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The Value of a Data and Digital Object Management Plan (D(DO)MP) in Fostering Sharing Practices in a Multidisciplinary Multinational Project 数据和数字对象管理计划(D(DO)MP)在促进多学科跨国项目共享实践中的价值

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-038

Alison Specht, Margaret O’Brien, Rorie Edmunds, Pedro Corrêa, Romain David, Laurence Mabile, Jeaneth Machicao, Yasuhiro Murayama, Shelley Stall

{"title":"The Value of a Data and Digital Object Management Plan (D(DO)MP) in Fostering Sharing Practices in a Multidisciplinary Multinational Project","authors":"Alison Specht, Margaret O’Brien, Rorie Edmunds, Pedro Corrêa, Romain David, Laurence Mabile, Jeaneth Machicao, Yasuhiro Murayama, Shelley Stall","doi":"10.5334/dsj-2023-038","DOIUrl":"https://doi.org/10.5334/dsj-2023-038","url":null,"abstract":"Data Management Plans (DMP) are now a routine part of research proposals but are generally not referred to after funding is granted. The Belmont Forum requires an extensive document, a ‘Data and Digital Object Management Plan’ (D(DO)MP) for its awarded projects that is expected to be kept current over the life of the project. The D(DO)MP is intended to record team decisions about major tools and practices to be used over the life of the project for data and software stewardship, and for preservation of data and software products, aligned with the desired Open Science outcomes relevant to the project. Here we present one of the first instances of the use of Belmont’s D(DO)MP through a case study of the PARSEC project, a multinational and multidisciplinary investigation of the socioeconomic impacts of protected areas. We describe the development and revision of our interpretation of the D(DO)MP and discuss its adoption and acceptance by our research group. We periodically assessed the data management sophistication of team members and their use of the various nominated tools and practices. As a result, for example, we included summaries to enable the key components of the D(DO)MP to be readily viewed by the researcher. To meet the Open Science outcomes in a complex project like PARSEC, a comprehensive and appropriately structured D(DO)MP helps project leaders (a) ensure that team members are committed to the collaboration goals of the project, (b) that there is regular and effective feedback within the team, (c) training in new tools is provided as and when needed, and (d) there is easy access to a short reference to the tools and descriptions of the nominated practices.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136006037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Benefits and Challenges: Data Management Plans in Two Collaborative Projects 利益与挑战:两个协作项目中的数据管理计划

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-025

Denise Jäckel, Anna Lehmann

{"title":"Benefits and Challenges: Data Management Plans in Two Collaborative Projects","authors":"Denise Jäckel, Anna Lehmann","doi":"10.5334/dsj-2023-025","DOIUrl":"https://doi.org/10.5334/dsj-2023-025","url":null,"abstract":"The data-driven shift in the science research leads to a wider range of research data. To manage this data in a sustainable and adequate way, data management plans (DMPs) were established as a method. However, some researchers still do not create DMPs due to lack of time, resources and understanding of the needs. Furthermore, most of the existing templates and tools are largely unknown. In this article, we investigated the benefits and challenges of DMPs in two joint research projects of several academic institutions. For this, we described the process during the DMP creation, potential challenges and benefits experienced. We showed that a DMP with completely uniform content among the partner institutions was not possible due to individual and subject differences (e.g., in storage and policies). Instead, individual texts had to be formulated in some cases to overcome the diversity. This complexity could not be handled with the existing tools. Therefore, both projects created an own adapted template with some generic contents. Existing guidelines and internal project policies helped during the generation. We experienced that fewer people work more efficiently on a DMP than many and that all researchers within the project can profit from every individual DMP. Although we were not required to produce one, we recognised the associated benefits as a guide during the research process in joint projects.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71068516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

ENEA PAES: A Web Platform for Supporting Italian Municipalities in Sustainable Energy Action Plan ENEA PAES:支持意大利市政当局实施可持续能源行动计划的网络平台

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-037

Fabio Cignini, Enrico Cosimi, Vittoria Cozza, Flavio Fontana, Maurizio Matera, Giangiacomo Ponzo, Maria Salvato, Veronica Tomassetti

{"title":"ENEA PAES: A Web Platform for Supporting Italian Municipalities in Sustainable Energy Action Plan","authors":"Fabio Cignini, Enrico Cosimi, Vittoria Cozza, Flavio Fontana, Maurizio Matera, Giangiacomo Ponzo, Maria Salvato, Veronica Tomassetti","doi":"10.5334/dsj-2023-037","DOIUrl":"https://doi.org/10.5334/dsj-2023-037","url":null,"abstract":"The Covenant of Mayors promotes the Sustainable Energy Action Plan (SEAP), aiming to mitigate greenhouse gas (GHG) emissions in line with the European Union’s 2030 and 2050 targets. The Covenant signatories could take enormous advantage from a digital platform that allows SEAP drafting also to no technically skilled users, like majority of them are. The Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) has developed the PAES platform in order to provide digital support to public administrations (PA) adhering to the Covenant of Mayors. The platform exploits open data and it is fed by energetic data aggregated on a municipal level. The platform offers appropriate functionalities for baseline CO2 emissions inventory (BEI) filling out and a best practice (BP) simulation tool. The latter allows to contextualize each BP and to estimate its effects in terms of the main GHG emission. The BP showing the best estimation results can then be converted into concrete adaptation actions. So, this digital system facilitates local Italian municipalities in the strategic planning and monitoring of adaptation actions taken over time.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135845686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation of a Federated Information System by Means of Reuse of Research Data Archived in Research Data Repositories 利用研究数据存储库中存档研究数据的重用实现联邦信息系统

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-039

Sylvia Melzer, Stefan Thiemann, Simon Schiff, Ralf Möller

{"title":"Implementation of a Federated Information System by Means of Reuse of Research Data Archived in Research Data Repositories","authors":"Sylvia Melzer, Stefan Thiemann, Simon Schiff, Ralf Möller","doi":"10.5334/dsj-2023-039","DOIUrl":"https://doi.org/10.5334/dsj-2023-039","url":null,"abstract":"At universities, research data is increasingly stored in research data repositories according to a data management plan (DMP) and thus made available for further use. The challenge of reusing hundreds, thousands, or millions of data sets is to obtain an overview of the data in a short period of time and to search through all the data. The high variability of the formats used to store research data requires a new approach to data reusability that focuses on the visualisation and searchability of archived research data, which can also be combined with each other. In this article, we present a practical DMP that describes how information systems can be created on demand by reusing research data archived in research data repositories and how these systems can be merged into a federated information system. As a result, in our projects, information systems have been created in minutes or a couple of hours with few resources. The initial effort to create a federated system remains; however, this allows federated searches to be performed. Extending a federated system to include other information systems can then be accomplished by making a few configurations and manageable adjustments to the source code.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136303138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Programmatic and Scalable Approach to Making Data Management Machine-Actionable 使数据管理机器可操作的程序化和可扩展方法

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-026

M. Praetzellis, M. Buys, Xiaoli Chen, J. Chodacki, N. Davies, Kristian Garza, Catherine Nancarrow, Brian Riley, E. Robinson

引用次数: 0

Data Science in a Pandemic 大流行中的数据科学

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-041

Dennis F. X. Mathaisel

{"title":"Data Science in a Pandemic","authors":"Dennis F. X. Mathaisel","doi":"10.5334/dsj-2023-041","DOIUrl":"https://doi.org/10.5334/dsj-2023-041","url":null,"abstract":"Data Science has the potential to provide humanity with critical insight into the massive data being collected during a pandemic. The COVID-19 pandemic presented that opportunity, and Data Science supported an international audience promptly, reliably, effectively, and frequently during that difficult time. The most significant contributions were data visualizations and data dashboards, however, other tools, such as predictive and prescriptive analytics, were equally critical to the effort. The urgency at the start of the pandemic was to quickly communicate information to citizens, governments, and institutions. The change in modality from traditional statistical metrics and tables to data visualizations was extremely significant and helpful to so many. This paper reviews these contributions by demonstrating how the COVID-19 story unfolded through author-generated data visualizations and dashboards, and by providing the community with open-source access to the scripts that generated these visualizations. The open-source access to the (R language) scripts reflects this article’s novelty in the literature. Using publicly available datasets from multiple sources, and employing R toolkits, the author validates the role that Data Science can play in a pandemic, and that can be implemented by anyone with some basic knowledge of scripting languages, like R. The intent is to provide these valuable tools to the community and to demonstrate their effectiveness in the likely event when there is another crisis.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135261934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards a Toolbox for Automated Assessment of Machine-Actionable Data Management Plans 面向机器可操作数据管理计划自动评估的工具箱

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-028

Tomasz Miksa, M. Suchánek, Jan Slifka, Vojtěch Knaisl, F. Ekaputra, Filip Kovacevic, Annisa Maulida Ningtyas, Alaa El-Ebshihy, R. Pergl

引用次数: 1

Implementing Informatics Tools with Data Management Plans for Disease Area Research 实施信息学工具与疾病领域研究的数据管理计划

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-024

V. Navale, Matthew McAuliffe

引用次数: 0

Data Management Plan Implementation, Assessments, and Evaluations: Implications and Recommendations 数据管理计划的实施、评估和评价:影响和建议

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-027

B. Bishop, Peter Neish, Ji Hyun Kim, Raphaëlle Bats, Anthony J. Million, Jake Carlson, Heather Moulaison Sandy, Minh T. Pham

引用次数: 0

Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST) 通过FAIR+实施调查工具(FAIRIST)与研究人员互动，提高对公平和开放科学的认识

Data Science Journal Pub Date : 2023-01-01 DOI: 10.5334/dsj-2023-032

Christine R. Kirkpatrick, Kevin Coakley, Julianne Christopher, Inês Dutra

{"title":"Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST)","authors":"Christine R. Kirkpatrick, Kevin Coakley, Julianne Christopher, Inês Dutra","doi":"10.5334/dsj-2023-032","DOIUrl":"https://doi.org/10.5334/dsj-2023-032","url":null,"abstract":"Seven years after the seminal paper on FAIR was published, that introduced the concept of making research outputs Findable, Accessible, Interoperable, and Reusable, researchers still struggle to understand how to implement the principles. For many researchers, FAIR promises long-term benefits for near-term effort, requires skills not yet acquired, and is one more thing in a long list of unfunded mandates and onerous requirements for scientists. Even for those required to, or who are convinced that they must make time for FAIR research practices, their preference is for just-in-time advice properly sized to the scientific artifacts and process. Because of the generality of most FAIR implementation guidance, it is difficult for a researcher to adjust to the advice according to their situation. Technological advances, especially in the area of artificial intelligence (AI) and machine learning (ML), complicate FAIR adoption, as researchers and data stewards ponder how to make software, workflows, and models FAIR and reproducible. The FAIR+ Implementation Survey Tool (FAIRIST) mitigates the problem by integrating research requirements with research proposals in a systematic way. FAIRIST factors in new scholarly outputs, such as nanopublications and notebooks, and the various research artifacts related to AI research (data, models, workflows, and benchmarks). Researchers step through a self-serve survey process and receive a table ready for use in their data management plan (DMP) and/or work plan. while gaining awareness of the FAIR Principles and Open Science concepts. FAIRIST is a model that uses part of the proposal process as a way to do outreach, raise awareness of FAIR dimensions and considerations, while providing timely assistance for competitive proposals.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134988993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0