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30 results for “data management plan”
OpenAIRE and FAIR Data Expert Group survey about Horizon 2020 template for Data Management Plans
<p>This dataset is published in 2017 by the OpenAIRE project and the FAIR Data Expert Group.</p> <p>It contains two survey data files, two pdf-files summarising the results in a report and an infographic, and a Readme.txt file.</p> <p>The OpenAIRE project supports the open science ambitions of the European Commission. The project and in particular the Research Data Management team provide support, training and information on the Open Research Data Pilot. In this context, a survey was carried out to collect feedback on the Horizon 2020 template for Data Management Plans (DMPs). The team collaborated with the FAIR data expert group, which is providing recommendations to the European Commission on turning FAIR data into reality. One of the specific tasks of the Expert Group is contributing to an evaluation of the Horizon 2020 approach to DMPs, including future revisions of the template and the development of additional sector/ discipline-specific guidance. The aim of the survey was to collect experiences of researchers and DMP reviewers with the DMP template and guidelines on FAIR data management in Horizon 2020. The survey assesses the usefulness of the guidelines and any aspects that are confusing and unclear to determine what improvements can be made.</p> <p>Feedback was sought from both researchers and research support staff. The survey was initially scheduled to run from 22 May to 21 June 2017. Several organisations were asked to help announce the survey, including OpenAIRE’s National Open Access Desks, the FAIR data expert group, FOSTER, LIBER, and the RDA Interest Group on Active DMPs. When the first survey responses showed only a small share of researchers, more stakeholders were contacted to specifically target this community. The European Research Area was approached, whose project officers circulated the survey call among award holders of EC projects. Early-career researchers were also informed through the YEAR network and EURODOC. This resulted in an extension of the survey to 21 July 2017.</p> <p>At the close of the survey on 21 July 2017, a total number of 289 responses were reached. 50% of the respondents indicated that they were researchers, and 60% that they were (also) research support staff. OpenAIRE and the FAIR data expert group are very pleased with this balanced outcome and would like to thank all colleagues and organisations who promoted the survey, as well as everyone who took part in it.</p> <p> </p>
Data Management Plan (DMP) Process Example
<p>This diagram is an example of a funding program solicitation mapped to the select key components of a data management plan, major data lifecycle process, infrastructure and resources, and proposed elements for sustainability of a funded research project. This diagram was developed out of a need to illustrate introductory DMP processes workflows for education, teaching, and training purposes. The DCC Checklist for a Data Management Plan (2013) and the USGS Data Lifecycle Model (2013) were adapted in this diagram.</p>
Assessing Quality Variations in Early Career Researchers' Data Management Plans: Quantitative Data of the Content Analysis
<p>The data includes the numerical results of the ranking of the data management plans created during the Basics of Research Data Management (BRDM) courses worth 3 ECTS credits in the years 2020 - 2022. The ranking was made using the Finnish DMP Evaluation Guidance (https://doi.org/10.5281/zenodo.4729831). Additionally, the data contains the results of the analysis of the best RDM practices included in the DMPs.</p> <p>Note 1: The comma-separated coded CSV version 1 (5.2.2024) may not open correctly on MacOS. You can use the comma-delimited CSV file version 2 or 3 (31.5.2024).</p> <p>Note 2: Versions 1 (Quality_variations_in_ECRs_DMPs_data) and 3 (Quality_variations_in_ECRs_DMPs_data_ver_3) contain evaluations of DMPs, best practices for data management, as well as methods for data sharing, storage, and preservation. In version 2 (Quality_variations_in_ECRs_DMPs_data_ver_2), the methods for data sharing, storage, and preservation are missing.</p> <p>Data is related to the research article https://doi.org/10.2218/ijdc.v18i1.873.</p>
Data Management Plan
<p>Video of a presentation for the training seminars in Research Data Management of the FoDaKo-project: <a href="https://fodako.de/">https://fodako.de</a></p>
Data From: Toward a Better Data Management Plan: The Impact of DMPs on Grant Funded Research Practices
<p>Researchers from Montana State University analyzed 186 National Science Foundation (NSF) data management plans, using the Data Management Plans As a Research Tool (DART) rubric.</p>
Data management planning - Training for trainers, part I-III: answers to per-assignments
<p>The data have been collected as part of data management planning training for trainers. Data consists participants answers to pre-assignments.</p> <p>Consent for data sharing</p> <ul> <li>First session: Consent for datat sharing was asked afterwards by email</li> <li>Second and third session: Consent was asked when collecting answers on the e-form.</li> </ul> <p>The slides of the DMP training fro trainers is available on SlideShare:</p> <ul> <li>Session I: <a href="https://www2.slideshare.net/MariKuusniemi/part-i-data-management-planning-training-for-trainers">https://www2.slideshare.net/MariKuusniemi/part-i-data-management-planning-training-for-trainers</a></li> <li>Session II: <a href="https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-ii">https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-ii</a></li> <li>Session III: <a href="https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-iii">https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-iii</a></li> </ul> <p>The training was organised by Tuuli Office.</p>
Investigating Data Assets, Management, and Planning at UF
<p>This dataset represents a data assessment of select researchers across multiple communities of practice at the University of Florida as part of an IRB 201602303 study to investigate the data management practices, storage, and training needs of researchers. The study was conducted from January 3, 2017 - April 30, 2017. One hundred fifty-nine starts, one hundred fifty-six informed consent, and one hundred thirty-three completes for a 83% completion. However, Question 26 which contained PID was deleted from this raw dataset.</p>
Guidelines for Data Management Plan implementation of One Health EJP projects: Webinar held on the 19th December 2018
<p>Webinar held on the 19th December 2018 to introduce Data Management Plan to scientists involved in the research and integrative projects of One Health European Joint Program.</p>
Data Management Plan preliminary version (D1.3)
<p>First version of the Data Management Plan, to be updated twice in the project</p>
Aligning Data Management Plans with Community Standards using FAIR Implementation Profiles
<p>Here you can find the files corresponding to our submission titled 'Aligning DMPs with Community Standards using FIPs'.</p> <p>- VU DMP template and the mapping is included in the folder /VU-DMP-template-and-mapping</p> <p>- All the FAIR Implementation Profiles are included in the folder /FIPs.</p> <p>- The knowledge model we created for the project, and a small demo of the interface are in the folder /KM-and-demo.</p> <p>- The folder /user-study consists of the following:</p> <p> a) The mock DMPs we provided to the participants of this research are in /mock_DMPs.</p> <p> b) We downloaded the resulting DMPs after participants completed their DMPs, they are in the folder /resulting_DMPs.</p> <p> c) Survey results can be found in the folder /survey_results.</p> <p> d) Some Python scripts were used for the analysis of the survey results. They are in the folder /Python_script_for_analysis.</p> <p><br>The project is open source under the license CC-BY 4.0.</p> <p>Contact: Shuai Wang (shuai.wang@vu.nl)</p> <p> </p>
Uncommon Commons? Creative Commons licencing in Horizon 2020 Data Management Plans
<p>As policies, good practices and funder mandates on research data management evolve, more emphasis has been put on the licencing of data. Licencing information allow potential re-users to quickly identify what they can do with the data in question and is therefore an important component to ensure the reusability of research.</p> <p>In my research I analyse a pre-existing collection of 840 Horizon 2020 public data management plans (DMPs) available on the repository of the University of Vienna, Phaidra,, to determine which ones mention creative commons licences and among those who do, what licences are being used.</p> <p>This excel file contains the data underlying the publication "Uncommon Commons? Creative Commons licencing in Horizon 2020 Data Management Plans ".</p> <p>Sheet 1 contains the data collected in the previous "Data Re-Use" project: 840 DMPs downloaded from CORDIS and vetted to ensure they are public documents and not copyrighted</p> <p>Sheet 2 contains the same data as sheet 1, with columns D to Q not visible (for better reading) but an added column R which now contains the CC licening information (where available)</p> <p>Sheet 3 is filtered so that only the projects containing CC BY relevant licencing are shown</p> <p>Sheet 4 is filtered so that only the projects containing CC-BY-SA relevant licencing are shown</p> <p>Sheet 5 is filtered so that only the projects containing CC-BY-NC relevant licencing are shown</p> <p>Sheet 6 is filtered so that only the projects containing CC-BY-ND relevant licencing are shown</p> <p>Sheet 7 is filtered so that only the projects containing Cc-BY-NC-ND relevant licencing are shown</p> <p>Sheet 8 is filtered so that only the projects containing CC-BY-NC-SA relevant licencing are shown</p> <p>Sheet 9 is filtered so that only the projects containing CC0 relevant information are shown</p> <p>Sheet 10 provides an overview table of the relevant licences (manual entry)</p> <p>Sheet 11 and 12 contain graphic visulations of the data as used in the article</p>
Data Management Plan: FNS Project "Le scénario chez Alain Tanner : discours et pratiques. Une approche génétique du récit filmique et des représentations de genre"
<p>Le présent projet entend investiguer, sur la base principalement des archives personnelles d’Alain Tanner déposées à la Cinémathèque suisse (CS), la genèse des dix-neuf longs métrages de fiction réalisés par le cinéaste suisse romand entre 1969 (<em>Charles mort ou vif</em>) et 2004 (<em>Paul s’en va</em>) en optant pour une méthodologie relevant de l’étude génétique des textes scénaristiques. </p> <p>Parallèlement à l’étude des archives de production qui nous renseignent sur les pratiques d’écriture, nous envisageons le discours tenu à propos du scénario par Tanner, l’un des cinéastes suisses à avoir bénéficié d’une importante reconnaissance internationale et exercé un impact considérable sur la manière dont le cinéma a été conçu dans son pays. Nous postulons que le « scénario » se situe au cœur de l’œuvre du cinéaste dans la mesure où ce dernier a constamment entretenu un rapport ambivalent à ce stade de la fabrication de ses films : alors qu’il n’a eu de cesse de relativiser le rôle de l’écriture au profit de la mise en scène, il a par ailleurs constamment problématisé, dans ses prises de position publiques et ses nombreux textes de réflexion sur sa pratique, la question de l’écriture. La constitution d’un historique de production de l’ensemble des longs métrages que Tanner a réalisés, (co)produits et (co)écrits, ainsi qu’une étude comparative des états et variantes de scénario entre eux et avec les différents films tels qu’ils ont été exploités sont ainsi corrélés à l’ensemble des discours sur le cinéma qui ont été émis par Tanner à travers divers canaux médiatiques, ainsi qu’avec la réception critique de ses films qui s’est fait l’écho de son discours et a commenté son travail. L’engagement institutionnel de Tanner dans les années 1960 ainsi que sa visibilité médiatique tout au long de sa carrière permettront d’offrir un éclairage plus large sur l’histoire du cinéma suisse de fiction. </p> <p>La genèse des scénarios de Tanner sera en particulier envisagée dans ce que leur étude apporte sur un plan méthodologique à la génétique des textes, et dans la manière dont ceux-ci s’appuient sur du matériel antérieur (romans pour ses deux adaptations, journaux intimes, faits divers, photographies, cartes géographiques, etc.), programment différents aspects du film à venir (dialogues, mouvement d’appareil, montage, jeu d’acteur, bande-sons, etc.) et résultent d’une écriture collaborative. A ce titre, trois personnalités ayant travaillé successivement comme coscénariste sur des films de Tanner et stimulé sa réflexion sur le cinéma font l’objet d’une étude : le critique d’art John Berger, l’actrice et chanteuse Myriam Mézières et enfin le romancier et figure du monde des lettres et des médias Bernard Comment. Les modalités de la création à quatre mains sont discutées dans une perspective double : (1) une étude narratologique (la construction du récit et des personnages, le processus de l’adaptation, etc.) ; (2) une étude des représentations genrées. Sur ces deux plans, nous avons l’ambition de montrer, en dépit d’ambivalences diverses, combien le cinéma de Tanner se distingue de la production dominante et même du cinéma d’auteur francophone post-Nouvelle Vague par une originalité certaine qui demeure à ce jour trop peu discutée dans l’histoire du cinéma (suisse). L’étude de ce corpus se prête à affiner l’approche génétique en l’adaptant à l’hétérogénéité et au non-conformisme des pratiques de Tanner. </p> <p> </p> <p> </p>
Data Management Plan for PsyCoMed
<p>Ongoing Data management plan for PsyCoMed 14-06-2024</p>
D1.2 Data Management Plan (DMP)
<p>This deliverable constitutes the Data Management Plan (DMP) of the NANOFACTS project. It is the first version of DMP, describing data management life cycle for all research and publication data. This deliverable is introducing ways to produce, collect, process, save, exchange, share, and publish research data in line with the EC “Guidelines on FAIR Data Management in Horizon 2020”.</p>
Data from: Data management plan (DMP): Towards a more efficient scientific management at the Universidad Centroamericana José Simeón Cañas
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Data from: Incorporating uncertainty into forest management planning: timber harvest, wildfire and climate change in the boreal forest
In an effort to ensure the sustainability of their forests, boreal forest managers often use forest planning models to make future projections of timber supply and other key services, such as habitat for wildlife. Projecting the fate of these services has proven to be challenging, however, as major uncertainties exist regarding the principal drivers of boreal ecosystem dynamics, including the future spatial and temporal distribution of wildfire and timber harvesting. Existing forest planning models are not well suited to dealing with this uncertainty because they produce deterministic projections based on central tendencies of these drivers. Here we present a new approach for incorporating uncertainty into forest management planning, which we demonstrate using two landscapes in the Canadian boreal forest. Our approach takes the assumptions contained within the latest forest management plans for each of these landscapes, including parameterizations of their deterministic forest planning models, and converts these assumptions into equivalent parameterizations of a stochastic, spatially-explicit state-and-transition simulation model (STSM). We then use Monte Carlo simulations with the STSM to "stress-test" the forest management plan with respect to a range of possible future uncertainties, including uncertainties in future levels and patterns of wildfire and timber harvest, along with the possible changes in wildfire that might result from future climate change. Our analysis demonstrates the importance of incorporating stochastic variability into projections of future ecosystem condition. The STSM projections that acknowledged variability in wildfire and timber harvest differed from the deterministic forest planning model projections that were based solely on mean values. Our analysis also suggests that there is an increased risk of shortfalls in timber harvest, for both boreal landscapes, associated with future projections for changes in wildfire due to climate change, and that management strategies aimed at reducing the future level of timber harvest offer an opportunity to mitigate these risks. We believe our approach provides a new risk-based framework for incorporating uncertainty into forest management, including the effects of climate change.
Data Management Plan (final): SPPELME
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Technology Acquisition Plans to Foster Supply Chain Risk Management Learning Outcomes in Project-Based Software Development Courses: Raw Data and TAP Template
<p>This is a data set and TAP template to accompany the paper</p> <p>"Technology Acquisition Plans to Foster<span> </span>Supply Chain Risk Management Learning Outcomes in Project-Based Software Development Courses" by Tenbergen and Mead published at the 36th International Conference on Software Engineering Education and Training.</p>
Data Management Plan (DMP)v2
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WORLDCOM Data Management Plan
<p>Data Management Plan for the OHEJP WorldCOM project.</p>
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