Qualitative Data Management and Analysis within a Data Repository

2019 ◽  
Vol 42 (8) ◽  
pp. 640-648 ◽  
Author(s):  
Marcy G. Antonio ◽  
Kara Schick-Makaroff ◽  
James M. Doiron ◽  
Laurene Sheilds ◽  
Lacie White ◽  
...  
Keyword(s):  
Qualitative Research ◽  
Data Management ◽  
Management Plan ◽  
Data Repository ◽  
Data Repositories ◽  
Research Teams ◽  
Geographically Dispersed ◽  
Audio Recordings ◽  
Field Notes ◽  
Period Data

Data repositories can support secure data management for multi-institutional and geographically dispersed research teams. Primarily designed to provide secure access, storage, and sharing of quantitative data, limited focus has been given to the unique considerations of data repositories for qualitative research. We share our experiences of using a data repository in a large qualitative nursing research study. Over a 27-month period, data collected by this 15-member team from 83 participants included photos, audio recordings and transcripts of interviews, and field notes. The data repository supported the secure collection, storage, and management of over 1,800 files with data. However, challenges were introduced during analysis that required negotiations about the structure and processes of the data repository. We discuss strengths and limitations of data repositories, and introduce practical strategies for developing a data management plan for qualitative research, which is supported through a data repository.

scholarly journals Research data management and services: Resources for different data practitioners

2021 ◽  
Vol 45 (3-4) ◽  
Author(s):  
Gilbert Mushi
Keyword(s):  
Data Management ◽  
Developed Countries ◽  
Management Plan ◽  
Research Data ◽  
Data Repository ◽  
Data Repositories ◽  
Research Libraries ◽  
Research Data Management ◽  
Metadata Standards ◽  
Training Resources

The emergence of data-driven research and demands for the establishment of Research Data Management (RDM) has created interest in academic institutions and research organizations globally. Some of the libraries especially in developed countries have started offering RDM services to their communities. Although lagging behind, some academic libraries in developing countries are at the stage of planning or implementing the service. However, the level of RDM awareness is very low among researchers, librarians and other data practitioners. The objective of this paper is to present available open resources for different data practitioners particularly researchers and librarians. It includes training resources for both researchers and librarians, Data Management Plan (DMP) tool for researchers; data repositories available for researchers to freely archive and share their research data to the local and international communities.   A case study with a survey was conducted at the University of Dodoma to identify relevant RDM services so that librarians could assist researchers to make their data accessible to the local and international community. The study findings revealed a low level of RDM awareness among researchers and librarians. Over 50% of the respondent indicated their perceived knowledge as poor in the following RDM knowledge areas; DMP, data repository, long term digital preservation, funders RDM mandates, metadata standards describing data and general awareness of RDM. Therefore, this paper presents available open resources for different data practitioners to improve RDM knowledge and boost the confidence of academic and research libraries in establishing the service.

Exploiting SeaDataCloud Temperature and Salinity time series data collections and comparing with Copernicus - a novel approach with SOURCE tool

2020 ◽  
Author(s):  
Paolo Oliveri ◽  
SImona Simoncelli ◽  
Pierluigi DI Pietro ◽  
Sara Durante
Keyword(s):  
Time Series ◽  
Best Practices ◽  
Data Management ◽  
Time Series Data ◽  
Management Plan ◽  
Global Ocean ◽  
Series Data ◽  
Data Repository ◽  
Log File ◽  
Data Collections

<p>One of the main challenges for the present and future in ocean observations is to find best practices for data management: infrastructures like Copernicus and SeaDataCloud already take responsibility for assembly, archive, update and publish data. Here we present the strengths and weaknesses in a SeaDataCloud Temperature and Salinity time series data collections, in particular a tool able to recognize the different devices and platforms and to merge them with processed Copernicus platforms.</p><p>While Copernicus has the main target to quickly acquire and publish data, SeaDataNet aims to publish data with the best quality available. This two data repository should be considered together, since the originator can ingest the data in both the infrastructures or only in one, or partially in both. This results sometimes in data partially available in Copernicus or SeaDataCloud, with great impact for the researcher who wants to access as much data as possible. The data reprocessing should not be loaded on researchers' shoulders, since only skilled users in all data management plan know how merge the data.</p><p>The SeaDataCloud time series data collections is a Global Ocean soon-to-be-published dataset that will represent a reference for ocean researchers, released in binary, user friendly Ocean Data View format. The database management plan was originally for profiles, but had been adapted for time series, resolving several issues like the uniqueness of the identifiers (ID).</p><p>Here we present an extension of the SOURCE (Sea Observations Utility for Reprocessing. Calibration and Evaluation) Python package, able to enhance the data quality with redundant sophisticated methods and simplify their usage. </p><p>SOURCE increases quality control (Q/C) performances on observations using statistical quality check procedures that follows the ocean best practices guidelines, exploiting the following  issues:</p><ol><li>Find and aggregate all broken time series using likeness in ID parameter strings;</li> <li>Find and organize in a dictionary all different metadata variables;</li> <li>Correct time series time to match simpler measure units;</li> <li>Filter devices that are outside of a selected horizontal rectangle;</li> <li>Give some information on original Q/C scheme by SeaDataCloud infrastructure;</li> <li>Give information tables on platforms and on the merged ID string duplicates together with an errors log file (missing time, depth, data, wrong Q/C variables, etc.).</li> </ol><p>In particular, the duplicates table and the log file may be helpful to SeaDataCloud partners in order to update the data collection and make it finally available for the users.</p><p>The reconstructed SeaDataCloud time series data, divided by parameter and stored in a more flexible dataset, give the possibility to ingest it in the main part of the software, allowing to compare it with Copernicus time series, find the same platform using horizontal and vertical surroundings (without looking to ID) find and cleanup  duplicated data, merge the two databases to extend the data coverage.</p><p>This allow researchers to have the most wide and the best quality possible data for the final users release and to to use these data to calibrate and validate models, in order to reach an idea of a whole area sea conditions.</p>

scholarly journals Information Integration for Machine Actionable Data Management Plans

2017 ◽  
Vol 12 (1) ◽  
pp. 22-35 ◽  
Author(s):  
Tomasz Miksa ◽  
Andreas Rauber ◽  
Roman Ganguly ◽  
Paolo Budroni
Keyword(s):  
Data Management ◽  
Information Integration ◽  
Open Science ◽  
Management Plan ◽  
Reproducible Research ◽  
Free Form ◽  
Text Documents ◽  
Data Repositories ◽  
Standard Data ◽  
Management Plans

Data management plans are free-form text documents describing the data used and produced in scientific experiments. The complexity of data-driven experiments requires precise descriptions of tools and datasets used in computations to enable their reproducibility and reuse. Data management plans fall short of these requirements. In this paper, we propose machine-actionable data management plans that cover the same themes as standard data management plans, but particular sections are filled with information obtained from existing tools. We present mapping of tools from the domains of digital preservation, reproducible research, open science, and data repositories to data management plan sections. Thus, we identify the requirements for a good solution and identify its limitations. We also propose a machine-actionable data model that enables information integration. The model uses ontologies and is based on existing standards.

Data management planning and repository demands for qualitative research

KWALON ◽  
2016 ◽  
Vol 21 (1) ◽  
Author(s):  
René van Horik
Keyword(s):  
Data Management ◽  
Research Data ◽  
Digital Data ◽  
Data Repository ◽  
Data Sets ◽  
Data Repositories ◽  
Management Planning ◽  
Research Activities ◽  
Trusted Data ◽  
New Research

Summary Nowadays, research without a role for digital data and data analysis tools is barely possible. As a result, we see an increasing interest in research data management, as this enables the replication of research outcomes and the reuse of research data for new research activities. Data management planning outlines how to handle data, both during research and after the research is completed. Trusted data repositories are places were research data are archived and made available for the long term. This article covers the state of the art concerning data management and data repository demands with a focus on qualitative data sets.

scholarly journals Researchers at Arab Universities Hold Positive Views on Research Data Management and Data Sharing

2020 ◽  
Vol 15 (2) ◽  
pp. 168-170
Author(s):  
Jennifer Kaari
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Data Privacy ◽  
Management Practices ◽  
Open Data ◽  
Scientific Progress ◽  
Management Plan ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management

A Review of: Elsayed, A. M., & Saleh, E. I. (2018). Research data management and sharing among researchers in Arab universities: An exploratory study. IFLA Journal, 44(4), 281–299. https://doi.org/10.1177/0340035218785196 Abstract Objective – To investigate researchers’ practices and attitudes regarding research data management and data sharing. Design – Email survey. Setting – Universities in Egypt, Jordan, and Saudi Arabia. Subjects – Surveys were sent to 4,086 academic faculty researchers. Methods – The survey was emailed to faculty at three Arab universities, targeting faculty in the life sciences and engineering. The survey was created using Google Docs and remained open for five months. Participants were asked basic demographic questions, questions regarding their research data and metadata practices, and questions regarding their data sharing practices. Main Results – The authors received 337 responses, for a response rate of 8%. The results showed that 48.4% of respondents had a data management plan and that 97% were responsible for preserving their own data. Most respondents stored their research data on their personal storage devices. The authors found that 64.4% of respondents reported sharing their research data. Respondents most frequently shared their data by publishing in a data research journal, sharing through academic social networks such as ResearchGate, and providing data upon request to peers. Only 5.1% of respondents shared data through an open data repository.  Of those who did not share data, data privacy and confidentiality were the most common reasons cited. Of the respondents who did share their data, contributing to scientific progress and increased citation and visibility were the primary reasons for doing so. A total of 59.6% of respondents stated that they needed more training in research data management from their universities. Conclusion – The authors conclude that researchers at Arab universities are still primarily responsible for their own data and that data management planning is still a new concept to most researchers. For the most part, the researchers had a positive attitude toward data sharing, although depositing data in open repositories is still not a widespread practice. The authors conclude that in order to encourage strong data management practices and open data sharing among Arab university researchers, more training and institutional support is needed.

scholarly journals Integration of an Active Research Data System with a Data Repository to Streamline the Research Data Lifecyle: Pure-NOMAD Case Study

2018 ◽  
Vol 12 (2) ◽  
pp. 210-219
Author(s):  
Simone Ivan Conte ◽  
Federica Fina ◽  
Michalis Psalios ◽  
Shyam Ryal ◽  
Tomas Lebl ◽  
...  
Keyword(s):  
Data Management ◽  
Active Phase ◽  
Research Data ◽  
Data Management System ◽  
Data Repository ◽  
Data Repositories ◽  
Human Errors ◽  
Important Challenge ◽  
Active Data ◽  
Active Research

Research funders have introduced requirements that expect researchers to properly manage and publicly share their research data, and expect institutions to put in place services to support researchers in meeting these requirements. So far the general focus of these services and systems has been on addressing the final stages of the research data lifecycle (archive, share and re-use), rather than stages related to the active phase of the cycle (collect/create and analyse). As a result, full integration of active data management systems with data repositories is not yet the norm, making the streamlined transition of data from an active to a published and archived status an important challenge. In this paper we present the integration between an active data management system developed in-house (NOMAD) and Elsevier’s Pure data repository used at our institution, with the aim of offering a simple workflow to facilitate and promote the data deposit process. The integration results in a new data management and publication workflow that helps researchers to save time, minimize human errors related to manually handling files, and further promote data deposit together with collaboration across the institution.

scholarly journals Dealing with Data: Science Librarians’ Participation in Data Management at Association of Research Libraries Institutions

2014 ◽  
Vol 75 (4) ◽  
pp. 557-574 ◽  
Author(s):  
Karen Antell ◽  
Jody Bales Foote ◽  
Jaymie Turner ◽  
Brian Shults
Keyword(s):  
Data Management ◽  
Academic Libraries ◽  
Data Science ◽  
Management Plan ◽  
Funding Agency ◽  
Management Support ◽  
Data Repositories ◽  
Institutional Repositories ◽  
Research Libraries ◽  
Association Of Research Libraries

As long as empirical research has existed, researchers have been doing “data management” in one form or another. However, funding agency mandates for doing formal data management are relatively recent, and academic libraries’ involvement has been concentrated mainly in the last few years. The National Science Foundation implemented a new mandate in January 2011, requiring researchers to include a data management plan with their proposals for funding. This has prompted many academic libraries to work more actively than before in data management, and science librarians in particular are uniquely poised to step into new roles to meet researchers’ data management needs. This study, a survey of science librarians at institutions affiliated with the Association of Research Libraries, investigates science librarians’ awareness of and involvement in institutional repositories, data repositories, and data management support services at their institutions. The study also explores the roles and responsibilities, both new and traditional, that science librarians have assumed related to data management, and the skills that science librarians believe are necessary to meet the demands of data management work. The results reveal themes of both uncertainty and optimism—uncertainty about the roles of librarians, libraries, and other campus entities; uncertainty about the skills that will be required; but also optimism about applying “traditional” librarian skills to this emerging field of academic librarianship.

Research data management in Turkey: A survey to build an effective national data repository

IFLA Journal ◽  
2020 ◽  
pp. 034003522091798
Author(s):  
Guleda Dogan ◽  
Zehra Taskin ◽  
Arsev Umur Aydinoglu
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Management Plan ◽  
Development Stage ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management ◽  
Funding Agencies ◽  
Technological Research Council ◽  
Management Issues

Research data management is an important topic for funding agencies, universities and researchers. In this context, the main aim of this study is to collect preliminary information for Aperta, which is being developed by the Scientific and Technological Research Council of Turkey, to fulfil the following goals: determine the research data management awareness levels of researchers in Turkey; understand current research data management practices in their research environments; and find out their experiences of policy issues. For this, a questionnaire was distributed to 37,223 researchers, with 1577 researchers completing it. The results indicated that researchers who spend more time with data have more concerns about data management issues. The levels of experience of creating a data management plan were quite low. The importance of this study lies in how it is able to show the current research data management practices of Turkish scholars during the new repository’s foundational development stage.

scholarly journals Do I Have To Be An “Other” To Be Myself? Exploring Gender Diversity In Taxonomy, Data Collection, And Through The Research Data Lifecycle

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Ari Gofman ◽  
Sam A. Leif ◽  
Hannah Gunderman ◽  
Nina Exner
Keyword(s):  
Data Collection ◽  
Data Management ◽  
Research Question ◽  
Good Practice ◽  
Gender Diversity ◽  
Radical Change ◽  
Management Plan ◽  
Data Repositories ◽  
Planning Stage ◽  
Gender Category

Objective: Existing studies estimate that between 0.3% and 2% of adults in the U.S. (between 900,000 and 2.6 million in 2020) identify as a nonbinary gender or otherwise gender nonconforming. In response to the RDAP 2021 theme of radical change, this article examines the need to change how datasets represent nonbinary persons and how research involving gender data should approach the curation of this data at each stage of the research lifecycle. Methods: In this article, we examine some of the known challenges of gender inclusion in datasets and summarize some solutions underway. Using a critical lens, we examine the difference between current practice and inclusive practice in gender representation, describing inclusive practices at each stage of the research lifecycle from writing a data management plan to sharing data. Results: Data structures that limit gender to “male” and “female” or ontological structures that use mapping to collapse gender demographics to binary values exclude nonbinary and gender diverse populations. Some data collection instruments attempt inclusivity by adding the gender category of “other,” but using the “other” gender category labels nonbinary persons as intrinsically alien. Inclusive change must go farther, to move from alienation to inclusive categories. We describe several techniques for inclusively representing gender in data, from the data management planning stage, to collecting data, cleaning data, and sharing data. To facilitate better sharing of gender data, repositories must also allow mapping that includes nonbinary genders explicitly and allow for ontological mapping for long-term representation of diverse gender identities. Conclusions: A good practice during research design is to consider two levels of critique in the data collection plan. First, consider the research question at hand and remove unnecessary gendering from the data. Secondly, if the research question needs gender, make sure to include nonbinary genders explicitly. Allies must take on this problem without leaving it to those who are most affected by it. Further, more voices calling for inclusionary practices surrounding data rises to a crescendo that cannot be ignored.

Implikatur Ekspresi Tindak Tutur Verdiktif Srimpi Anglir Mendhung

Panggung ◽  
2019 ◽  
Vol 29 (4) ◽  
Author(s):  
Maryono Maryono
Keyword(s):  
Qualitative Research ◽  
Research Methodology ◽  
Speech Acts ◽  
Performing Arts ◽  
Audio Recordings ◽  
Qualitative Research Methodology ◽  
Extrinsic Values

ABSTRACTUnderstanding of art will be complete if it can express a particular value. One source of values in art is the pleasure of its objectivity, which encompasses intrinsic and extrinsic values with aesthetical visualization. The values of implicature in the Srimpi Anglir Mendhung can be found by referring to the expression of verdictive speech acts in its verbal and nonverbal components. In order to study the implicature values contained in Srimpi Anglir Mendhung, the researcher uses a qualitative research methodology based on the theory of pragmatics and theory of performing arts. The strategies used for collecting data are a library study, a study of visual recordings, a study of audio recordings, and interviews. The technique of analysis is interactive and involves the triangulation of data, methodology, and theory. The results of the discussion show that the implicature in the expression of verdictive speech acts in Srimpi Anglir Mendhung is a form of adulation and homage to the noble king, Sultan Agung Hanyakra Kusuma from the Mataram Kingdom. The values of heroism and virtue contained in Srimpi Anglir Mendhung are a reflection of the values of life, which should be emulated and appreciated by the audience and general public.Keywords: implicature, expression of verdictive speech acts, and Srimpi Anglir Mendhung dance. ABSTRAKPemahaman tentang seni terjadi secara lengkap apabila mampu untuk mengungkapkan suatu nilai. Satu sumber nilai seni adalah kenikmatan yang diberikan oleh objektifitas terhadap nilai-nilai instrinsik dan ekstrinsik dengan visualisasi estetis. Merujuk pada ekspresi tindak tutur verdiktif pada komponen verbal dan nonverbal, Tari Srimpi Anglir Mendhung dapat ditarik implikatur nilainya. Untuk mengkaji implikatur nilai yang terkandung dalam Tari Srimpi Anglir Mendhung, peneliti menggunakan metodologi penelitian kualitatif dengan berlandaskan teori pragmatik dan teori seni pertunjukan. Strategi pengumpulan data berupa studi pustaka, studi rekaman visual, studi rekaman audio, dan wawancara. Teknik analisisnya bersifat interaktif dengan mentrianggulasikan data, metodologis, dan teori. Hasil pembahasan ditemukan bahwa implikatur ekspresi tindak tutur verdiktif Srimpi Anglir Mendhung merupakan bentuk sanjungan dan penghormatan terhadap raja yang dimuliakan yaitu Sultan Agung Hanyakra Kusuma dari Kerajaan Mataram. Nilai-nilai keprajuritan dan kebajikan yang terkandung dalam Srimpi Anglir Mendhung merupakan cerminan nilai-nilai kehidupan, layak diteladani dan diapresiasi oleh audiens maupun masyarakat luas.Kata kunci: ekspresi, implikatur, Tari Srimpi Anglir Mendhung, tindak tutur verdiktif

Sign in / Sign up

Export Citation Format

Share Document