scholarly journals DataShare: Empowering Researcher Data Curation

2014 ◽  
Vol 9 (1) ◽  
pp. 110-118 ◽  
Author(s):  
Stephen Abrams ◽  
Patricia Cruse ◽  
Carly Strasser ◽  
Perry Willet ◽  
Geoffrey Boushey ◽  
...  
Keyword(s):  
Management Practices ◽  
Research Data ◽  
Ease Of Use ◽  
Public Access ◽  
Data Curation ◽  
Service Access ◽  
Barriers To Entry ◽  
Research Activity ◽  
Faceted Search ◽  
Widespread Adoption

Researchers are increasingly being asked to ensure that all products of research activity – not just traditional publications – are preserved and made widely available for study and reuse as a precondition for publication or grant funding, or to conform to disciplinary best practices. In order to conform to these requirements, scholars need effective, easy-to-use tools and services for the long-term curation of their research data. The DataShare service, developed at the University of California, is being used by researchers to: (1) prepare for curation by reviewing best practice recommendations for the acquisition or creation of digital research data; (2) select datasets using intuitive file browsing and drag-and-drop interfaces; (3) describe their data for enhanced discoverability in terms of the DataCite metadata schema; (4) preserve their data by uploading to a public access collection in the UC3 Merritt curation repository; (5) cite their data in terms of persistent and globally-resolvable DOI identifiers; (6) expose their data through registration with well-known abstracting and indexing services and major internet search engines; (7) control the dissemination of their data through enforceable data use agreements; and (8) discover and retrieve datasets of interest through a faceted search and browse environment. Since the widespread adoption of effective data management practices is highly dependent on ease of use and integration into existing individual, institutional, and disciplinary workflows, the emphasis throughout the design and implementation of DataShare is to provide the highest level of curation service with the lowest possible technical barriers to entry by individual researchers. By enabling intuitive, self-service access to data curation functions, DataShare helps to contribute to more widespread adoption of good data curation practices that are critical to open scientific inquiry, discourse, and advancement.

scholarly journals Disciplinary differences in faculty research data management practices and perspectives

2013 ◽  
Vol 8 (2) ◽  
pp. 5-26 ◽  
Author(s):  
Katherine G. Akers ◽  
Jennifer Doty
Keyword(s):  
Data Management ◽  
Research University ◽  
Management Practices ◽  
Research Data ◽  
Data Curation ◽  
Academic Librarians ◽  
Disciplinary Differences ◽  
Research Data Management ◽  
Management Actions ◽  
Research Domains

Academic librarians are increasingly engaging in data curation by providing infrastructure (e.g., institutional repositories) and offering services (e.g., data management plan consultations) to support the management of research data on their campuses. Efforts to develop these resources may benefit from a greater understanding of disciplinary differences in research data management needs. After conducting a survey of data management practices and perspectives at our research university, we categorized faculty members into four research domains—arts and humanities, social sciences, medical sciences, and basic sciences—and analyzed variations in their patterns of survey responses. We found statistically significant differences among the four research domains for nearly every survey item, revealing important disciplinary distinctions in data management actions, attitudes, and interest in support services. Serious consideration of both the similarities and dissimilarities among disciplines will help guide academic librarians and other data curation professionals in developing a range of data-management services that can be tailored to the unique needs of different scholarly researchers.

scholarly journals How Data Curation Enables Epistemically Responsible Reuse of Qualitative Data

2021 ◽  
Author(s):  
Sebastian Karcher ◽  
Dessislava Kirilova ◽  
Christiane Pagé ◽  
Nic Weber
Keyword(s):  
Qualitative Research ◽  
Quantitative Research ◽  
Qualitative Data ◽  
Management Practices ◽  
Secondary Analysis ◽  
Research Data ◽  
Data Curation ◽  
Special Issue ◽  
Technological Advances ◽  
Recent Trends

Data sharing and reuse are becoming the norm in quantitative research. At the same time, significant skepticism still accompanies the sharing and reuse of qualitative research data on both ethical and epistemological grounds. Nevertheless, there is growing interest in the reuse of qualitative data, as demonstrated by the range of contributions in this special issue. In this research note, we address epistemological critiques of reusing qualitative data and argue that careful curation of data can enable what we term “epistemologically responsible reuse” of qualitative data. We begin by briefly defining qualitative data and summarizing common epistemological objections to their shareability or usefulness for secondary analysis. We then introduce the concept of curation as enabling epistemologically responsible reuse and a potential way to address such objections. We discuss three recent trends that we believe are enhancing curatorial practices and thus expand the opportunities for responsible reuse: improvements in data management practices among researchers, the development of collaborative curation practices at repositories focused on qualitative data and technological advances that support sharing rich qualitative data. Using three examples of successful reuse of qualitative data, we illustrate the potential of these three trends to further improve the availability of reusable data projects.

Research data services

IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 266-277 ◽  
Author(s):  
Monica Lassi ◽  
Maria Johnsson ◽  
Koraljka Golub
Keyword(s):  
Data Management ◽  
Exploratory Study ◽  
Preliminary Analysis ◽  
Management Practices ◽  
Environmental Studies ◽  
Research Data ◽  
Data Curation ◽  
Data Services ◽  
Research Data Management ◽  
Ongoing Development

The paper reports on an exploratory study of researchers’ needs for effective research data management at two Swedish universities, conducted in order to inform the ongoing development of research data services. Twelve researchers from diverse fields have been interviewed, including biology, cultural studies, economics, environmental studies, geography, history, linguistics, media and psychology. The interviews were structured, guided by the Data Curation Profiles Toolkit developed at Purdue University, with added questions regarding subject metadata. The preliminary analysis indicates that the research data management practices vary greatly among the respondents, and therefore so do the implications for research data services. The added questions on subject metadata indicate needs of services guiding researchers in describing their datasets with adequate metadata.

Selecting a Pesticide Fate Model at the Watershed Scale Using a Multi-criteria Analysis

2006 ◽  
Vol 41 (3) ◽  
pp. 283-295 ◽  
Author(s):  
Renaud Quilbé ◽  
Alain N. Rousseau ◽  
Pierre Lafrance ◽  
Jacinthe Leclerc ◽  
Mohamed Amrani
Keyword(s):  
Best Management Practices ◽  
Management Practices ◽  
Ease Of Use ◽  
Watershed Scale ◽  
Water Quality Standards ◽  
Best Management ◽  
Multi Criteria Analysis ◽  
Selection Framework ◽  
Selection Of

Abstract Numerous models have been developed over the last decades to simulate the fate of pesticides at the watershed scale. Based on a literature review, we inventoried thirty-six models categorized as management, research, screening or multimedia models, each of them having specific strengths and weaknesses. Given this large number of models, it may be difficult for potential users (stakeholders or scientists) to find the most suited one with respect to their needs. To help in this process, this paper proposes a pragmatic approach based on a multi-criteria analysis. Selection criteria are defined following the user's needs and classified in five classes: modelling characteristics, output variables, model applicability, possibilities to simulate best management practices (BMPs) and ease of use. The relative importance of each criterion is quantified by a weight and the total score of a model is calculated by adding the resulting weights of satisfied criteria. This selection framework is illustrated with a case study that consists in selecting a model to develop water quality standards at the watershed scale with respect to the implementation of BMPs. This resulted in the selection of three models: BASINS, SWAT and GIBSI.

scholarly journals Connecting Data Publication to the Research Workflow: A Preliminary Analysis

2017 ◽  
Vol 12 (1) ◽  
pp. 88-105 ◽  
Author(s):  
Sünje Dallmeier-Tiessen ◽  
Varsha Khodiyar ◽  
Fiona Murphy ◽  
Amy Nurnberger ◽  
Lisa Raymond ◽  
...  
Keyword(s):  
Working Group ◽  
Research Data ◽  
Data Publishing ◽  
Data Repository ◽  
Research Activity ◽  
Data Repositories ◽  
Data Publication ◽  
Loosely Coupled ◽  
Definition Of ◽  
Data Documentation

The data curation community has long encouraged researchers to document collected research data during active stages of the research workflow, to provide robust metadata earlier, and support research data publication and preservation. Data documentation with robust metadata is one of a number of steps in effective data publication. Data publication is the process of making digital research objects ‘FAIR’, i.e. findable, accessible, interoperable, and reusable; attributes increasingly expected by research communities, funders and society. Research data publishing workflows are the means to that end. Currently, however, much published research data remains inconsistently and inadequately documented by researchers. Documentation of data closer in time to data collection would help mitigate the high cost that repositories associate with the ingest process. More effective data publication and sharing should in principle result from early interactions between researchers and their selected data repository. This paper describes a short study undertaken by members of the Research Data Alliance (RDA) and World Data System (WDS) working group on Publishing Data Workflows. We present a collection of recent examples of data publication workflows that connect data repositories and publishing platforms with research activity ‘upstream’ of the ingest process. We re-articulate previous recommendations of the working group, to account for the varied upstream service components and platforms that support the flow of contextual and provenance information downstream. These workflows should be open and loosely coupled to support interoperability, including with preservation and publication environments. Our recommendations aim to stimulate further work on researchers’ views of data publishing and the extent to which available services and infrastructure facilitate the publication of FAIR data. We also aim to stimulate further dialogue about, and definition of, the roles and responsibilities of research data services and platform providers for the ‘FAIRness’ of research data publication workflows themselves.

scholarly journals DataStaR: Using the Semantic Web approach for Data Curation

2011 ◽  
Vol 6 (2) ◽  
pp. 209-221 ◽  
Author(s):  
Huda Khan ◽  
Brian Caruso ◽  
Jon Corson-Rikert ◽  
Dianne Dietrich ◽  
Brian Lowe ◽  
...  
Keyword(s):  
Social Sciences ◽  
Semantic Web ◽  
Data Sharing ◽  
Research Data ◽  
Data Curation ◽  
Data Staging ◽  
Domain Specific ◽  
Digital Infrastructure

In disciplines as varied as medicine, social sciences, and economics, data and their analyses are essential parts of researchers’ contributions to their respective fields. While sharing research data for review and analysis presents new opportunities for furthering research, capturing these data in digital forms and providing the digital infrastructure for sharing data and metadata pose several challenges. This paper reviews the motivations behind and design of the Data Staging Repository (DataStaR) platform that targets specific portions of the research data curation lifecycle: data and metadata capture and sharing prior to publication, and publication to permanent archival repositories. The goal of DataStaR is to support both the sharing and publishing of data while at the same time enabling metadata creation without imposing additional overheads for researchers and librarians. Furthermore, DataStaR is intended to provide cross-disciplinary support by being able to integrate different domain-specific metadata schemas according to researchers’ needs. DataStaR’s strategy of a usable interface coupled with metadata flexibility allows for a more scaleable solution for data sharing, publication, and metadata reuse.

scholarly journals Establishing the Link between Management Practise, Employees’ Ability and Workforce Productivity: A Case of UK’s Telecom Sector

2020 ◽  
Vol 2 (2) ◽  
pp. 10-19
Author(s):  
Junaid Khan ◽  
Umair Zahid
Keyword(s):  
Management Practices ◽  
Descriptive Analysis ◽  
Research Data ◽  
Research Support ◽  
Telecommunication Sector ◽  
Productivity Level ◽  
Statistical Measures ◽  
Workforce Productivity ◽  
The Uk ◽  
Telecom Sector

Workforce productivity had been affected by many different factors in organisations around the globe. There have been many instances in different organisations workforce that has affected their productivity level. Current research looks into the management practices and the ability of employees working in the telecommunication sector of the UK for analysing their linkage with workforce productivity. The use of different management practices has been directly linked with workforce productivity in the telecommunication sector of the UK. The current study uses quantitative primary measures for collecting and analysing the research data. The developed results of the research support all the developed hypotheses of the research that were established to measure the direct impact of employee ability and management practices of the telecommunication sector on workforce productivity. The collected data was analysed through the use of statistical measures of descriptive analysis, regression analysis, and correlation analysis. The developed research results accept the alternate hypotheses developed in the research body.

scholarly journals Evaluasi Kepuasan Pelayanan Pengguna Aplikasi OPAC Perpustakaan STMIK AMIKOM Yogyakarta

2015 ◽  
Vol 1 (1) ◽  
pp. 46
Author(s):  
Fatimah Nur Arifah ◽  
Abidarin Rosidi ◽  
Hanif Al Fatta
Keyword(s):  
Performance Analysis ◽  
User Satisfaction ◽  
Ease Of Use ◽  
Public Access ◽  
End User ◽  
Improve Performance ◽  
Five Dimensions ◽  
Satisfaction Index ◽  
Level Of Satisfaction ◽  
End User Computing

Penelitian ini bertujuan untuk mengetahui dan mengukur tingkat kepuasan pengguna terhadap aplikasi Online Public Access Catalog (OPAC) pada Perpustakaan STMIK AMIKOM Yogyakarta. Subjek penelitian ini ialah mahasiswa yang terdaftar sebagai anggota perpustakaan dan objek penelitian ini adalah aplikasi OPAC Perpustakaan STMIK AMIKOM Yogyakarta. Analisis data dalam penelitian ini menggunakan diagram Importance Performance Analysis (IPA) dipadukan dengan Indeks Kepuasan Pengguna (IKP) didasarkan pada indikator-indikator dari lima dimensi End User Computing Satisfaction yaitu isi (content), keakuratan (accuracy), bentuk (format), kemudahan penggunaan (ease of use) dan ketepatan waktu (timeliness). Hasil penelitian menunjukkan pengguna OPAC Perpustakaan STMIK AMIKOM Yogyakarta cukup puas dengan hasil perhitungan IKP 78,01 %. Penelitian ini diharapkan dapat memberi masukan pada pengelola OPAC sebagai bahan acuan untuk meningkatkan kinerja OPAC.This study aims to identify and measure the level of satisfaction of users of the application Online Public Access Catalog (OPAC) in the library STMIK AMIKOM Yogyakarta. These subjects are students who are registered as members of the library and the object of this study is OPAC STMIK Library AMIKOM Yogyakarta. Analysis of the data in this study using a diagram of Importance Performance Analysis (IPA) which is combined with User Satisfaction Index (IKP) based on the five dimensions of End User Computing Satisfaction; content, accuracy, format, ease of use and timeliness. The results showed users of OPAC STMIK AMIKOM Yogyakarta quite satisfied with the results of the calculation IKP 78.01%. This research is expected to provide input to the manager of the OPAC as a reference to improve performance of the OPAC.

Sharing Open Data in Agriculture

2021 ◽  
pp. 244-266
Author(s):  
Liah Shonhe
Keyword(s):  
Agricultural Sector ◽  
Open Data ◽  
Research Data ◽  
Data Sets ◽  
Research Activity ◽  
African Countries ◽  
Data Set ◽  
Data Repositories ◽  
Bibliographic Data ◽  
Prolific Authors

The main focus of the study was to explore the practices of open data sharing in the agricultural sector, including establishing the research outputs concerning open data in agriculture. The study adopted a desktop research methodology based on literature review and bibliographic data from WoS database. Bibliometric indicators discussed include yearly productivity, most prolific authors, and enhanced countries. Study findings revealed that research activity in the field of agriculture and open access is very low. There were 36 OA articles and only 6 publications had an open data badge. Most researchers do not yet embrace the need to openly publish their data set despite the availability of numerous open data repositories. Unfortunately, most African countries are still lagging behind in management of agricultural open data. The study therefore recommends that researchers should publish their research data sets as OA. African countries need to put more efforts in establishing open data repositories and implementing the necessary policies to facilitate OA.

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