Access To Research Data Research Articles

Perception of Researchers & Academicians of Parul University towards Research Data Management System & Role of Library

Research data management is a system that helps in archiving and retrieving of research data to reuse and preserving them for long term use. Many universities in developed countries have already started providing RDM services to their researchers and academicians. In India, it is still in the initial stage. The purpose of the present study is to investigate the perceptions of researchers and academicians of Parul University on research data management and research data sharing. It also explores the ways the researchers preserved their research data for future use. It also explores the ways the library can take initiatives to encourage and extend support to the researchers and academicians to the organisation, preservation, and sharing of research data. To investigate and study the problem 100 questionnaires were distributed. There are 88 responses we received out of 100. The study revealed that the majority of respondents were agreeing about the research data sharing and free accessibility of research data to browse and reuse. Researchers are very much interested and agreed in the library’s involvement in organizing and preservation of research data. Researchers and faculty members are more concerned about their intellectual property rights while sharing the data on the public domain.

The National Open Access Research Data Archive (MIDAS) and Its Potential Benefits for Climate Research

The National Open Access Research Data Archive (MIDAS) and Its Potential Benefits for Climate Research

A cross-sectional study of social inequities in medical crowdfunding campaigns in the United States.

Americans are increasingly relying on crowdfunding to pay for the costs of healthcare. In medical crowdfunding (MCF), online platforms allow individuals to appeal to social networks to request donations for health and medical needs. Users are often told that success depends on how they organize and share their campaigns to increase social network engagement. However, experts have cautioned that MCF could exacerbate health and social disparities by amplifying the choices (and biases) of the crowd and leveraging these to determine who has access to financial support for healthcare. To date, research on potential axes of disparity in MCF, and their impacts on fundraising outcomes, has been limited. To answer these questions, this paper presents an exploratory cross-sectional study of a randomized sample of 637 MCF campaigns on the popular platform GoFundMe, for which the race, gender, age, and relationships of campaigners and campaign recipients were categorized alongside campaign characteristics and outcomes. Using both descriptive and inferential statistics, the analysis examines race, gender, and age disparities in MCF use, and tests how these are associated with differential campaign outcomes. The results show systemic disparities in MCF use and outcomes: people of color (and black women in particular) are under-represented; there is significant evidence of an additional digital care labor burden on women organizers of campaigns; and marginalized race and gender groups are associated with poorer fundraising outcomes. Outcomes are only minimally associated with campaign characteristics under users’ control, such as photos, videos, and updates. These results corroborate widespread concerns with how technology fuels health inequities, and how crowdfunding may be creating an unequal and biased marketplace for those seeking financial support to access healthcare. Further research and better data access are needed to explore these dynamics more deeply and inform policy for this largely unregulated industry.

Special Issue: 2019 Research Data Access and Preservation Summit

Special Issue: 2019 Research Data Access and Preservation Summit

Examining barriers for establishing a national data service

A system for monitoring the current situation of Data Archive Services (DAS) maturity in European countries was developed during the CESSDA Strengthening and Widening in (SaW 2016 and 2017) and further adapted in CESSDA Widening Activities 2018 (WA 2018) projects for continuous monitoring. An assessment of the existing national data sharing culture, the development of the social science sector and its production of high-quality research data, the funders’ research data policy requirements, and the capacity and skills of national grassroots initiatives, provide a framework for understanding the current situation in different countries. Methods used in the projects, included desk research of existing documents and a survey, combined with extensive interviews focused on the area of expertise of the informants (individuals from data services, research and decision makers’ representatives from each country). The focus of the paper is the situation in 20 non-member CESSDA European countries with emerging and immature DAS initiatives. Results show that countries are slowly but persistently removing the key obstacles in establishing a DAS initiative in their respective countries. The remaining obstacles reside mainly outside the control of the data professional community – namely research funders slowly adopt data sharing policies and incentives for data sharing, including the provision of a sustainable DAS infrastructure, capable of supporting researchers with publishing and accessing research data. The results show that the lack of expertise and skills of DAS initiatives, their understanding of tools and services or organizational settings are not such an issue, as more mature DAS are organising training and mentorship activities. Detailed guidance in the DAS advocacy and planning was prepared in the framework of the above-mentioned pan-European and some past regional projects. The tools and framework of those activities will be referred to in the discussions as a resource that can be used in other countries and continents.

Writing With Librarians: Reporting Back on Turning Your Poster or Presentation Into an Article

<strong>Objective</strong>: The objective of this article is to report on the process and effectiveness of a workshop presented at the Research Data Access and Preservation Summit 2019. Reporting back on how the workshop was developed and the impact it had on participants can inform future workshops on writing for librarians. Workshop materials are available in an associated OSF project. <strong>Methods</strong>: The authors approached workshop development holistically—that writing is a craft that requires habits and networks, and that participants are interested in hearing the technical guidelines of writing and submitting an article. The workshop dedicated time to activities meant to build a plan for writing. Data presented in this article was collected using Qualtrics, and is reported on in aggregate. Participants responded to the survey before the workshop started and after the conclusion of the workshop. <strong>Results</strong>: Participants reported that the workshop gave them a plan for how to move forward with transforming their presentation or poster into an article, and that they generally felt more empowered to write. <strong>Conclusions</strong>: This article suggests that it is important to provide an avenue for authors to develop professionally around writing. Attendees were eager for an opportunity to develop their writing, and to learn more about the opaque processes related to publishing an article, like how double-blind peer-review works and the different types of articles. The authors hope that others can reuse the materials presented at the workshop and provide more avenues of professional development for librarians and library professionals. <em>The substance of this article is based upon a workshop at RDAP Summit 2019.</em>

A Small Liberal Arts College Librarian at RDAP: Observations on Translating our Work Between Institutions

This commentary describes the impressions of a first-time attendee from a small liberal arts college (SLAC) to the Research Data Access and Preservation (RDAP) Summit, in May 2019, and observations about the makeup of the conference in terms of types of jobs and types of institutions represented among the attendees. The author also outlines a more general difficulty librarians from any institution face in adapting lessons learned and examples given by research data management librarians at other institutions, due to differences in institutional structure. The commentary suggests ways data management professionals might make reuse of ideas and solutions easier for one another, by analyzing why solutions work at different types of institutions, and by developing our understanding of how to replicate successful projects and practices in different organizational structures. The author discusses the value of attending RDAP Summit for librarians from smaller institutions such as SLACs, and compares the RDAP experience with professional development opportunities regarding data librarianship that are available on a region-by-region basis. <em>The substance of this article is based upon the author’s experience at RDAP Summit 2019.</em>

Piloting a Safe Health Researcher course

Robust and standardised licensing and governance frameworks are used to ensure that datasets intended for research use are made available under the terms and conditions specified by a data owner.&#x0D; The UK Data Service makes use of the Five Safes framework to operate its 3-tier data access policy, and ensuring that data classified as personal data can be made available via appropriate legal gateways. This set of principles has gained traction with national statistics around the world, yet it is remarkably absent in the narrative of data access for health research. The health domain tends to focus on ‘data sharing agreements’, and less on training around trust, security and disclosure. The concept of a Safe Health Researcher is missing, yet is appealing.&#x0D; The UK Data Service has been piloting such a half day course, with colleagues in the health domain. The training helps consolidate the less well defined idea of a ‘bona fide’ researcher, typically required by funders such as the UK’s Medical Research Council when accessing their data assets. The term bonafide makes some assumptions about the credentials of the researchers, yet fails to ‘test’ them, instead relying on ‘trust ‘underwritten by the individual’s university, and maybe a short online security course.&#x0D; While purposeful breaches are certainly not common place, a researcher accessing personal or sensitive data would benefit from a structured half-day course that covers aspects of: potential/ actual disclosure risk in health data and appropriate access pathways; safeguards to be put in place when data with risk are shared; and what might constitute a published ‘unsafe’ output, i.e. with a risk of disclosure. The training focuses on health data and research examples, and draws on aspects of the research data management and publishing training undertaken by the UK Data Service (e.g. Corti et al, 2014) and on the UK Statistics Authority approved ‘Safe Research Training’ (SRT) course, which leads to the Accredited Researcher status.

Real world evidence for European health policy-making: making the case for interoperability

Abstract Background The foundations of evidence-based health policy-making are transitioning from the use of partial evidence yielded elsewhere and the application of heuristic rules, to the development of learning systems based on the reuse of routine data collected by the same institutions that have to implement those policies. Supporting that transition, the scientific production of real-world evidence (RWE) is becoming pivotal, particularly in international policy-making. However, leveraging the immense wealth of data curated in European public institutions, requires the development of a new world-class research infrastructure and a supporting interoperability framework (IOF). Methods Based on the European Interoperability Framework (EIF) legal, organizational, semantic, and technical issues are being assessed. While legal, organizational and technical topics are analyzed from the perspective of the type of infrastructure, centralized or federated, to be developed, semantic interoperability is explored using three case studies on the linkage of different real world data sources: for characterizing resilient populations, studying the burden of dementia, and the effectiveness of stroke care pathways. Results Preliminary assessments advocate for the development of a federated infrastructure where data remain in house and research questions, data access and interoperability services are shared according to the capacity of each specific partner in the federation. Interoperability services for such an infrastructure should cover: a) the development and maintenance of a common data model to assure semantic interoperability, b) the development of self-contained distributed analytical pipelines; and c) the implementation of a training program aimed at increasing the capacity of each RI hub. Conclusions An interoperable federated research infrastructure is required to leverage the potential of real world data for European health policy-making. InfAct is paving the way.

All the world’s polar research data in one place

Data from the Polar Regions are of critical importance to modern research. Regardless of their disciplinary and institutional affiliations, researchers rely heavily on the comparison of existing data with new data sets to assess changes that are taking effect. In turn, knowledge based on as broad and comprehensive a selection of polar data sets as possible is used to inform politicians and decision makers. Although individual researchers and their institutions are aware of the importance of making collected data openly available through institutional websites, the infrastructures that are used for these purposes at many institutions, are often poorly interoperable, and therefore make valuable data difficult to find and reuse. In a recent survey of 113 major polar data providers, we found that an estimated 60% of the existing polar research data is unfindable through common search engines and can only be accessed through an institutional webpage. This findability gap limits the ability of researchers to establish robust models by which changes in the polar regions can be predicted. In this contribution, we present a new, free-to-use discovery service covering the global output of openly accessible polar research data and publications, with the purpose of rendering polar research more visible and retrievable to the research community as well as to the interested public, teachers and students and public services. The new service is currently under construction and will be hosted by UiT The Arctic University of Norway in close collaboration with the Norwegian Polar Institute.

Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute's Neuroinformatics Platform.

The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing, and analysis of different data types across several brain disorders. Underlying the platform is a robust and scalable data governance structure which allows for the flexibility to advance scientific understanding, while protecting the privacy of research participants. Recognizing the value of an open science approach to enabling discovery, the governance structure was designed not only to support collaborative research programs, but also to support open science by making all data open and accessible in the future. OBI’s rigorous approach to data sharing maintains the accessibility of research data for big discoveries without compromising privacy and security. Taking a Privacy by Design approach to both data sharing and development of the platform has allowed OBI to establish some best practices related to large-scale data sharing within Canada. The aim of this report is to highlight these best practices and develop a key open resource which may be referenced during the development of similar open science initiatives.

Open Arctic Research Index: Final report and recommendations

Access research data and research documents (e.g. publications) and make it more visible and findable through the internet is coming up as one of the major challenges for future development of the next generation of Digital Libraries. This challenge becomes more complicated when data producers (e.g. research institutes) are not aware by the needs of the scientific community for visibility and findability of their data or when the data producers lack the technology or the motivation to make their data available online.Although the Open Arctic Research Index pilot project focused only on the open-access research data and the open-access research documents published on Polar regions, the OpenARI found 60% of these open-access records are unfindable through searchable platforms outside the institutional webpage itself. This raises an awareness sign of the need of the scientific community to harvest the metadata of these open-access records in a homogenous, seamless database and making this database available to researchers, students and publics through one search platform. At present, neither Google Scholar nor any other search platform provide this service.Based on the fact that around 60% of the open-access polar records are unfindable through one search platform, we strongly suggest launching a full-scale management service at the University of Tromsø – the Arctic University of Norway (UiT). This new service will be built on existing experiences from High North Research Documents (i.e. an existing service at the UiT). OpenARI has concluded fifteen needs that are required for the full-scale management model. In addition to the main service (i.e. make open-access polar records more visible and findable through one search platform), we suggest to add three new services: 1) hosting of original data from the Polar regions; 2) creating a research platform; 3) creating an education platform. A new process including four stages of filtration is suggested in order to reduce the time and the overhead costs of using the UiT’s server. End-users will be able to perform search using a map. In addition to the classical way of presenting the results of a search, the end-users will be able to see the search results on a map and/or as a timeline.

Compartilhamento de dados de pesquisa em saúde: iniciativas do National Institutes of Health (NIH)

Este artigo apresenta um levantamento e uma análise das políticas e infraestruturas de compartilhamento de dados de pesquisa em saúde adotadas pelos institutos e centros que compõem o NIH – National Institutes of Health (Institutos Nacionais de Saúde), organismo norte-americano de pesquisa biomédica. A partir de pesquisa bibliográfica sobre definições e conceitos abordados neste estudo, o trabalho empírico consistiu na realização de buscas, nos sites dos institutos, centros e escritório central do NIH, de iniciativas de abertura e compartilhamento de dados de pesquisa. Localizaram-se no escritório central no NIH áreas responsáveis por essas ações, e foram identificados políticas e repositórios de compartilhamento de dados cadastrados no diretório de busca da NLM – U.S. National Library of Medicine (Biblioteca Nacional de Medicina dos Estados Unidos). Como resultado, foram feitas análises sobre cada uma dessas iniciativas, considerando: as principais políticas de dados adotadas e seus principais objetivos, tipos e níveis de acesso e de publicação dos dados, formas de inserção e contribuição de dados, existência ou não de códigos de conduta, principais áreas de pesquisa envolvidas, tipos de repositórios (temáticos ou institucionais). As considerações finais fornecem subsídios para debates sobre diferentes tipos e abordagens de abertura e compartilhamento de dados de pesquisa científica, indicando questões pertinentes aos desdobramentos futuros da pesquisa.

Special Issue: 2018 Research Data Access and Preservation Summit

The <em>Journal of eScience Librarianship</em> partners with the Research Data Access & Preservation (RDAP) Association to publish selected conference proceedings. This issue highlights some of the novel ideas, programs, and perspectives presented at the RDAP 2018 Summit.

PhD on Track: Open Science as a new track

PhD on Track is a web resource aimed primarily at PhD candidates and early career researchers. The ambition is to provide an accessible point of departure for beginning researchers related to searching and reviewing scholarly literature, and to sharing and publishing reports and data.It can be challenging for new candidates (or even for experienced researchers) to find their way in the tangle of new guidelines and practices on openness, data management, publishing, and adjoining issues. PhD on Track is intended to help, by collecting and organising in one resource, providing an overview of the most essential information. In our poster, we wish to focus on recent major revisions to the resource, and in particular on the new module Open Science. Revisions were made in response to important developments regarding new national and international guidelines on open publishing and data management, and in open science in general. PhD on Track, and the new Open Science module in particular, collects and organises relevant information – and discusses some of the fundamental issues on open access publishing, open archives, research data, and data management, including how to make data management plans and how to handle sensitive data. There are also sections on pre-registration, research ethics, copyright issues, and research assessment.PhD on Track is an open, freely available resource that was originally launched in 2013, as a co-operation between Norwegian and Danish institutions. From 2017, it is operated by 6 Norwegian institutions: the four university libraries in Bergen, Oslo, Trondheim, and Tromsø, in addition to the libraries at NHH Norwegian School of Economics Library and Western Norway University of Applied Sciences. While PhD on Track provides more detail on Norwegian policies and guidelines, it has been designed with an international audience in mind. It will be relaunched in the autumn of 2018.

UkbREST: efficient and streamlined data access for reproducible research in large biobanks.

SummaryLarge biobanks, such as UK Biobank with half a million participants, are changing the scale and availability of genotypic and phenotypic data for researchers to ask fundamental questions about the biology of health and disease. The breadth of the UK Biobank data is enabling discoveries at an unprecedented pace. However, this size and complexity pose new challenges to investigators who need to keep the accruing data up to date, comply with potential consent changes, and efficiently and reproducibly extract subsets of the data to answer specific scientific questions. Here we propose a tool called ukbREST designed for the UK Biobank study (easily extensible to other biobanks), which allows authorized users to efficiently retrieve phenotypic and genetic data. It exposes a REST API that makes data highly accessible inside a private and secure network, allowing the data specification in a human readable text format easily shareable with other researchers. These characteristics make ukbREST an important tool to make biobank’s valuable data more readily accessible to the research community and facilitate reproducibility of the analysis, a key aspect of science.Availability and implementationIt is implemented in Python using the Flask-RESTful framework for the API, and it is under the MIT license. It works with PostgreSQL and a Docker image is available for easy deployment. The source code and documentation is available in Github: https://github.com/hakyimlab/ukbrest.

The EnviDat Concept for an Institutional Environmental Data Portal

EnviDat is the environmental data portal developed by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. The strategic initiative EnviDat highlights the importance WSL lays on Research Data Management (RDM) at the institutional level and demonstrates the commitment to accessible research data in order to advance environmental science. EnviDat focuses on registering and publishing environmental data sets and provides unified and efficient access to the WSL’s comprehensive reservoir of environmental monitoring and research data. Research data management is organized in a decentralized manner where the responsibility to curate research data remains with the experts and the original data providers. EnviDat supports data producers and data users in registration, documentation, storage, publication, search and retrieval of a wide range of heterogeneous data sets from the environmental domain. Innovative features include (i) a flexible, three-layer metadata schema, (ii) an additive data discovery model that considers spatial data and (iii) a DataCRediT mechanism designed for specifying data authorship. In addition, the overall user-friendly appearance in EnviDat provides an important opportunity for showcasing WSL research activities and results. The EnviDat portal builds on a conceptual system consisting of a core system, a set of guiding principles and a number of key services. Its development closely follows the conceptual framework, being guided by principles towards the ultimate goal of providing useful services for researchers.

Cultural and institutional barriers among data stewards regarding data access for research

IntroductionIn British Columbia, the rules and procedures that data stewards follow to adjudicate data access requests (DAR) vary considerably. These variations can lead to discrepancies in the speed at which DARs are processed. With complex DARs involving numerous data stewards and data sets, the request may take over a year&#x0D; Objectives and ApproachOur main goal was to understand the institutional and cultural factors that influence data stewards when processing a DAR. We wished to see in particular if risk aversion was playing a role when making decisions about data access. We interviewed 24 people representing 21 organizations in British Columbia. Most were data stewards, but we also interviewed people processing the data requests and also privacy advisors.&#x0D; ResultsWe found that organizations varied greatly in terms of their skills and expertise regarding the rules and procedures around processing DARs. In particular, data stewards noted that they experienced differences in interpreting legislation, resulting in disagreements when they were working with other data stewards. In terms of risk aversion, data stewards stated they wished to encourage research, but in some cases followed unclear rules. Nearly all noted that there is little guidance provided for the job of “data steward” and either no or very little training when taking on these positions.&#x0D; Conclusion/ImplicationsWhile there may be stated governmental policies promoting that linked data be used for research, ultimately it is the data stewards approving DARs that will determine access to data. Understanding how and why they make those decisions will help better implement data access policies.

Using spatiotemporal patterns to optimize Earth Observation Big Data access: Novel approaches of indexing, service modeling and cloud computing

Based on our GEOSS Clearinghouse operating experience, we summarized the three Earth Observation (EO) Big Data access challenges, namely, fast access, accurate service estimation and global access, and two essential research questions: are there any spatiotemporal patterns when end users access EO data, and how can these spatiotemporal patterns be utilized to better facilitate EO Big Data access? To tackle these two research questions, we conducted a two-year pattern analysis with 2+ million user access records. The spatial pattern, temporal pattern and spatiotemporal pattern of user-data interactions were explored. For the second research question, we developed three spatiotemporal optimization strategies to respond to the three access challenges: a) spatiotemporal indexing to accelerate data access, b) spatiotemporal service modeling to improve data access accuracy and c) spatiotemporal cloud computing to enhance global access. This research is a pioneering framework for spatiotemporal optimization of EO Big Data access and valuable for other multidisciplinary geographic data and information research.

Health economic evaluations based on routine data in Germany: a systematic review

BackgroundImproved data access and funding for health services research have promoted the application of routine data to measure costs and effects of interventions within the German health care system. Following the trend towards real world evidence, this review aims to evaluate the status and quality of health economic evaluations based on routine data in Germany.MethodsTo identify relevant economic evaluations, a systematic literature search in the databases PubMed and EMBASE was complemented by a manual search. The included studies had to be full economic evaluations using German routine data to measure either costs, effects, or both. Study characteristics were assessed with a structured template. Additionally, the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) were used to measure quality of reporting.ResultsIn total, 912 records were identified and 35 studies were included in the further analysis. The majority of these studies was published in the past 5 years (n = 27, 77.1%) and used insurance claims data as a source of routine data (n = 30, 85.7%). The most common method used for handling selection bias was propensity score matching. With regard to the reporting quality, 42.9% (n = 15) of the studies satisfied at least 80% of the criteria on the CHEERS checklist.ConclusionsThis review confirms that routine data has become an increasingly common data source for health economic evaluations in Germany. While most studies addressed the application of routine data, this analysis reveals deficits in considering methodological particularities and in reporting quality of economic evaluations based on routine data. Nevertheless, this review demonstrates the overall potential of routine data for economic evaluations.