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213 results for “Research management”
Skills and Competency Framework for Research Community Managers (Figure)
<p><strong><span>Figure 3: RCM Skills and Competency Framework: </span></strong><span>This figure illustrates a framework comprising five overarching competencies, described with 13 skills each. A total of 65 skills are categorised into core competencies in communications and engagement, and peripheral competencies in strategic contributions, technical skills, and accountability. </span></p>
Community Maturation Matrix (Illustration): Professionalising Community Management Roles in Interdisciplinary Research Projects
<p>Figure 1 (.jpg) file, editable version (.pptx) and supplementary 1 (.xlsx) for the research article: Professionalising Community Management Roles in Interdisciplinary Research Projects (July, 2024)</p> <p>Figure 1: Community Maturation Indicator: This is a framework through which maturation status for a community can be indicated at any given time as “Level of Community Participation” and “Stage of Community Building”. The Levels of Community Participation is shown in the x-axis (spanning 6 levels): Level 1: Inform Community, Level 2: Invite Feedback, Level 3: Engage and Involve, Level 4: Mobilise and Connect, Level 5: Empower Groups, and Level 6: Decentralise Power. The Stages of Community Building are shown as y-axis (spanning 6 stages): Stage 1: Initiation, Stage 2: Planning and Design, Stage 3: Implementation, Stage 4: Growth and Scaling, Stage 5: Monitoring and Evaluation, and Stage 6: Sustainability or Sunsetting. </p> <p>Supplementary 1: An example of how a community may progress its maturation levels. After the level has been identified, a CoP can start applying targeted approaches to community building, which occurs in stages. For example, at the community initiation stage of a new CoP, an RCM shares information and communicates project goals (Stage 1); at the planning and design stage, they build stakeholder awareness plans and help to prioritise specific objectives (Stage 2); at the implementation stage, they provide collaborative opportunities for specific stakeholders (Stage 3); at the growth stage, they facilitate knowledge exchange and skill building (Stage 4); and at the evaluation stage, it assesses the success of the CoP through feedback data to inform plans (Stage 5). These stages collectively affect how the project and its community can be sustained in the future or whether it should be paused (sunsetting) (Stage 6). RCMs build effective community strategies and implement creative approaches to support the development of a CoP, advancing a community from one stage to the next (Supplementary 1, Column 1 of the Community Maturation Indicators).</p> <p> </p>
Introduction to Research Data Management for Ecologists Distributed Graduate Seminar
<p>This video was made to introduce students who had registered for the Spring 2021 <em>Research Data Management for Ecologists</em> distributed graduate seminar that was offered at Florida International University, University of New Mexico, and University of Wisconsin, Madison.</p>
Data for: A new GTSeq resource to facilitate multijurisdictional research and management of walleye Sander vitreus
<p>Conservation and management professionals often work across jurisdictional boundaries to identify broad ecological patterns. These collaborations help to protect populations whose distributions span political borders. One common limitation to multijurisdictional collaboration is consistency in data recording and reporting. This limitation can impact genetic research which relies on data about specific markers in an organism's genome. Incomplete overlap of markers between separate studies can prevent direct comparisons of results. Standardized marker panels can reduce the impact of this issue and provide a common starting place for new research. Genotyping-in-thousands (GTSeq) is one approach used to create standardized marker panels for non-model organisms. Here we describe the development, optimization, and early assessments of a new GTSeq panel for use with walleye (<em>Sander vitreus</em>) from the Great Lakes region of North America. High genome-coverage sequencing conducted using RAD-capture provided genotypes for thousands of single nucleotide polymorphisms (SNPs). From these markers, SNP and microhaplotype markers were chosen that were informative for genetic stock identification (GSI) and kinship analysis. The final GTSeq panel contained 500 markers, including 197 microhaplotypes and 303 SNPs. Leave-one-out GSI simulations indicated that GSI accuracy should be greater than 80% in most jurisdictions. The false positive rates of parent-offspring and full-sibling kinship identification was found to be low. Finally, genotypes could be consistently scored among separate sequencing runs >94% of the time. Results indicate that the GTSeq panel that we developed should perform well for multijurisdictional walleye research throughout the Great Lakes region.</p>
Dataset for paper entitled "Thirty Three Years of Research about the Relation between Management and Business Strategy in Islamic Way"
<p>This is dataset of papers collected from Scopus that was related to business, strategy, and management in accordance to Islamic way. It contains CSV and Bibtex version. </p>
Researcher effects on the biological structure and edaphic conditions of field sites and implications for management
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Data Management and Sharing: Practices and Perceptions of Psychology Researchers
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Data from: Phosphorus budgets of intensively managed row crops at a long-term agroecosystem research site in the upper US Midwest
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Data and code from: Public participation in tropical conservation and environmental management research: Towards a locally grounded and reflexive practice
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Case study data of the paper: A methodological guide to observe local-scale geodiversity for biodiversity research and management
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Data for: A new GTSeq resource to facilitate multijurisdictional research and management of walleye Sander vitreus
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Bashar H. Malkawi, Knowledge Management Research and practice
<p>Editorial Board Member, Knowledge Management Research and practice</p>
Supplementary material 3 from: Petersen M, Pramann B, Toepfer R, Neumann J, Enke H, Hoffmann J, Mauer R (2020) Research Data Management - Current status and future challenges for German non-university research institutions. Research Ideas and Outcomes 6: e55141. https://doi.org/10.3897/rio.6.e55141
Praxisbericht: Entwicklung eines Maßnahmenkatalogs zur Verbesserung des Forschungsdatenmanagements am Herder-Institut für historische Ostmitteleuropaforschung
Humboldt-Universität zu Berlin Research Data Management Survey Results. Comparing respondent groups "Professor" and "Research associate"
<p>This spreadsheet represents results of the research data management survey at Humboldt-Universität zu Berlin, comparing respondents groups "Professor" and "Research associate".</p>
Humboldt-Universität zu Berlin Research Data Management Survey Results
<p>This spreadsheet represents anonymized summary results of the research data management survey at Humboldt-Universität zu Berlin.</p>
The Role of Research University Libraries in Research Data Management: The Case of Türkiye
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Establishing Technical Debt Management - A Five-Step Workshop Approach and an Action Research Study
<div> <div>The additional material for the paper "Establishing Technical Debt Management - A Five-Step Workshop Approach and an Action Research Study" comprises the following documents:</div> <div> </div> <div>* Guideline_to_Use_TD-SAGAT.docx (.pdf)</div> <div> A short guideline on how to use the TD-SAGAT method.</div> <div>* SAGAT_for_TD_from_Goals_to_Queries.pdf</div> <div> Determination of survey questions by following the SAGAT approach of following the hierarchy of goals, subgoals, decisions, requirements, and queries </div> <div>* WIKI page on technical debt.pdf</div> <div> The teams' wiki page on TD management written by the TD manager</div> <div>* AzureTDTickets_Template.pdf</div> <div> Screenshot of the backlog's TD item template as presented in the paper for better readability.</div> <div>* OverviewOfActionCycles_ExtendedTable5.xlsx</div> <div> Table 5 (Overview of actions cycles with workshop topics, TD activities, actions taken, and learning) as an Excel sheet with additional information on actions and learning, which we did not put into the paper</div> <div> </div> <div>* Workshops/workshop_slides/TDMGuide_<x>_Workshop.pptx</div> <div> Slides for each of the six workshops </div> <div>* Workshops/workshop_slides/TDMGuide_0_InitTalk_35Min_EN.pptx</div> <div> The initial one-hour introduction into the TD topic (~40 min. talk + 20 min. for a short discussion) </div> <div> </div> <div>* Workshops/workshop_flipcharts/WS<No.>_<explanation>.jpg</div> <div> Six anonymized flipchart photos to give an impression of the workshops, particularly of the kick-off workshop (other workshops made less use of flipcharts).</div> <div> Translations are directly included in the photos, except for ...</div> <div>* Workshops/workshop_flipcharts/WS1_Topic Cache - Translation.txt</div> <div> Translation of the German topic cache in an extra file, as there were too many topics to translate in the photo</div> <div> </div> <div>* Workshops/Workshop Agendas.pdf</div> <div>Agendas for the kick-off workshop and a general agenda for further workshops, each with a detailed agenda for workshop moderators and a rough agenda for participants.</div> <div> </div> <div>* Workshops/ TD_Energy_Matrix.xlsx</div> <div> Matrix where participants mark their own, the teams, and the companies' (assumed) level of willingness to invest in a TDM versus their (assumed) evaluation of TDM's importance. Used in kickoff workshop</div> <div> </div> <div> </div> <div>* Evaluations/Backlog_Evaluations_and_Figures.xlsx</div> <div>- Backlog data from the 5th workshop (for 6th workshop, we used the PowerBI Visualization instead)</div> <div>- Evaluation of this data comprising </div> <div>- priority calculations based on priority risk and </div> <div>- priority calculations based on priority risk based on ROI</div> <div> </div> <div>* Evaluations/Meetings_Overview_Observations_Evaluation_Figures.xlsx</div> <div>- Overview of all meetings plus information on length, participants, whether a video exists and was used for evaluation</div> <div>- Filled out observation protocols from different meetings</div> <div>- Summation, evaluations, and resulting figures</div> <div> </div> <div>* Evaluations/TD-SAGAT_Survey_and_SurveyResults_Figures.xlsx</div> <div>- Survey questions for TD-SAGAT plus results</div> <div>- Evaluation plus figures</div> <div> </div> <div>* Evaluations/Workshop_Survey_and_SurveyResults_Figures.xlsx</div> <div>- Survey questions for Workshops plus results</div> <div>- Evaluation plus figures</div> <div> </div> <div>* Evaluations/Kickoff_Survey_and_SurveyResults.xlsx</div> <div>- Survey questions for Kickoff Workshops (incl. questions on current TDM process) plus results</div> <div>- Evaluation in Workshop_Survey_and_SurveyResults_Figures.xslx</div> <div> </div> <div> </div> <div>* Visualizations/V<No.>_<adopted|mockup>_<explanation>.png</div> <div>- "adopted" visualizations are similarly presented in the paper in Fig. 2.</div> <div>- "mockup" visualizations were presented during the workshops but not adopted in this form. </div> <div>If a respective "adopted" visualization for this No. exists, the visualisation was replaced by a more suitable one. </div> <div>If no respective "adopted" visualization for this No. exists, the visualisation was discarded.</div> <div> </div> <div> </div> <div>* Visualizations/Dashboard <Manager|Team>.png</div> <div>- shows the dashboard mockups for the manager and the team, respectively. </div> <div>Visualizations presented in the dashboards that were not adopted by the team were removed or replaced by the improved visualizations in the final dashboard versions.</div> <div> </div> <div> </div> <div> </div> <div> </div> </div>
Supplementary material 1 from: Petza D, Anastopoulos P, Coll M, Garcia SM, Kaiser M, Kalogirou S, Lourdi I, Rice J, Sciberras M, Katsanevakis S (2021) The contribution of Area-Based Fisheries Management Measures to Fisheries Sustainability and Marine Conservation: a global scoping review protocol. Research Ideas and Outcomes 7: e70486. https://doi.org/10.3897/rio.7.e70486
The contribution of Area-Based Fisheries Management Measures to Fisheries Sustainability and Marine Conservation: a global scoping review protocol - Search Strategy
Supplementary material 2 from: Petza D, Anastopoulos P, Coll M, Garcia SM, Kaiser M, Kalogirou S, Lourdi I, Rice J, Sciberras M, Katsanevakis S (2021) The contribution of Area-Based Fisheries Management Measures to Fisheries Sustainability and Marine Conservation: a global scoping review protocol. Research Ideas and Outcomes 7: e70486. https://doi.org/10.3897/rio.7.e70486
The contribution of Area-Based Fisheries' Management Measures to Fisheries Sustainability and Marine Conservation: a global scoping review protocol - Data Extraction Tool
Conspecific attraction for conservation and management of terrestrial breeding birds: current knowledge and future research directions
<p>Conspecific presence can indicate the location or quality of resources, and animals settling near conspecifics often gain fitness benefits. This can result in adaptive conspecific attraction during breeding habitat selection as demonstrated in numerous terrestrial, territorial birds. There is growing interest in using simulated conspecific social cues (e.g., decoys, broadcasted vocalizations) to manage bird distributions, yet it remains unclear when this approach is likely to succeed. We reviewed published studies to evaluate whether the strength of conspecific attraction in terrestrial birds is mediated by characteristics of species (life history traits), simulated cues (e.g., timing and duration), sites (e.g., quality), and how conspecific attraction was measured. We identified 31 experiments that simulated social cues and compared conspecific settlement between treatment and control sites. We then used phylogenetically controlled meta-regression to assess impacts of 19 moderators on settlement. Nearly all species included in these experiments were migratory passerines, and social cues generally had a strong, positive influence on their settlement decisions, as the odds of site occupancy were 3.12× (95% CI = 0.81, 11.69) greater in treatment sites relative to control sites. Within this group, conspecific attraction was evolutionarily conserved with ≥ 25.5% (CI = 5.1%, 65.4%) of the variance in treatment effects explained by phylogenetic relatedness. However, we found no evidence that any covariates influenced the response to social cues, and we posit this stems from limited research specifically designed to identify the mechanisms mediating conspecific attraction. We therefore developed a research agenda that provides a framework for testing mechanistic hypotheses regarding how cue characteristics, species traits, and spatial contexts may mediate attraction to conspecifics. Evaluating these hypotheses will greatly advance the field by helping managers understand when, where, and why simulating social cues can be used to enhance populations of species that are of conservation concern.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.