expended and time involved for the study. Data were analyzed with the use of Statistical Package for Social Science (SPSS 16) while simple frequency count of percentage distribution was used to present the results of findings in table.

Some of the findings of the study revealed that Indigenous Knowledge documented at the research institutes were on: Agriculture; kingship system in different towns; traditional medicine; general traditional culture; as well as traditional politics and governance. In addition, Indigenous

Knowledge practices were documented with recordings and visual documentation among other methods, and these are being done by all the library personnel. Meanwhile, Indigenous Knowledge practices are being disseminated through: video, library website, print media, direct mail, public lectures, exhibitions and displays, and exchange. Certain recommendations were made based on the findings of this study.

URL : https://digitalcommons.unl.edu/libphilprac/1628/

Impact of Institutional Repositories’ on Scholarly Practices of Scientists

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Authors : Prachi Shukla, Naved Ahmad

Institutional Repositories (IRs) are established mainly to provide access to information resources which are otherwise not easily accessible in digital format. Many institutions across the world and particularly in India have successfully developed their own IRs but have not attempted to assess their importance and impact on the Users.

This study conveys the findings of the survey conducted at research centric CSIR (Council of Scientific and Industrial Research) laboratories of India to determine the scientists’ and research scholars’ preference for publishing their research materials; to measure the impact of IRs on their scholarly practices and to recommend future changes for inviting more participation in an IR.

The study deduced that ‘Peer- Review scholarly Journals’ are preferred medium for publishing research content and ‘Increase in the access to grey literature’ is the most significant impact of IR on respondents.

The findings of this research paper provide insight to the IR managers and administrators of low-deposit and low-usage repositories about the contributors’ apprehensions. The study will also help them to define and adopt policies that will eventually enhance their IRs visibility and impact.

URL : https://digitalcommons.unl.edu/libphilprac/1631/

Creating a Community of Data Champions

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Authors : Rosie Higman, Marta Teperek, Danny Kingsley

Research Data Management (RDM) presents an unusual challenge for service providers in Higher Education. There is increased awareness of the need for training in this area but the nature of the discipline-specific practices involved make it difficult to provide training across a multi-disciplinary organisation.

Whilst most UK universities now have a research data team of some description, they are often small and rarely have the resources necessary to provide targeted training to the different disciplines and research career stages that they are increasingly expected to support.

This practice paper describes the approach taken at the University of Cambridge to address this problem by creating a community of Data Champions. This collaborative initiative, working with researchers to provide training and advocacy for good RDM practice, allows for more discipline-specific training to be given, researchers to be credited for their expertise and creates an opportunity for those interested in RDM to exchange knowledge with others.

The ‘community of practice’ model has been used in many sectors, including Higher Education, to facilitate collaboration across organisational units and this initiative will adopt some of the same principles to improve communication across a decentralised institution.

The Data Champions initiative at Cambridge was launched in September 2016 and this paper reports on the early months, plans for building the community in the future and the possible risks associated with this approach to providing RDM services.

URL : Creating a Community of Data Champions

DOI : https://doi.org/10.2218/ijdc.v12i2.562

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier

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Author : Christine L. Borgman

As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property.

Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of ‘grey data’ about individuals in their daily activities of research, teaching, learning, services, and administration.

The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII.

Universities are exploiting these data for research, learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities are besieging universities with requests for access to data or for partnerships to mine them.

The privacy frontier facing research universities spans open access practices, uses and misuses of data, public records requests, cyber risk, and curating data for privacy protection.

This paper explores the competing values inherent in data stewardship and makes recommendations for practice, drawing on the pioneering work of the University of California in privacy and information security, data governance, and cyber risk.

URL : https://arxiv.org/abs/1802.02953

Evolution of the scholarly mega-journal, 2006–2017

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 Author : Bo-Christer Björk

Mega-journals are a new kind of scholarly journal made possible by electronic publishing. They are open access (OA) and funded by charges, which authors pay for the publishing services. What distinguishes mega-journals from other OA journals is, in particular, a peer review focusing only on scientific trustworthiness.

The journals can easily publish thousands of articles per year and there is no need to filter articles due to restricted slots in the publishing schedule. This study updates some earlier longitudinal studies of the evolution of mega-journals and their publication volumes.

After very rapid growth in 2010–2013, the increase in overall article volumes has slowed down. Mega-journals are also increasingly dependent for sustained growth on Chinese authors, who now contribute 25% of all articles in such journals.

There has also been an internal shift in market shares. PLOS ONE, which totally dominated mega-journal publishing in the early years, currently publishes around one-third of all articles. Scientific Reports has grown rapidly since 2014 and is now the biggest journal.

URL : Evolution of the scholarly mega-journal, 2006–2017

DOI : https://doi.org/10.7717/peerj.4357

Developing indicators on Open Access by combining evidence from diverse data sources

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Authors : Thed van Leeuwen, Ingeborg Meijer, Alfredo Yegros-Yegros, Rodrigo Costas

In the last couple of years, the role of Open Access (OA) publishing has become central in science management and research policy. In the UK and the Netherlands, national OA mandates require the scientific community to seriously consider publishing research outputs in OA forms.

At the same time, other elements of Open Science are becoming also part of the debate, thus including not only publishing research outputs but also other related aspects of the chain of scientific knowledge production such as open peer review and open data.

From a research management point of view, it is important to keep track of the progress made in the OA publishing debate. Until now, this has been quite problematic, given the fact that OA as a topic is hard to grasp by bibliometric methods, as most databases supporting bibliometric data lack exhaustive and accurate open access labelling of scientific publications.

In this study, we present a methodology that systematically creates OA labels for large sets of publications processed in the Web of Science database. The methodology is based on the combination of diverse data sources that provide evidence of publications being OA.

URL : https://arxiv.org/abs/1802.02827v1

Can your paper evade the editors axe? Towards an AI assisted peer review system

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Authors : Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Srinivasa Satya Sameer Kumar Chivukula, Georgios Tsatsaronis, Pascal Coupet, Michelle Gregory

This work is an exploratory study of how we could progress a step towards an AI assisted peer- review system. The proposed approach is an ambitious attempt to automate the Desk-Rejection phenomenon prevalent in academic peer review.

In this investigation we first attempt to decipher the possible reasons of rejection of a scientific manuscript from the editors desk. To seek a solution to those causes, we combine a flair of information extraction techniques, clustering, citation analysis to finally formulate a supervised solution to the identified problems.

The projected approach integrates two important aspects of rejection: i) a paper being rejected because of out of scope and ii) a paper rejected due to poor quality. We extract several features to quantify the quality of a paper and the degree of in-scope exploring keyword search, citation analysis, reputations of authors and affiliations, similarity with respect to accepted papers.

The features are then fed to standard machine learning based classifiers to develop an automated system. On a decent set of test data our generic approach yields promising results across 3 different journals.

The study inherently exhibits the possibility of a redefined interest of the research community on the study of rejected papers and inculcates a drive towards an automated peer review system.

URL : https://arxiv.org/abs/1802.01403