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Journal articles on the topic 'Data Practices'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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1

Briney, Kristin, Heather Coates, and Abigail Goben. "Foundational Practices of Research Data Management." Research Ideas and Outcomes 6 (July 27, 2020): e56508. https://doi.org/10.3897/rio.6.e56508.

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The importance of research data has grown as researchers across disciplines seek to ensure reproducibility, facilitate data reuse, and acknowledge data as a valuable scholarly commodity. Researchers are under increasing pressure to share their data for validation and reuse. Adopting good data management practices allows researchers to efficiently locate their data, understand it, and use it throughout all of the stages of a project and in the future. Additionally, good data management can streamline data analysis, visualization, and reporting, thus making publication less stressful and time-co

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2

Wong, Janis. "Data Practices and Data Stewardship." Interactions 30, no. 3 (2023): 60–63. http://dx.doi.org/10.1145/3589133.

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This forum is dedicated to exploring the notion of meaningfulness in design processes, taking the perspectives of community groups, nongovernmental organizations, and those who are marginalized in society as starting points. Authors will reflect conceptually and methodologically on practical engagements. --- Rosanna Bellini and Angelika Strohmayer, Editors

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3

Churchill, Elizabeth F. "Designing data practices." Interactions 23, no. 5 (2016): 20–21. http://dx.doi.org/10.1145/2983401.

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Sandhya Kona, Sree. "Ensuring Data Integrity in Big Data Ingestion: Techniques and Best Practices for Data Quality Assurance." International Journal of Science and Research (IJSR) 9, no. 5 (2020): 1866–69. http://dx.doi.org/10.21275/sr24522140238.

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Lin, Canchu, Anand S. Kunnathur, and Long Li. "Conceptualizing big data practices." International Journal of Accounting & Information Management 28, no. 2 (2020): 205–22. http://dx.doi.org/10.1108/ijaim-12-2018-0154.

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Purpose The purpose of this paper is to provide a conceptual understanding of Big Data practices in organizations, which will enable exploring the operational and strategic roles of Big Data in organizational performance. Design/methodology/approach Both academic and non-academic literature studies on Big Data were reviewed so as to capture what was known about Big Data practices. Qualitative interviews were conducted with firm executives about Big Data practices in their organizations. Both literature review and interview results were analyzed based on the dynamic capabilities perspective. Fi

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6

Manahilova, Galina. "DATA VISUALIZATION BEST PRACTICES." Entrepreneurship 11, no. 1 (2023): 41–47. http://dx.doi.org/10.37708/ep.swu.v11i1.4.

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Today nearly all organizations use data visualization to review their financial and business results, drive conclusions and make decisions. There are many benefits of data visualization. These include but are not limited to presenting many numbers in a small space, a synthesized view of the data, making comparisons easy, and the users thinking of the data rather than methodology, etc. Essentially, the overall graphics reveal the data. This paper will review three best practices graphs: voting results, categories performance and comparison, and marketing performance. While looking into best dat

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Villanueva, Angela G., Robert Cook-Deegan, Jill O. Robinson, Amy L. McGuire, and Mary A. Majumder. "Genomic Data-Sharing Practices." Journal of Law, Medicine & Ethics 47, no. 1 (2019): 31–40. http://dx.doi.org/10.1177/1073110519840482.

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Making data broadly accessible is essential to creating a medical information commons (MIC). Transparency about data-sharing practices can cultivate trust among prospective and existing MIC participants. We present an analysis of 34 initiatives sharing DNA-derived data based on public information. We describe data-sharing practices captured, including practices related to consent, privacy and security, data access, oversight, and participant engagement. Our results reveal that data-sharing initiatives have some distance to go in achieving transparency.

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Ma, Rongqian, and Fanghui Xiao. "Data Practices in Digital History." International Journal of Digital Curation 15, no. 1 (2020): 21. http://dx.doi.org/10.2218/ijdc.v15i1.597.

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 This paper presents an exploratory research project that investigates data practices in digital history research. Emerging from the 1950s and ‘60s in the United States, digital history remains a charged topic among historians, requiring a new research paradigm that includes new concepts and methodologies, an intensive degree of interdisciplinary, inter-institutional, and international collaboration, and experimental forms of research sharing, publishing, and evaluation. Using mixed methods of interviews and questionnaire, we identified data challenges in digital history research practic

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Kwon, Hyun Jung, Yoon Joo Seo, Mi Yeon Kim, and Sue Yeon Chung. "Recommended practices for supplemental data." Science Editing 7, no. 1 (2020): 94–103. http://dx.doi.org/10.6087/kcse.200.

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Since various forms of supplemental data (SD) have been introduced in academic publications, it has become necessary to establish guidelines to systematically process, indicate, and distribute such data. This material aims to help the science journals establish rational SD policies and guidelines and to ensure compliance with such policies and to manage them consistently. Generally, SD can be approached in a literal way by categorizing ‘appendices’ as ‘additional or separately added complementary materials’ and ‘supplements’ as ‘materials supplemental to the research in a comprehensive sense,’

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Pansara, Ronak. "Master Data Governance Best Practices." International Journal of Computer Science and Mobile Computing 10, no. 11 (2021): 1–3. http://dx.doi.org/10.47760/ijcsmc.2021.v10i11.001.

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Master data governance is not a new field, and it has existed since the early 90s (8). However, the demand for master data governance has been rising recently due to the ever-increasing demand for cost optimization, faster product innovations, compliance with the set rules and regulations, and competitive advantage in the business field. One of the areas in which companies can achieve master data governance is through maintaining consistent data quality. Handling data is one of the pain areas in most companies due to the complicities involved in managing data. Still, companies that succeed in

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11

Vakali, A., B. Catania, and A. Maddalena. "XML data stores: emerging practices." IEEE Internet Computing 9, no. 2 (2005): 62–69. http://dx.doi.org/10.1109/mic.2005.48.

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Ann Alexander, Cheryl, and Lidong Wang. "Cybersecurity Data Sources and Practices." Journal of Computer Networks 12, no. 1 (2024): 1–6. http://dx.doi.org/10.12691/jcn-12-1-1.

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13

Hickson, Susan, Kylie Ann Poulton, Maria Connor, Joanna Richardson, and Malcolm Wolski. "Modifying researchers’ data management practices." IFLA Journal 42, no. 4 (2016): 253–65. http://dx.doi.org/10.1177/0340035216673856.

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Data is the new buzzword in academic libraries, as policy increasingly mandates that data must be open and accessible, funders require formal data management plans, and institutions are implementing guidelines around best practice. Given concerns about the current data management practices of researchers, this paper reports on the initial findings from a project being undertaken at Griffith University to apply a conceptual (A-COM-B) framework to understanding researchers’ behaviour. The objective of the project is to encourage the use of institutionally endorsed solutions for research data man

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14

Scheel, Stephan, Evelyn Ruppert, and Funda Ustek-Spilda. "Enacting migration through data practices." Environment and Planning D: Society and Space 37, no. 4 (2019): 579–88. http://dx.doi.org/10.1177/0263775819865791.

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15

Watson, Hugh J., David A. Annino, Barbara H. Wixom, K. Liddell Avery, and Mathew Rutherford. "Current Practices in Data Warehousing." Information Systems Management 18, no. 1 (2001): 47–55. http://dx.doi.org/10.1201/1078/43194.18.1.20010101/31264.6.

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Dekker, Ron. "Social Data: CESSDA Best Practices." Data Intelligence 2, no. 1-2 (2020): 220–29. http://dx.doi.org/10.1162/dint_a_00044.

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The European Commission report “Turning FAIR into reality” provides an index of 27 FAIR Action Plan recommendations. This index is used for a self-assessment on CESSDA, the Consortium of European Social Science Data Archives. CESSDA is performing well on “Concepts for FAIR implementation”, “Skills for FAIR”, and “Investment in FAIR”; there is work in progress on “FAIR culture”, and work to start up on “FAIR ecosystem” and especially on “Incentives and metrics for FAIR data and services”. Next, an analysis on the FAIR components, reveals that CESSDA has accomplished the “F”, is working on the “

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17

Alter, George, and Richard Gonzalez. "Responsible practices for data sharing." American Psychologist 73, no. 2 (2018): 146–56. http://dx.doi.org/10.1037/amp0000258.

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Seidenwurm, David, and Jon Breslau. "Data-Driven Mammography Screening Practices." JAMA Oncology 4, no. 4 (2018): 587. http://dx.doi.org/10.1001/jamaoncol.2017.4069.

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19

Subaveerapandiyan, A., and Maurya Anuradha. "Research Data Preservation Practices of Library and Information Science Faculties." DESIDOC Journal of Library & Information Technology 42, no. 4 (2022): 259–64. https://doi.org/10.14429/djlit.42.4.17538.

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Digitisation of research data is widely increasing all around the world because it needs more and development of enormous digital technologies. Data curation services are starting to offer many libraries. Research data curation is the collective invaluable and reusable information of the researchers. Collected data preservation is more important. The majority of the higher education institutes preserved the research data for their students and researchers. It is stored for a long time using various formats. It is called research data preservation. Without proper research data management plan a

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20

Smith, Gavin JD. "Data doxa: The affective consequences of data practices." Big Data & Society 5, no. 1 (2018): 205395171775155. http://dx.doi.org/10.1177/2053951717751551.

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This paper explores the embedding of data producing technologies in people's everyday lives and practices. It traces how repeated encounters with digital data operate to naturalise these entities, while often blindsiding their agentive properties and the ways they get implicated in processes of exploitation and governance. I propose and develop the notion of ‘data doxa’ to conceptualise the way in which digital data – and the devices and platforms that stage data – have come to be perceived in Western societies as normal, necessary and enabling. The ‘data doxa’ concept also accentuates the enc

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Abhijit, Joshi. "The Rise of Data Lakes: Best Practices for Architecture and Value Extraction." Journal of Scientific and Engineering Research 5, no. 12 (2018): 342–47. https://doi.org/10.5281/zenodo.11667542.

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This whitepaper aims to elucidate the concept and strategic importance of data lakes, providing an in-depth technical exploration suitable for executives and technical stakeholders alike. Drawing upon established best practices derived from industry leaders and seasoned data experts at Cloudera, this document intends to demystify data lakes, advocating for their adoption based on proven principles rather than transient trends. Amidst the complexity and burgeoning volumes of business and analytical data, clarity on optimal data lake architectures and actionable strategies for extracting value i

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22

Vayyavur, Raj. "Best Practices for Data Governance and Architecture for Strategic Advancement." International Journal of Science and Research (IJSR) 12, no. 1 (2023): 1337–40. http://dx.doi.org/10.21275/sr24820003208.

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23

Mullapudi, Mahidhar, Aditya Vamsi Mamidi, and Mahesh Babu Munjala. "Operational Excellence: Best Practices for Monitoring in Data - Intensive Applications." International Journal of Science and Research (IJSR) 10, no. 3 (2021): 1950–55. http://dx.doi.org/10.21275/sr24203225052.

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24

Luo, Yuhan, Chi Young Oh, Beth St Jean, and Eun Kyoung Choe. "Interrelationships Between Patients’ Data Tracking Practices, Data Sharing Practices, and Health Literacy: Onsite Survey Study." Journal of Medical Internet Research 22, no. 12 (2020): e18937. http://dx.doi.org/10.2196/18937.

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Background Although the use of patient-generated data (PGD) in the optimization of patient care shows great promise, little is known about whether patients who track their PGD necessarily share the data with their clinicians. Meanwhile, health literacy—an important construct that captures an individual’s ability to manage their health and to engage with their health care providers—has often been neglected in prior studies focused on PGD tracking and sharing. To leverage the full potential of PGD, it is necessary to bridge the gap between patients’ data tracking and data sharing practices by fi

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Researcher. "UNDERSTANDING DATA MIGRATION: PROCESSES, TYPES, AND BEST PRACTICES." International Journal of Computer Engineering and Technology (IJCET) 15, no. 4 (2024): 882–96. https://doi.org/10.5281/zenodo.13609132.

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This comprehensive article explores the critical process of data migration in today's rapidly evolving digital landscape. It delves into the importance of data migration, its various types, popular tools, challenges in traditional techniques, and best practices for successful implementation. The article highlights how data migration has become a strategic imperative for organizations undergoing digital transformation, affecting business continuity, data integrity, compliance, cost management, and performance optimization. It provides insights into the growing data migration market, the shift t

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Sai, Kalyana Pranitha Buddiga. "The Importance of Data Cleaning in Machine Learning: Best Practices and Techniques." European Journal of Advances in Engineering and Technology 7, no. 10 (2020): 70–73. https://doi.org/10.5281/zenodo.12737222.

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This paper delves into the critical role of data cleaning in the success of machine learning projects. Clean, high-quality data is foundational to the performance and reliability of machine learning models. However, real-world datasets are often messy, containing errors, inconsistencies, missing values, and outliers. Data cleaning, also known as data preprocessing or data wrangling, involves identifying and rectifying these issues to ensure that the data is suitable for analysis and modeling. This paper discusses the importance of data cleaning in machine learning, explores common challenges a

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27

Van, Tuyl Steven, and Amanda Whitmire. "Investigation of Non-Academic Data Management Practices to Inform Academic Research Data Management." Research Ideas and Outcomes 4 (October 31, 2018): e30829. https://doi.org/10.3897/rio.4.e30829.

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In recent years, the academic research data management (RDM) community has worked closely with funding agencies, university administrators, and researchers to develop best practices for RDM. The RDM community, however, has spent relatively little time exploring best practices used in non-academic environments (industry, government, etc.) for management, preservation, and sharing of data. In this poster, we present the results of a project wherein we approached a number of non-academic corporations and institutions to discuss how data is managed in those organizations and discern what the acade

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28

Aiken, Peter, Mark Gillenson, Xihui Zhang, and David Rafner. "Data Management and Data Administration." Journal of Database Management 22, no. 3 (2011): 24–45. http://dx.doi.org/10.4018/jdm.2011070102.

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Data management (DM) has existed in conjunction with software development and the management of the full set of information technology (IT)-related components. However, it has been more than two decades since research into DM as it is practiced has been published. In this paper, the authors compare aspects of DM across a quarter-century timeline, obtaining data using comparable sets of subject matter experts. Using this information to observe the profession’s evolution, the authors have updated the understanding of DM as it is practiced, giving additional insight into DM, including its current

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Wang, Zhen, Guofu Wei, Yaling Zhan, and Yanhuan Sun. "Big data in telecommunication operators: data, platform and practices." Journal of Communications and Information Networks 2, no. 3 (2017): 78–91. http://dx.doi.org/10.1007/s41650-017-0010-1.

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30

Jiang, Shiyan, and Jennifer Kahn. "Data wrangling practices and collaborative interactions with aggregated data." International Journal of Computer-Supported Collaborative Learning 15, no. 3 (2020): 257–81. http://dx.doi.org/10.1007/s11412-020-09327-1.

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31

Robinson-García, Nicolas, Evaristo Jiménez-Contreras, and Daniel Torres-Salinas. "Analyzing data citation practices using the data citation index." Journal of the Association for Information Science and Technology 67, no. 12 (2015): 2964–75. http://dx.doi.org/10.1002/asi.23529.

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32

Duggan, Michael. "Navigational Mapping Practices: Contexts, Politics, Data." Westminster Papers in Communication and Culture 13, no. 2 (2018): 31–45. http://dx.doi.org/10.16997/wpcc.288.

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33

Bodner, Todd E. "Missing Data: Prevalence and Reporting Practices." Psychological Reports 99, no. 3 (2006): 675–80. http://dx.doi.org/10.2466/pr0.99.3.675-680.

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34

BODNER, TODD E. "MISSING DATA: PREVALENCE AND REPORTING PRACTICES." Psychological Reports 99, no. 7 (2006): 675. http://dx.doi.org/10.2466/pr0.99.7.675-680.

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35

Gouge, Catherine C., and Erin Brock Carlson. "Building Toward More Just Data Practices." IEEE Transactions on Professional Communication 65, no. 1 (2022): 241–54. http://dx.doi.org/10.1109/tpc.2021.3137675.

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36

Valcu, Mihai, and Cristina-Maria Valcu. "Data transformation practices in biomedical sciences." Nature Methods 8, no. 2 (2011): 104–5. http://dx.doi.org/10.1038/nmeth0211-104.

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37

Malik, P. "Governing Big Data: Principles and practices." IBM Journal of Research and Development 57, no. 3/4 (2013): 1:1–1:13. http://dx.doi.org/10.1147/jrd.2013.2241359.

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38

Bloom, Nicholas, Renata Lemos, Raffaella Sadun, Daniela Scur, and John Van Reenen. "International Data on Measuring Management Practices." American Economic Review 106, no. 5 (2016): 152–56. http://dx.doi.org/10.1257/aer.p20161058.

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We examine methods used to survey firms on their management and organizational practices. We contrast the strengths and weaknesses of “open ended questions” (like the World Management Survey) with “closed questions” (like the MOPS). For this type of data, open ended questions give higher quality responses, but are more costly than closed question-based surveys.

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Bollinger, Juli M., Abhi Sanka, Lena Dolman, Rachel G. Liao, and Robert Cook-Deegan. "BRCA1/2 Variant Data-Sharing Practices." Journal of Law, Medicine & Ethics 47, no. 1 (2019): 88–96. http://dx.doi.org/10.1177/1073110519840487.

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Accessing BRCA1/2 data facilitates the detection of disease-associated variants, which is critical to informing clinical management of risks. BRCA1/2 data sharing is complex and many practices exist. We describe current BRCA1/2 data-sharing practices, in the United States and globally, and discuss obstacles and incentives to sharing, based on 28 interviews with personnel at U.S. and non-U.S. clinical laboratories and databases. Our examination of the BRCA1/2 data-sharing landscape demonstrates strong support for and robust sharing of BRCA1/2 data around the world, increasing global accesses to

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40

Jackson, Alecia Youngblood. "Posthumanist data analysis of mangling practices." International Journal of Qualitative Studies in Education 26, no. 6 (2013): 741–48. http://dx.doi.org/10.1080/09518398.2013.788762.

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41

Falter, Kenneth H. "Data Quality Control: Theory and Practices." Journal of Quality Technology 25, no. 1 (1993): 62–63. http://dx.doi.org/10.1080/00224065.1993.11979418.

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42

Rahman, Nayem. "Enterprise Data Warehouse Governance Best Practices." International Journal of Knowledge-Based Organizations 6, no. 2 (2016): 21–37. http://dx.doi.org/10.4018/ijkbo.2016040102.

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Maintaining a stable data warehouse becomes quite a challenge if discipline is not applied to code development, code changes, code performance, system resource usage and configuration of integration specification. As the size of the data warehouse increases the value it brings to an organization tends to increase. However these benefits come at a cost of maintaining the applications and running the data warehouse efficiently on a twenty four hours a day and seven days a week basis. Governance is all about bringing discipline and control in the form of guidelines for application developers and

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43

Lee, Cindy S., Edward A. Sickles, and Elizabeth S. Burnside. "Data-Driven Mammography Screening Practices—Reply." JAMA Oncology 4, no. 4 (2018): 588. http://dx.doi.org/10.1001/jamaoncol.2017.4072.

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44

Martín-González, Yolanda, and Ana Iglesias-Rodríguez. "DATA LITERACY: PRACTICES AND TRAINING SCENARIOS." Revista EDICIC 3, no. 3 (2023): 1–15. http://dx.doi.org/10.62758/re.v3i3.202.

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Se considera la alfabetización en datos un concepto emergente o una línea de investigación novedosa que empodera al ciudadano en el contexto actual de la sociedad datificada al proporcionarle la formación necesaria para resolver problemas del mundo real y tomar decisiones basadas en datos. El individuo alfabetizado en datos es capaz de comprender, explicar, utilizar, interpretar, consumir y difundir -de manera crítica y eficaz- los datos, y convertirlos en información y en conocimiento. Este estudio se caracteriza por tener una naturaleza, fundamentalmente, cualitativa. En primer lugar, se des

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Tenopir, Carol, Carole L. Palmer, Lisa Metzer, Jeffrey van der Hoeven, and Jim Malone. "Sharing data: Practices, barriers, and incentives." Proceedings of the American Society for Information Science and Technology 48, no. 1 (2011): 1–4. http://dx.doi.org/10.1002/meet.2011.14504801026.

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Kanthed, Surbhi. "Energy-Saving Practices in Data Centers." International Journal of Multidisciplinary Research and Growth Evaluation 4, no. 5 (2023): 1149–55. https://doi.org/10.54660/.ijmrge.2023.4.5.1149-1155.

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Data centers are vital to the digital economy but consume significant amounts of electrical energy, highlighting the need for more sustainable operational practices. This paper examines contemporary energy-saving solutions for data centers, emphasizing empirical strategies rather than theoretical discussions. Key methods include advanced cooling approaches (e.g., hot/cold aisle containment, economizer-based “free cooling,” and liquid immersion cooling), server optimization techniques (such as virtualization, containerization, and intelligent power management), and improvements in power distrib

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Borghi, John, Stephen Abrams, Daniella Lowenberg, Stephanie Simms, and John Chodacki. "Support Your Data: A Research Data Management Guide for Researchers." Research Ideas and Outcomes 4 (May 9, 2018): e26439. https://doi.org/10.3897/rio.4.e26439.

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Researchers are faced with rapidly evolving expectations about how they should manage and share their data, code, and other research materials. To help them meet these expectations and generally manage and share their data more effectively, we are developing a suite of tools which we are currently referring to as "Support Your Data". These tools, which include a rubric designed to enable researchers to self-assess their current data management practices and a series of short guides which provide actionable information about how to advance practices as necessary or desired, are intended to be e

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Gries, Corinna, Stace Beaulieu, Renée Brown, et al. "Change in Pictures: Creating best practices in archiving ecological imagery for reuse." Biodiversity Information Science and Standards 4 (September 30, 2020): e59082. https://doi.org/10.3897/biss.4.59082.

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The research data repository of the Environmental Data Initiative (EDI) is building on over 30 years of data curation research and experience in the National Science Foundation-funded US Long-Term Ecological Research (LTER) Network. It provides mature functionalities, well established workflows, and now publishes all 'long-tail' environmental data. High quality scientific metadata are enforced through automatic checks against community developed rules and the Ecological Metadata Language (EML) standard. Although the EDI repository is far along in making its data findable, accessible, interoper

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49

Kumar Moka, Anil. "Comprehensive Approaches to Data Security: Threats, Best Practices, and Future Outlook." International Journal of Science and Research (IJSR) 13, no. 10 (2024): 1793–99. http://dx.doi.org/10.21275/sr241025160006.

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50

Katari, Abhilash. "Data Quality Management in Financial ETL Processes: Techniques and Best Practices." International Journal of Science and Research (IJSR) 8, no. 4 (2019): 2026–32. http://dx.doi.org/10.21275/sr24926100524.

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