Archiving social survey data in Africa : an overview of African microdata curation and the role of survey data archives in data management in Africa

Includes bibliographical references (p. 124-157).This study examines current practice in the curation of social survey data in African countries and makes suggestions for future improvements in this regard. Curation of data refers to its preservation and management for reuse. Utilising survey data for the study of social phenomena other than those for which the original survey was initiated is a relatively new research approach in Africa. Thus best practice for this type of research is still being put in place by African organisations. This involves the development of optimal means of processing and storing the data for re-use. Of concern to this study is what constitutes the most effective way of managing and sharing the information garnered from these surveys as a resource for economic and social development in Africa. Social survey data refers to both the statistical information which is the final product of censuses or sample surveys, and the documentation provided with the data to facilitate its reuse. Documentation includes technical notes and questionnaires used in the survey process, as well as meta data (detailed information about the data) and reports produced concerning the final survey findings. The research looks at the history of the management of social survey data worldwide and in African countries, and the policies and processes involved in curating survey information in these countries. The comparative component of the study examines developments in this field internationally and compares these to practices on the African continent. International best practice in the field has been used to evaluate current methods of survey data archiving in African countries. The study presents strategies to ensure the optimal preservation and effective sharing of survey data among countries of the region. Strategies for the establishment of a Pan African network of data sharing organisations are suggested to support future repurposing of African census and survey data

Guide for National Planning for Setting Up New Data Services

This guide aims to assist interested actors or country teams in developing plans for establishing national data services in the social sciences. The guide helps country teams to include in their plans a mission statement, a governance structure, a description of areas of competence and infrastructure that need to be strengthened, as well as a description of future needs and necessary resources for setting up and maintaining viable data services

Data policies, data management, and the quality of academic writing

Publishing in top-ranking journals in the social sciences and international relations requires writing with clarity. Accurately described and transparent methods sections ensure high-quality academic writing. The methodology section of empirical papers should explain the exact steps taken by the authors when operationalizing concepts and testing hypotheses to facilitate replication. This also allows for monitoring quality, challenging findings, and promoting good scientific practices. The quality of methodology sections is the result of the interaction between academic cultures of data sharing, effective application of rules, and good-quality research data management (RDM). This article evaluates the impact of standards on replicability. We present an empirical analysis of a set of sixty-six articles published during the period 1984–2013 that use data from all waves of the European Values Survey. We find differences demonstrating the impact of good RDM and data policies on good scientific practice

Applications of Research Data Management at GESIS Data Archive for the Social Sciences

The chapter "Applications of Research Data Management at GESIS Data Archive for the Social Sciences" explores ways in which an archive - i.e. an organization whose work has a strong focus on preservation and dissemination of digital data - can become involved in research data management (RDM). The Data Archive looks back on a long history of working with researchers to make their data re-usable and accessible since 1960. Today it provides support for Research Data Management across the entire data lifecycle by offering a wide range of tools and services tailored to the needs of different types of stakeholders. The chapter gives an overview of selected tools and services offered in the areas of metadata and data documentation, data preparation, data publication, and long-term preservation. To illustrate how support for research data management plays out in different settings, three case studies for typical scenarios are presented: 1) The European Values Survey (EVS), a large international longitudinal survey studying basic human values across Europe. 2) The German Longitudinal Election Study (GLES), a national survey program with a comprehensive approach to gain insights into the German federal elections. 3) A data center in the health sector which decided to make data originally collected to support policy-making available to research

Studying the History of Social Science Data Archives as Knowledge Infrastructure

In this paper, we develop a brief history of Social Science Data Archives (SSDAs) and their implications for evolving scholarship on the sustainability and coordination of contemporary knowledge infrastructures.  We draw upon analyses of institutional and policy documents and interviews from active SSDAs as well as field level analyses of professional societies for staff and representatives of SSDAs.  We examine the history of SSDAs in shaping the social sciences of the latter part of the twentieth century, their strategies for remaining active and relevant through institutional and financial uncertainty, and conclude with implications for current STS scholarship in cyberinfrastructures and open data.Irish Research CouncilAlfred P. Sloan FoundationWisconsin Alumni Research FoundationASIS&T History and Foundations SIG History Fun

Deliverable 3.4: National Development Plans for Data Services in Non-CESSDA Member Countries in the ERA

This deliverable contains the second output of task 3.3 – national development plans for establishing data services in the social sciences in non-CESSDA member countries in Europe. The goal of task 3.3 of CESSDA SaW was to draw up individual national development plans for aspiring CESSDA Service Providers. In total, NDPs have been developed in 13 countries. Nine NDPs are included in this deliverable, while four are still pending approval from national authorities and/or local potential host institutions

Infrastructure services and needs for the provision of enhanced qualitative data resources

The article provides an overview of the opportunities and challenges faced by a national qualitative data service provider, and specifically, how these relate to broader infrastructural requirements, based mainly on the case of the UK. Tracing the history of the UK service Qualidata since 1994 makes it possible to pinpoint how major cultural and funding barriers have been overcome, and how new opportunities have enabled the UK service to gain a renewed lease of life. The second part of the article outlines the new UK Economic and Social Data Service, which has a specific qualitative data component built in to it. The new directions of the service and its promised deliverables are described, and suggestions made on some key developments in national infrastructure that would greatly contribute to its success. Two areas of particular significance are the establishment of more coordinated and mandatory social science datasets policies by research funders; and a nationally coordinated research methods training strategy that recognises the value of secondary analysis of qualitative data. Finally, the article provides specific information on a UK pilot project to make qualitative research data on Edwardian England available online

Open research data: Report to the Australian National Data Service (ANDS)

Main points Research data are an asset we have been building for decades, through billions of dollars of public investment in research annually. The information and communication technology (ICT) revolution presents an unprecedented opportunity to ‘leverage’ that asset. Given this, there is increasing awareness around the world that there are benefits to be gained from curating and openly sharing research data (Kvalheim and Kvamme 2014). Conservatively, we estimate that the value of data in Australia’s public research to be at least $1.9 billion and possibly up to$6 billion a year at current levels of expenditure and activity. Research data curation and sharing might be worth at least $1.8 billion and possibly up to$5.5 billion a year, of which perhaps $1.4 billion to$4.9 billion annually is yet to be realized. Hence, any policy around publicly-funded research data should aim to realise as much of this unrealised value as practicable. Aims and scope This study offers conservative estimates of the value and benefits to Australia of making publicly-funded research data freely available, and examines the role and contribution of data repositories and associated infrastructure. It also explores the policy settings required to optimise research data sharing, and thereby increase the return on public investment in research. The study’s focus is Australia’s Commonwealth-funded research and agencies. It includes research commissioned or funded by Commonwealth bodies as well as in-house research within research-oriented agencies wholly or largely funded by the Commonwealth. Government data or public sector information is a separate category of publicly-funded data – although there is some overlap at the margins (e.g. Commonwealth Government funding for Geoscience Australia). Main findings For the purposes of estimation, we explore a range of research funding and expenditure from total Australian Government funding support for research to the sum of government and higher education expenditure on research by sector of execution. The lower bound estimates are based on the labour-cost share of research funding and expenditure ($4.3 billion to$6.4 billion per annum), and upper bound estimates on total research funding and expenditure ($8.9 billion to$13.3 billion per annum)

The relationship between research data management and virtual research environments

The aim of the study was to compile a conceptual model of a Virtual Research Environment (VRE) that indicates the relationship between Research Data Management (RDM) and VREs. The outcome of this study was that VREs are ideal platforms for the management of research data. In the first part of the study, a literature review was conducted by focusing on four themes: VREs and other concepts related to VREs; VRE components and tools; RDM; and the relationship between VREs and RDM. The first theme included a discussion of definitions of concepts, approaches to VREs, their development, aims, characteristics, similarities and differences of concepts, an overview of the e-Research approaches followed in this study, as well as an overview of concepts used in this study. The second theme consisted of an overview of developments of VREs in four countries (United Kingdom, USA, The Netherlands, and Germany), an indication of the differences and similarities of these programmes, and a discussion on the concept of research lifecycles, as well as VRE components. These components were then matched with possible tools, as well as to research lifecycle stages, which led to the development of a first conceptual VRE framework. The third theme included an overview of the definitions of the concepts ‘data’ and ‘research data’, as well as RDM and related concepts, an investigation of international developments with regards to RDM, an overview of the differences and similarities of approaches followed internationally, and a discussion of RDM developments in South Africa. This was followed by a discussion of the concept ‘research data lifecycles’, their various stages, corresponding processes and the roles various stakeholders can play in each stage. The fourth theme consisted of a discussion of the relationship between research lifecycles and research data lifecycles, a discussion on the role of RDM as a component within a VRE, the management of research data by means of a VRE, as well as the presentation of a possible conceptual model for the management of research data by means of a VRE. This literature review was conducted as a background and basis for this study. In the second part of the study, the research methodology was outlined. The chosen methodology entailed a non-empirical part consisting of a literature study, and an empirical part consisting of two case studies from a South African University. The two case studies were specifically chosen because each used different methods in conducting research. The one case study used natural science oriented data and laboratory/experimental methods, and the other, human orientated data and survey instruments. The proposed conceptual model derived from the literature study was assessed through these case studies and feedback received was used to modify and/or enhance the conceptual model. The contribution of this study lies primarily in the presentation of a conceptual VRE model with distinct component layers and generic components, which can be used as technological and collaborative frameworks for the successful management of research data.Thesis (DPhil)--University of Pretoria, 2018.National Research FoundationInformation ScienceDPhilUnrestricte