Research data management (RDM) focuses on the organization and description of data, from its entry to the research cycle through to the dissemination and archiving of valuable results. RDM entails storage, security, preservation, compliance, quality, sharing and jurisdiction. In the academic world, RDM can support the research process by searching for relevant data, storing data, describing data and advising researchers on good RDM practice. This study focused on developing RDM services. The aim of the study was to establish the role Makerere University Library could play in developing RDM Services. A number of questions were formulated to guide the researcher in finding answers to the research questions. A literature review, based on the research sub-questions, was carried out. The review covered the concept of RDM, academic libraries and their RDM practices, various RDM services in academic libraries, RDM services that require sustainability and how current researchers, in general, manage their data. The research undertaken took a qualitative approach with a case study design. This was due to the need to gather in-depth and comprehensive views and experiences regarding RDM at Makerere University. A purposive sampling technique was used to identify researchers who are actively involved in managing research data at Makerere University. Data were collected using semi structured interviews, from eight participants; one from each college. The participants were selected because of their knowledge about RDM and semi-structured interviews were preferred due to their flexibility. An interview schedule was used as the data collection instrument. Data was transcribed into Microsoft Word for easy analysis. Findings that addressed the research question and sub-questions were presented and interpreted in chapter four and conclusions as well as recommendations were discussed in detail in chapter five of this research report. In summary it is possible to say that although researchers, from across the entire university, generate big volumes of research data it appears that researchers themselves manage, control and store their data making use of different removable devices. This is risky. So there is a need to develop RDM skills for all stakeholders. It does appear though that the researchers at Makerere University would be willing the support of RDM services if these are developed by the library. / Mini Dissertation (MIT)--University of Pretoria, 2017. / Carnegie Corporation of New York / Information Science / MIT / Unrestricted

An ACRL white paper from 2012 reported that, at that time, only a small number of academic libraries in the United States and Canada offered research data services (RDS), but many were planning to do so within the next two years (Tenopir, Birch, and Allard, 2012). By 2013, 74% of the Association of Research Libraries (ARL) survey respondents offered RDS and an additional 23% were planning to do so (Fearon, Gunia, Pralle, Lake, and Sallans, 2013). The academic libraries recognize that the landscape of services changes quickly and that they need to support the changing needs of research and instruction. In their efforts to implement RDS, libraries often respond to pressures originating outside the library, such as national or funder mandates for data management planning and data sharing. To provide effective support for researchers and instructors, though, libraries must be proactive and develop new services that look forward and yet accommodate the existing human, technological, and intellectual capital accumulated over the decades. Setting the stage for data curation in libraries means to create visionary approaches that supersede institutional differences while still accommodating diversity in implementation. How do academic libraries work towards that? This chapter will combine an historical overview of RDS thinking and implementations based on the existing literature with an empirical analysis of ARL libraries’ current RDS goals and activities. The latter is based on the study we conducted in 2015 that included a content analysis of North American research library web pages and interviews of library leaders and administrators of ARL libraries. Using historical and our own data, we will synthesize the current state of RDS implementation across ARL libraries. Further, we will examine the models of research data management maturity (see, for example, Qin, Crowston and Flynn, 2014) and discuss how such models compare to our own three-level classification of services and activities offered at libraries - basic, intermediate, and advanced. Our analysis will conclude with a set of recommendations for next steps, i.e., actions and resources that a library might consider to expand their RDS to the next maturity level. References Fearon, D. Jr., Gunia, B., Pralle, B.E., Lake, S., Sallans, A.L. (2013). Research data management services. (ARL Spec Kit 334). Washington, D.C.: ARL. Retrieved from: http://publications.arl.org/Research-Data-Management-Services-SPEC-Kit-334/ Tenopir, C., Birch, B., & Allard, S. (2012). Academic libraries and research data services: Current practices and plans for the future. ACRL. Retrieved from http://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/whitepapers/Tenopir_Birch_Allard.pdf Qin, J., Crowston, K., & Flynn, C. (2014). 1.1 Commitment to Perform. A Capability Maturity Model for Research Data Management. wiki. Retrieved http://rdm.ischool.syr.edu/xwiki/bin/view/CMM+for+RDM/WebHome

This study investigated the role of academic libraries in implementing research data services, UKZN being the case study. The objectives of the study were to identify the need for research data services among UKZN researchers, to identify the major challenges associated with introducing research data services at UKZN, and to determine the possibility of implementing research data services at UKZN Libraries. The Data Curation Centre Lifecycle model was adopted as a framework for the study as it manages to connect the different stages of research data management. The study took a mixed methods approach of which interviews and a survey were used. A purposive sample was used to select library staff and random sample was drawn from 1341 UKZN academics. From a sample of 1341, 299 was the minimum size recommended by the Raosoft sample size calculator for a 5% margin of error and 95% confidence level. For quantitative analysis, an online questionnaire was administered using Google Forms. A series of questions were formulated for guidance in obtaining answers to the study objectives. Google Forms was used for the analysis while figures and tables were created using Microsoft Excel. Interviews from the library staff were recorded and data from interviews was transcribed into Microsoft Word. The study revealed that UKZN Libraries are still struggling with RDM policy development. The findings of the study revealed that researchers who responded to the study showed a lack of RDM awareness while library staff showed a moderate level of awareness. The study revealed that researchers at UKZN work with different types of data and they use different storage options such as removable storage devices, computer hard drives and cloud services. Although a few researchers have developed data management plans at UKZN, they have not done so because they were mandated by the institution - UKZN has not yet developed DMPs and library staff are not aware which funders require DMPs. The researchers who responded to the study showed interest in different trainings such as, training on data storage, development of DMPs and metadata creation. The library staff were more eager to provide data storage, data archiving and sharing mainly because of the existence of the UKZN data repository (Yabelana). Study recommendations are based on the analysed data. One of the recommendations was that UKZN Libraries should assume a role of being an advisor and trainer for research data services at UKZN.

Research Data Management (RDM) has received a lot of attention recently. In South Africa, the importance of RDM has amplified since the release of the National Research Foundation‟s (NRF) open access statement. According to the statement, researchers who receive funding from the NRF must deposit their research output in an open access (OA) repository. In addition, the data supporting the research should be deposited in an accredited OA repository with a Digital Object Identifier (DOI) for future citations (NRF, 2015: online). The mandate, along with other drivers such as research data re-use, increased impact and validation of research findings has forced institutions to investigate the possibility of offering RDM services in their institutions (Ashley, 2012). It is expected that libraries and Library and Information Science (LIS) professionals will initiate and support RDM in their institutions. LIS professionals will need to upgrade or obtain new skills and knowledge to fulfil their new roles and responsibilities. Various training opportunities are available to interested professionals to improve their knowledge and skills related to RDM. These can be as simple as a workshop or as complex as a university degree. The objective of this research was to identify and evaluate a RDM training intervention to determine whether the training intervention could enhance the knowledge and skills of LIS professionals in South African (SA) Higher Education Institutions (HEIs). An embedded research design was used to investigate whether an RDM workshop, hosted by the Network for Data and Information Curation Communities (NeDICC), could enhance the LIS professional‟s (participants) perception of their RDM understanding, knowledge and skills. The research found that the RDM workshop was highly successful in enhancing the participant‟s perception of their RDM understanding and knowledge. The RDM workshop was less successful in enhancing the participant‟s perception of their RDM skills. It was recommended that LIS professionals (1) take advantage of the online RDM training material available to enhance their understanding and knowledge of RDM; (2) attend face-to-face training interventions to enhance or develop their RDM skills and (3) enrol in university level educational programmes to gain a qualification in RDM if they qualify. It was also recommended that institutions that provide RDM training should focus on specific aspects of RDM instead of offering a general overview. This research can be used to inspire larger studies or studies that compare two or more RDM training interventions. / Mini Dissertation (MIT)--University of Pretoria, 2016. / Carnegie Corporation of New York / University of Pretoria / Information Science / MIT / Unrestricted

This dissertation presents the first study of data preservation and research reproducibility in data science at the Large Hadron Collider at CERN. In particular, provenance capture of the experimental data and the reproducibility of physics analyses at the LHCb experiment were studied. First, the preservation of the software and hardware dependencies of the LHCb experimental data and simulations was investigated. It was found that the links between the data processing information and the datasets themselves were obscure. In order to document these dependencies, a graph database was designed and implemented. The nodes in the graph represent the data with their processing information, software and computational environment, whilst the edges represent their dependence on the other nodes. The database provides a central place to preserve information that was previously scattered across the LHCb computing infrastructure. Using the developed database, a methodology to recreate the LHCb computational environment and to execute the data processing on the cloud was implemented with the use of virtual containers. It was found that the produced physics events were identical to the official LHCb data, meaning that the system can aid in data preservation. Furthermore, the developed method can be used for outreach purposes, providing a streamlined way for a person external to CERN to process and analyse the LHCb data. Following this, the reproducibility of data analyses was studied. A data provenance tracking service was implemented within the LHCb software framework \textsc{Gaudi}. The service allows analysts to capture their data processing configurations that can be used to reproduce a dataset within the dataset itself. Furthermore, to assess the current status of the reproducibility of LHCb physics analyses, the major parts of an analysis were reproduced by following methods described in publicly and internally available documentation. This study allowed the identification of barriers to reproducibility and specific points where documentation is lacking. With this knowledge, one can specifically target areas that need improvement and encourage practices that would improve reproducibility in the future. Finally, contributions were made to the CERN Analysis Preservation portal, which is a general knowledge preservation framework developed at CERN to be used across all the LHC experiments. In particular, the functionality to preserve source code from git repositories and Docker images in one central location was implemented.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Operations Research." Includes bibliographical references (p. 95-103).

Conferencia realizado del 12 al 14 de setiembre en Lima, Peru del 2012 en el marco del 15º Simposio Internacional de Tesis y Disertaciones Electrónicas (ETD 2012). Evento aupiciado por la Universidad Nacional Mayor de San Marcos (UNMSM) y la Universidad Peruana de Ciencias Aplicadas (UPC). / During the ETD-conferences in the past we discussed the pros and cons of electronic thesis and dissertations. We described the requirements for maintaining ETD’s in repositories and how we could motivate authors to make their work open access and so that it will be available to interested people all over the world. A lot of repositories are available and many countries have well prepared ETD programs. In Germany all universities have an ETD-repository and we focus more and more on how to improve the visibility and attractiveness of these collections. The most important element is the relevance for the scholarly process. Increasingly a repository should be not only a collection, but a virtual environment—that is, an instrument to support scholars during their work. There are many possibilities, but an especially important point is the handling of research data. Research data are the starting point for every research project on the one hand, and on the other they are the result of any research. In the digital age we can not only store the data but also share them. This is why in recent years we speak not only about open access to scholarly publications but about open access to research data. In my paper I intend to describe to the present situation (at least in Germany) for using research data, the drivers and barriers in sharing research data and the consequences for the operators of repositories. In order to go more into the details, I will use results from the EU funded projects “SOAP – Study of Open Access Publishing” and “ODE – Opportunities Data Exchange”.

This thesis deals with concepts and solutions in the field of data management in everyday scientific life for image data from microscopy. The focus of the formulated requirements has so far been on published data, which represent only a small subset of the data generated in the scientific process. More and more, everyday research data are moving into the focus of the principles for the management of research data that were formulated early on (FAIR-principles). The adequate management of this mostly multimodal data is a real challenge in terms of its heterogeneity and scope. There is a lack of standardised and established workflows and also the software solutions available so far do not adequately reflect the special requirements of this area. However, the success of any data management process depends heavily on the degree of integration into the daily work routine. Data management must, as far as possible, fit seamlessly into this process. Microscopy data in the scientific process is embedded in pre-processing, which consists of preparatory laboratory work and the analytical evaluation of the microscopy data. In terms of volume, the image data often form the largest part of data generated within this entire research process. In this paper, we focus on concepts and techniques related to the handling and description of this image data and address the necessary basics. The aim is to improve the embedding of the existing data management solution for image data (OMERO) into the everyday scientific work. For this purpose, two independent software extensions for OMERO were implemented within the framework of this thesis: OpenLink and MDEmic. OpenLink simplifies the access to the data stored in the integrated repository in order to feed them into established workflows for further evaluations and enables not only the internal but also the external exchange of data without weakening the advantages of the data repository. The focus of the second implemented software solution, MDEmic, is on the capturing of relevant metadata for microscopy. Through the extended metadata collection, a corresponding linking of the multimodal data by means of a unique description and the corresponding semantic background is aimed at. The configurability of MDEmic is designed to address the currently very dynamic development of underlying concepts and formats. The main goal of MDEmic is to minimise the workload and to automate processes. This provides the scientist with a tool to handle this complex and extensive task of metadata acquisition for microscopic data in a simple way. With the help of the software, semantic and syntactic standardisation can take place without the scientist having to deal with the technical concepts. The generated metadata descriptions are automatically integrated into the image repository and, at the same time, can be transferred by the scientists into formats that are needed when publishing the data.

We asked whether the design of a Science Data Repository (SDR) can influence data sharing behaviour in small scientific collaborations. We hypothesised that an SDR can influence data-sharing behaviour when its design considers the context of data-sharing. We proposed an alternative approach to those documented in the literature, employing a combination of socio-technical empirical and analytical methods for context capturing, and choice architecture for context incorporation. To evaluate the approach we applied it to design features in a Scientific Data Repository for a population of small scientific collaborations within the Life Sciences. The application of this thesis' approach consisted of an exploratory case study, a review of factors associated with data sharing, the definition of design claims, and implementation of a set of design features. We collected data using interviews with members of the collaborations and designers of the SDR; as well as obtaining the data-logs from the collaborations' SDR. We evaluated the resulting design features using an asynchronous web experiment. We found that using the empirical approach to context capturing we are able to effectively identify factors associated with data sharing in the small scientific collaborations. Moreover, we identified a number of limitations on the application of the analytical approach to context capturing. Furthermore, we found that the Choice Architecture based procedure for context incorporation can define effective design features in Science Data Repositories. In this work, we show that we can facilitate data-sharing by incorporating context into the design of a Science Data Repository, and identified a set of restrictions to use our approach. The approach proposed in this thesis can be used by practitioners wishing to improve data sharing in an SDR. Contributions, such as the survey of factors associated with data sharing behaviour, can be used by researchers to understand the problems associated with data sharing in small scientific collaborations.

Research data is essential to scholarship. The value of research data and its management has been increasingly recognized by policy makers and higher education institutions. A deep understanding of disciplinary practices is vital to develop culturally-sensitive policy, tools and services for successful data management. Previous research has shown that data practices vary across sub-fields and disciplines. However, much less is known about how disciplinary cultures shape data practices. There is a need to theorise research data practices based on empirical evidence in order to inform policy, tools and services. The aim of the thesis is to examine the interrelation between data practices and disciplinary cultures within geography. Geography is well-established and multidisciplinary, consisting of elements from the sciences, social sciences and humanities. By examining a single discipline this thesis develops a theoretical understanding of research data practices at a finer level of granularity than would be achieved by looking at broad disciplinary groupings such as the physical and social sciences. Data collection and analysis consisted of two phases. Phase one was exploratory, including an analysis of geography department websites and researcher web profiles and a bibliometric study of collaboration patterns based on co-authorship. Phase one aimed to understand the disciplinary characteristics of geography in preparation for Phase two. The second phase consisted of a series of 23 semi-structured interviews with researchers in geography, which aimed to understand researchers data practices and their attitudes toward data sharing within the context of the sub-discipline(s) they inhabited. The findings of the thesis show that there are contrasting intellectual, social and data differences between physical and human geography. For example, intellectually, these two branches of geography differ in terms of their research objects and methods; socially, they differ in terms of the scale of their collaborative activities and the motivations to collaborate; furthermore, the nature of data, how data is collected and data sharing practices are also different between physical and human geography. The thesis concludes that differences in the notion of data and data sharing practices are grounded in disciplinary characteristics. The thesis develops a new three-dimensional framework to better understand the notion of data from a disciplinary perspective. The three dimensions are (1) physical form, (2) intellectual content and (3) social construction. Furthermore, Becher and Trowler s (2001) disciplinary taxonomy i.e. hard-soft/pure-applied, and the concepts urban-rural ways of life and convergent-divergent communities, is shown to be useful to explain the diverse data sharing practices of geographers. The thesis demonstrates the usefulness of applying disciplinary theories to the sphere of research data management.