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216 results for “STAKEHOLDERS”
Gaming Horizons Stakeholder Interviews - anonymised
<p>Anonymised transcripts of interviews carried out between March and June 2017. The interviews involved representatives from five stakeholder groups: game developers, researchers, educators, young players, and policy makers. The interviews explored the cultural, educational and ethical implications associated with the design and the usage of video games in European society. A report based on the findings can be downloaded from https://www.gaminghorizons.eu/deliverables/ </p> <p>A CSV file called Interviews metadata reports basic information for each interviewee: stakeholder type, gender and provenance. </p>
GRRIP WP5 - Stakeholder Survey
<p>This dataset includes the full survey data of the GRRIP project's WP5 Stakeholder Survey, including documentation about using the dataset and the original survey design.</p> <p>Respondents of this survey are interested in a research organisation in the marine and maritime sector and stakeholder in the GRRIP (Grounding RRI Practices in research performing organisations) project. The survey was conducted as part of auditing the policies and practices of the five marine & maritime organisations involved in GRRIP and to gather respondents' perspectives on these policies and practices.</p> <p> </p> <p><strong>About GRRIP</strong><br> GRRIP is an EU-funded project (<a href="https://grrip.eu/">grrip.eu</a>) that aims to embed sustainable RRI (responsible re-search and innovation) practices in the marine & maritime sector through institutional and cultural change. GRRIP will embed sustainable RRI practices in these five marine & maritime organisa-tions: The Centre for Marine and Renewable Energy (MaREI), University College Cork, Ireland Plataforma Oceánica de Canarias (Plocan), Gran Canaria WavEC Offshore Renewables, Lisbon, Portugal Institut Universitaire Mer Littoral U.Nantes (IUML), France Swansea University, Wales.</p> <p> </p> <p>-----------<br> <em>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No.</em> <a href="https://cordis.europa.eu/project/id/820283"><em>820283</em></a><em>.</em></p>
Multi-stakeholder research data management training as a tool to improve the quality, integrity, reliability and reproducibility of research: Quantitative data of the post-course surveys
<p>Data contains doctoral students' and postdoc researchers' (n=168) self-ratings of their RDM competencies before and after the 3 ECTS credits "Basics of Research Data Management" (BRDM) trainings held 2019-2021 in the University of Turku and Åbo Akademi University, Finland. Moreover, data contains respondents' self-reported further learning needs.</p>
BRAVE stakeholder survey
<p>Data set from the BRAVE stakeholder survey. A codebook ist documenting and complementing the data set.</p> <p>The BRAVE stakeholder survey was conducted within the context of the multidisciplinary research project “BRidging gaps for the adoption of Automated VEhicles” (BRAVE) funded by the EU as part of the Horizon 2020 research program. The survey took place in the seven countries of the participating project partners, i.e. in the EU countries France, Germany, Slovenia, Spain, and Sweden, as well as in Australia and the USA and took place in February and March 2020. The survey was conducted via computer assisted web interviews (CAWI).</p> <p>The aim of the study was to explore stakeholders’ expectations, concerns and needs of a large-scale introduction of automated vehicles at SAE Level 3. Applying a mixed method approach, expert interviews were conducted to design the questionnaire of the online stakeholder survey.</p> <p>The codebook of the BRAVE stakeholder survey documents the applied questionnaire and codes given in data preparation. The documentation accompanies the data set of the BRAVE stakeholder survey stored in the repository zenodo.org available under doi: 10.5281/zenodo.5495219.</p> <p>Further details on the survey and results are reported in the BRAVE Deliverable D2.2 “Report on the findings of the expert online survey”, available at https://www.brave-project.eu/wp-content/uploads/2021/03/20210225-Deliverable-D2.2-Stakeholder-survey-Final.pdf.</p>
Stakeholders in Croatian Agriculture Open Data Ecosystem
<p>The dataset shows the identified stakeholders in the Croatian agriculture open data ecosystem in the researched literature available on national portals Hrčak (the Portal of Croatian scientific and professional journals) and Dabar (Digital Academic Archives and Repositories). The complex query: "stakeholder" OR "persons" OR "actors" OR "agriculture" OR "agriculture business" OR "farms" OR "agriculture sector" OR "agriculture area" OR "agriculture field" AND "open data" was used for search of the national databases Hrčak and Dabar. The stakeholders identified in the query were classified and grouped into five key stakeholder groups: Agriculture producers/Farmers, Suppliers, Management and Support Organizations, Consumer Organizations/Consumers, Researches and Scientists, and Others.</p>
PROSEU Collective Renewable Energy Prosumers Stakeholders Database (Template)
<p>As part of work package nº2 of the H2020 PROSEU project, which aimed to establish a baseline review and characterisation of renewable energy sources (RES) prosumer (self-consumption) initiatives across Europe, databases identifying the diversity of collective forms of RES prosumers and related stakeholders were built by the project partners using the templates and respective variables presented here (English language). The databases served to create a stratified sample of RES prosumer initiatives for purposes of a survey, as well as distinguish them from other stakeholders in the field.</p>
2020 Stakeholder Survey of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) - Quantitative Dataset
<p>This dataset is the outcome of a survey of IPBES stakeholders that was conducted in May-June 2020. The aim of this survey is to better understand stakeholder engagement with IPBES, to improve implementation of the IPBES stakeholder engagement strategy (decision IPBES-3/4 presented in document IPBES/3/18), and to further increase the inclusivity and effectiveness of the IPBES work programme. Results will help, among others, to better align communication and outreach, and to strengthen collaborative processes within the IPBES work programme.</p> <p><br> This dataset presents only the quantitative data of the complete dataset of responses. It has been anonymised and all personal comments in response to open questions have been removed. For information, the full anonymised dataset has been published on Zenodo, with restricted access (see DOI: <a href="http://doi.org/10.5281/zenodo.4121916">10.5281/zenodo.4121916</a>).</p> <p>This dataset is under restricted access and embargoed until after the eighth session of IPBES Plenary. For any inquiry, please contact IPBES Head of Communications (stakeholders@ipbes.net). </p>
How can higher education stakeholders support Edtech?
<p>This video outlines policy recommendations for cross-sector digital transformation in higher education. It highlights the importance of collaboration between policy-makers, stakeholders, EdTech companies, and universities to advance digital technologies in higher education. The findings derive from the ESRC-funded project 'Universities and Unicorns: building digital assets in the higher education industry'.</p>
National Open Access Monitor, Draft Report: Stakeholder Feedback: Response Dataset
<p>This dataset contains the response data from the 'National Open Access Monitor, Draft Report: Stakeholder Feedback' Form which was open from 16th to 30th November 2023 under the National Open Access Monitor Project. A PDF reference copy of the Feedback Form is available here: <a href="https://zenodo.org/doi/10.5281/zenodo.10141988">https://zenodo.org/doi/10.5281/zenodo.10141988</a></p><p>The purpose of the form was to capture stakeholder feedback on the National Open Access Monitor, Ireland Draft Report, for actioning by OpenAIRE in the final National Open Access Monitor Report to be delivered in January 2024. The draft is an interim report, and includes reference to the initial feedback from IReL and the National Open Access Monitor Project Advisory Group.</p><p><strong>To note: </strong></p><ul><li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor I, Research Performing Organisation I, where requested by the participant in the participant consent form: <a href="https://doi.org/10.5281/zenodo.7589770">https://doi.org/10.5281/zenodo.7589770</a></li><li>This is the original raw data file, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised.</li></ul><p>-----------------------</p><p>The context for the feedback form is detailed in the National Open Access Monitor Project Plan: <a href="https://doi.org/10.5281/zenodo.7331431">https://doi.org/10.5281/zenodo.7331431</a>, the National Open Access Monitor Advisory Group Meeting Minutes, 27th October 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.10105023 ">https://zenodo.org/doi/10.5281/zenodo.10105023 </a>and the OpenAIRE National Open Access Monitor Ireland, Draft Report: <a href="https://zenodo.org/doi/10.5281/zenodo.10136295">https://zenodo.org/doi/10.5281/zenodo.10136295</a></p><p>This project is managed by <a href="http://www.irel.ie/">IReL </a>and has received funding from Ireland's National Open Research Forum under the NORF Open Research Fund. <a href="https://norf.ie/funding/">https://norf.ie/funding/ </a><a href="https://norf.ie/orf-projects-announcement/">https://norf.ie/orf-projects-announcement/</a></p>
A stakeholder-centered determination of High-Value Data sets: the use-case of Latvia
<p>The data in this dataset were collected in the result of the survey of Latvian society (2021) aimed at identifying high-value data set for Latvia, i.e. data sets that, in the view of Latvian society, could create the value for the Latvian economy and society.<br> The survey is created for both individuals and businesses.<br> It being made public both to act as supplementary data for "Towards enrichment of the open government data: a stakeholder-centered determination of High-Value Data sets for Latvia" paper (author: Anastasija Nikiforova, University of Latvia) and in order for other researchers to use these data in their own work.</p> <p>The survey was distributed among Latvian citizens and organisations. The structure of the survey is available in the supplementary file available (see Survey_HighValueDataSets.odt)</p> <p>***Description of the data in this data set: structure of the survey and pre-defined answers (if any)***<br> 1. Have you ever used open (government) data? - {(1) yes, once; (2) yes, there has been a little experience; (3) yes, continuously, (4) no, it wasn’t needed for me; (5) no, have tried but has failed}<br> 2. How would you assess the value of open govenment data that are currently available for your personal use or your business? - 5-point Likert scale, where 1 – any to 5 – very high<br> 3. If you ever used the open (government) data, what was the purpose of using them? - {(1) Have not had to use; (2) to identify the situation for an object or ab event (e.g. Covid-19 current state); (3) data-driven decision-making; (4) for the enrichment of my data, i.e. by supplementing them; (5) for better understanding of decisions of the government; (6) awareness of governments’ actions (increasing transparency); (7) forecasting (e.g. trendings etc.); (8) for developing data-driven solutions that use only the open data; (9) for developing data-driven solutions, using open data as a supplement to existing data; (10) for training and education purposes; (11) for entertainment; (12) other (open-ended question)<br> 4. What category(ies) of “high value datasets” is, in you opinion, able to create added value for society or the economy? {(1)Geospatial data; (2) Earth observation and environment; (3) Meteorological; (4) Statistics; (5) Companies and company ownership; (6) Mobility}<br> 5. To what extent do you think the current data catalogue of Latvia’s Open data portal corresponds to the needs of data users/ consumers? - 10-point Likert scale, where 1 – no data are useful, but 10 – fully correspond, i.e. all potentially valuable datasets are available<br> 6. Which of the current data categories in Latvia’s open data portals, in you opinion, most corresponds to the “high value dataset”? - {(1)Foreign affairs; (2) business econonmy; (3) energy; (4) citizens and society; (5) education and sport; (6) culture; (7) regions and municipalities; (8) justice, internal affairs and security; (9) transports; (10) public administration; (11) health; (12) environment; (13) agriculture, food and forestry; (14) science and technologies}<br> 7. Which of them form your TOP-3? - {(1)Foreign affairs; (2) business econonmy; (3) energy; (4) citizens and society; (5) education and sport; (6) culture; (7) regions and municipalities; (8) justice, internal affairs and security; (9) transports; (10) public administration; (11) health; (12) environment; (13) agriculture, food and forestry; (14) science and technologies}<br> 8. How would you assess the value of the following data categories?<br> 8.1. sensor data - 5-point Likert scale, where 1 – not needed to 5 – highly valuable<br> 8.2. real-time data - 5-point Likert scale, where 1 – not needed to 5 – highly valuable<br> 8.3. geospatial data - 5-point Likert scale, where 1 – not needed to 5 – highly valuable<br> 9. What would be these datasets? I.e. what (sub)topic could these data be associated with? - open-ended question<br> 10. Which of the data sets currently available could be valauble and useful for society and businesses? - open-ended question<br> 11. Which of the data sets currently NOT available in Latvia’s open data portal could, in your opinion, be valauble and useful for society and businesses? - open-ended question<br> 12. How did you define them? - {(1)Subjective opinion; (2) experience with data; (3) filtering out the most popular datasets, i.e. basing the on public opinion; (4) other (open-ended question)}<br> 13. How high could be the value of these data sets value for you or your business? - 5-point Likert scale, where 1 – not valuable, 5 – highly valuable<br> 14. Do you represent any company/ organization (are you working anywhere)? (if “yes”, please, fill out the survey twice, i.e. as an individual user AND a company representative) - {yes; no; I am an individual data user; other (open-ended)}<br> 15. What industry/ sector does your company/ organization belong to? (if you do not work at the moment, please, choose the last option) - {Information and communication services; Financial and ansurance activities; Accommodation and catering services; Education; Real estate operations; Wholesale and retail trade; repair of motor vehicles and motorcycles; transport and storage; construction; water supply; waste water; waste management and recovery; electricity, gas supple, heating and air conditioning; manufacturing industry; mining and quarrying; agriculture, forestry and fisheries professional, scientific and technical services; operation of administrative and service services; public administration and defence; compulsory social insurance; health and social care; art, entertainment and recreation; activities of households as employers;; CSO/NGO; Iam not a representative of any company<br> 16. To which category does your company/ organization belong to in terms of its size? - {small; medium; large; self-employeed; I am not a representative of any company}<br> 17. What is the age group that you belong to? (if you are an individual user, not a company representative) - {11..15, 16..20, 21..25, 26..30, 31..35, 36..40, 41..45, 46+, “do not want to reveal”}<br> 18. Please, indicate your education or a scientific degree that corresponds most to you? (if you are an individual user, not a company representative) - {master degree; bachelor’s degree; Dr. and/ or PhD; student (bachelor level); student (master level); doctoral candidate; pupil; do not want to reveal these data}</p> <p>***Format of the file***<br> .xls, .csv (for the first spreadsheet only), .odt</p> <p>***Licenses or restrictions***<br> CC-BY</p> <p> </p> <p> </p>
ACTIVAGE Cocreation Stakeholders sociodemograhic data
<pre>It contains the sociodemographic data of the participants in the different co-creation workshops carried out during the project duration. These data have the same fields as the sociodemographic baseline of the evaluation of pilot sites. It also includes the taxonomy of stakeholders that were defined in ACTIVAGE and details of the stakeholders involved in each DS</pre>
Data for 'Stakeholder Perspectives on Nature, People, and Sustainability at Mount Kilimanjaro'
<p>Title: Data for ‘Stakeholder Perspectives on Nature, People, and Sustainability at Mount Kilimanjaro’</p> <p>Recommended Citation: Masao CA, Prescott GW, Snethlage MA, Urbach D, Torre-Marin Rando A, Molina-Venegas R, Mollel NP, Hemp C, Hemp A, Fischer M (2022). People and Nature.</p> <p>Principal Investigator:<br> - Markus Fischer (markus.fischer@ips.unibe.ch)</p> <p>Authors:<br> * joint first-author<br> - Catherine A. Masao (ndeutz@yahoo.com, ORCID: 0000-0002-1242-9117) *<br> - Graham W. Prescott (graham.prescott.research@gmail.com, ORCID: 0000-0001-5123-514X) *<br> - Mark A. Snethlage (mark.snethlage@ips.unibe.ch, ORCID: 0000-0002-1398-8869) *<br> - Davnah Urbach (davnah.payne@ips.unibe.ch, ORCID: 0000-0001-9170-7834) *<br> - Amor Torre-Marin Rando (amor.torre@ips.unibe.ch)<br> - Rafael Molina Venegas (rafmolven@gmail.com, ORCID 0000-0001-5801-0736)<br> - Neduvoto P. Mollel (neduvotomollel@yahoo.com, ORCID: 0000-0002-4402-4667)<br> - Claudia Hemp (claudiahemp@yahoo.com, ORCID: 0000-0002-5369-2122)<br> - Andreas Hemp (andreas.hemp@uni-bayreuth.de, ORCID: 0000-0001-9170-7113)<br> - Markus Fischer (markus.fischer@ips.unibe.ch, ORCID: 0000-0002-5589-5900)</p> <p>Date of data collection: 2018-09<br> Location of data collection: Moshi, Kilimanjaro Region, Tanzania<br> Date of final file release: 2022-01-13</p> <p>Data Overview:</p> <p>We conducted a three-day stakeholder workshop in Moshi, Tanzania, in September 2018. The workshop was attended by 73 participants (16 women and 57 men), whom we invited to represent various sectors and local communities. We established the list of invitees through an extensive online search validated and complemented by key local informants. We divided registered participants into five groups based on their sectoral affiliation: 16 residents of local communities, including farmers (herein ‘Community’), 14 researchers and scientists (‘Research’), 16 professionals in conservation and management (‘Conservation’), 17 professionals in forestry, agriculture, and water management and governance (‘Resources’), and 10 other professionals mainly drawn from the tourism sector (‘Other’).</p> <p>We used two questionnaires—herein ‘habitat’ and ‘ecosystem services’— with open and closed questions. Closed questions were scored using a Likert-type scale.</p> <p>File overview:</p> <p>1. kilimanjaro_ipbes_workshop_habitat_questionnaire.csv</p> <p>Data from the ‘habitat’ questionnaire, entered by Catherine A. Masao and Mark A. Snethlage (finalised 2020-09-22). Individual perceptions about the state of and trends in habitats and species diversity and about the direct and indirect factors driving these trends. We invited participants to fill out separate questionnaires for each habitat of importance to their sector or for which they had knowledge, starting with the most important one.</p> <p>2. kilimanjaro_ipbes_workshop_ecosystem_services_questionnaire.csv</p> <p>Data from the ‘ecosystem services’ questionnaire, entered by Catherine A. Masao and Mark A. Snethlage (finalised 2020-01-09). The ‘ecosystem services’ questionnaire collected individual perceptions about the state of, trends in, and importance of NCP (Nature's Contributions to People), as well as about the factors driving observed changes in access and provision. With reference to the preliminary group discussion on NCP, we invited participants to fill out separate forms for each NCP they deemed important to their sector or had knowledge about and to indicate which habitat(s) provide(s) each of them.</p> <p>3. kilimanjaro_ipbes_workshop_ecosystem_services_access_change_codes.csv</p> <p>Adapted from the ecosytem services questionnaire data (kilimanjaro_ipbes_workshop_ecosystem_services_questionnaire.csv), coding the reasons for change in access to NCP.</p> <p>4. kilimanjaro_ipbes_workshop_spatial_scales_recommended_measures.csv</p> <p>Tally of recommended measures towards recorded from the carousel session, grouped by spatial scale and Conservation Measures Partnership (CMP) categories. See Table S7 for details.</p> <p><br> Code used for analysis:<br> R code used for the statistical analysis and to create the figures available from: https://github.com/grahamprescott/kilimanjaro.ipbes.workshop.paper</p> <p>File details:</p> <p>1. kilimanjaro_ipbes_workshop_habitat_questionnaire.csv</p> <p>143 observations of 73 variables</p> <p>Key Variables:<br> - Group<br> (categorical - stakeholder group to which participants were assigned. Blue = Community, Green = Research, Orange = Conservation, Red = Other, Yellow = Resources)<br> - Biome2<br> (categorical - standardised habitat categories used in the analysis, coded by Mark A. Snethlage)<br> - Habitat.area<br> (categorical - trends in habitat area over past 10 years (2008-2018); Decreased, Not Changed, Increased, No Answer)<br> - Habitat.condition<br> (categorical - trends in habitat condition over past 10 years (2008-2018); Deteriorated, Not Changed, Improved, No Answer)<br> - Habitat.area.will<br> (categorical - prediction for trend in habitat condition over next 10 years (2018-2028); Decrease Not Change, Increase, No Answer)<br> - Habitat.condition.will<br> (categorical - trends in habitat condition over past 10 years (2018-2028); Decrease, Not Change, Increase, No Answer)<br> Variables beginning with ES., DIR., IND., ACT. refer to ecosystem services (i.e. NCP), direct drivers, indirect drivers, and recommended actions associated with each habitat form. They are numerical and scored as 1 if that variable is mentioned (present) or 0 if not mentioned (absent). In a few cases where different ecosystem services listed by the participant are coded to the same variable the number is the number of times that ecosystem service is mentioned.</p> <p>Codes for ecosystem services (ES.): HAB (Habitat Creation and Maintenance), POL (Pollination and dispersal of seeds and other propagules), AIR (Regulation of Air Quality), CLI (Regulation of Climate), OCE (Regulation of Ocean Acidification), WQN (Regulation of Freshwater Quantity, Location, and Timing), WQL (Regulation of Freshwater and Coastal Water Quality), SOL (Formation, Protection, and Decontamination of Soils and Sediments), HAZ (Regulation of Hazards and Extreme Events), PST (Regulation of Organisms Detrimental to Humans), NRG (Energy), FOD (Food and Feed), MAT (Materials and Assistance), MED (Medicinal, Biochemical, and Genetic Resources), LRN (Learning and Inspiration), EXP (Physical and Psychological Experiences), IDE (Supporting Identities), OPT (Maintenance of Options), WEB (Human Wellbeing), LIV (Livelihoods). Note: WEB and LIV are not traditionally included in NCP categories, but we created them as additional categories to capture responses that could not strictly be placed into the traditional 18 categories. </p> <p>Codes for direct drivers (DIR.): ACT = ‘Human Activities’, CC = Climate Change, IAS = Invasive Alien Species, LUC = Land-Use Change, OVR = Overexploitation, POL = Pollution.</p> <p>Codes for indirect drivers (IND.): CLT = Cultural, DEM = Demographic, ECO = Economic, GOV = Governance, S.T = Science and Technology.</p> <p>Codes for recommended actions (ACT.): AWR = Awareness Raising, ECO = Livelihood, Economic & Moral Incentives, EDU = Education & Training, ENF = Law Enforcement & Prosecution, INS = Institutional Development, LAN = Land / Water Management, LAW = Legal & Policy Frameworks, PRT = Conservation Designation & Planning, RSR = Research & Monitoring, SPC = Species Management.</p> <p>2. kilimanjaro_ipbes_workshop_ecosystem_services_questionnaire.csv</p> <p>144 observations of 38 variables</p> <p>Key variables:</p> <p>- Group<br> (categorical - stakeholder group to which participants were assigned. Blue = Community, Green = Research, Orange = Conservation, Red = Other, Yellow = Resources)<br> - Service.original (free text response to which ecosystem service the participant was filling out the form)<br> - ESCODE<br> (categorical - NCP category to which we assigned the free text response. Abbreviations: HAB (Habitat Creation and Maintenance), POL (Pollination and dispersal of seeds and other propagules), AIR (Regulation of Air Quality), CLI (Regulation of Climate), OCE (Regulation of Ocean Acidification), WQN (Regulation of Freshwater Quantity, Location, and Timing), WQL (Regulation of Freshwater and Coastal Water Quality), SOL (Formation, Protection, and Decontamination of Soils and Sediments), HAZ (Regulation of Hazards and Extreme Events), PST (Regulation of Organisms Detrimental to Humans), NRG (Energy), FOD (Food and Feed), MAT (Materials and Assistance), MED (Medicinal, Biochemical, and Genetic Resources), LRN (Learning and Inspiration), EXP (Physical and Psychological Experiences), IDE (Supporting Identities), OPT (Maintenance of Options), WEB (Human Wellbeing), LIV (Livelihoods). Note: WEB and LIV are not traditionally included in NCP categories, but we created them as additional categories to capture responses that could not strictly be placed into the traditional 18 categories.)<br> - Biome<br> (categorical - which habitat provided the ecosystem service)<br> - Why.changed.provision<br> (free text response for why Provision changed)<br> - Why.changed.access<br> (free text response for why Access changed) [Note: although we theoretically expected a distinction between provision and access of each ecosystem service, we observed that this distinction was not strictly followed in practice and deemed the responses about access to be most accurate]<br> - Access<br> (categorical - changes in access to the ecosystem service over the last 10 years (2008-2018); Decreased, No Change, Increased, No Answer)<br> - Access.will<br> (categorical - predicted changes in access to the ecosystem service over the next 10 years (2018-2028); Deteriorate, Not Change, No Answer, Improve (note: no one responded ‘Improve’)) </p> <p><br> 3. kilimanjaro_ipbes_workshop_ecosystem_services_access_change_codes.csv</p> <p>144 observations of 7 variables</p> <p>We took the following variables from the ecosystem services questionnaire:<br> - ESCODE<br> (categorical - NCP category to which we assigned the free text response)<br> - Access<br> (whether access to this NCP increased or decreased between 2008-2018)<br> - Why.changed.access<br> (free text response for why Access changed)<br> And created a new variable to synthesise the drivers of change in NCP access:<br> - Why.changed.access.code</p> <p>Note: a challenge with the ‘Why.changed.access’ variable is that many drivers are listed in the same response. To process this, we duplicated the rows with multiple drivers so that there would be one row per driver. We did this using Microsoft Excel for Mac. We did this so that each link from a driver to an increase or decrease in a given NCP could be visualised. The individual links are not standardised by individual respondent or response. They represent every instance of a reported link between a driver of change and a change in access to a given NCP. Responses or respondents who listed multiple instances of NCP access change and/or multiple drivers have therefore contributed more to the Sankey figure (Figure 4). We chose this approach because the aim in this case was to document the complex web of drivers leading to changes in NCP access, drawing upon the collective expertise of the respondents, not to test for individual differences between groups or respondents. Graham W. Prescott and Mark A. Snethlage independently coded each of the drivers and reached a consensus on any disagreements. Graham W. Prescott edited the final file.</p> <p>4. kilimanjaro_ipbes_workshop_spatial_scales_recommended_measures.csv</p> <p>11 observations of 6 variables<br> <br> We also conducted a carousel session in which participants could suggest actions and actors that could contribute towards achieving a sustainable future for people and nature at Mt. Kilimanjaro. This file contains the tally of recommended measures arising from this carousel session, grouped by spatial scale and Conservation Measures Partnership (CMP) categories. For full list of measures, see Table S7.</p> <p> </p> <p> </p>
Database for Perceived Inclusivity and Trust in Protected Area Management Decisions among Stakeholders in Alaska
<p>This database is part of a state-wide survey in Alaska, USA. An online Qualtrics interface was used to administer the survey to a panel of Alaskan residents from June to August 2020.</p>
ESCALATOR - Stakeholder map data workflow
<p>The stakeholder map project aims to collect and share data on Digital Humanities (DH), Computational Social Sciences (CSS) and related activities and initiatives in South Africa. This data includes information about South African researchers, projects, publications, tools, datasets, academic programmes, training events, learning materials, and more. The aim is to provide deeper insight into the breadth of activities in this area, facilitate enhanced networking and collaboration, and support the optimal use of resources. The stakeholder map will, for example, support researchers looking for collaborators, help potential students to identify undergraduate and postgraduate training programmes, and highlight gaps and opportunities to funders and institutions.</p> <p>The initial design of the data pipeline and workflow for data visualisation has been completed. The pipeline is primarily based on open-source software and platforms often used in the open science community. Development is currently under way. Data will be captured via Google Forms and manipulated using R scripts, available on GitHub and archived in Zenodo. Interactive visualisations will be published on the ESCALATOR website. These visualisations include a [Shiny app](https://shiny.rstudio.com/) that will allow the community to explore data through a web interface and a [Kumu network visualisation](https://kumu.io/). Research articles can be added to an [open collection in Zotero](https://www.zotero.org/groups/3866799/dhcssza) to facilitate easy access to publications from the South African community.</p> <p><br> This diagramme shows the high-level workflow. We anticipate the diagramme will be updated as design and development progresses to incorporate lessons learned and feedback from the community.</p>
Inventory of tools and resources for crop diversification available for stakeholders
<p>The aim of the database is to give an overview of existing resources, tools and methods to promote crop diversification strategies (rotation, multiple cropping, intercropping) at different levels (including the value chain and territory levels). This version contains 143 resources.</p> <p>Each resource is described with a set of criteria: strategies used / described in the resource, purpose of the resource (what is an end-user doing with the resource), expected performances, area of validity, context of use, but also characteristics for use (cost, training, required time to collect data…).</p> <p>A toolbox was also designed to support end-users to navigate among this database and aims to help different type of end-users to identify interesting and adapted resources to foster crop diversification.</p> <p></p>
Supplementary material 2 from: Bayliss H, Stewart G, Wilcox A, Randall N (2013) A perceived gap between invasive species research and stakeholder priorities. NeoBiota 19: 67-82. https://doi.org/10.3897/neobiota.19.4897
Journal article classifications (doi: 10.3897/neobiota.19.4897.app2) File format: Comma Separated Value File (csv).:
Supplementary material 1 from: Bayliss H, Stewart G, Wilcox A, Randall N (2013) A perceived gap between invasive species research and stakeholder priorities. NeoBiota 19: 67-82. https://doi.org/10.3897/neobiota.19.4897
Stakeholder priorities. (doi: 10.3897/neobiota.19.4897.app1) File format: Micrisoft Comma Separated Value File (csv).:
Improving access to and reuse of research results, publications and data for scientific purposes - Stakeholders' consultations results
<p>The data sets were created via data collection effort for the Horizon Europe-funded "study to evaluate the effects of the EU copyright framework on research and the effects of potential interventions and to identify and present relevant provisions for research in EU data and digital legislation, with a focus on rights and obligations". The study was contacted by DG RTD. </p> <p>This research project supports Action 2 objectives of the European Research Area (ERA) Policy Agenda 2022-2024, which aims to propose an EU legislative and regulatory framework for copyright and data that is fit for research. The report provides a comprehensive analysis of barriers to the access and reuse of publicly funded research, including scientific publications and data. It assesses existing EU copyright legislation and EU data and digital legislation. It also assesses regulatory frameworks and national initiatives and identifies potential areas for improvement.</p> <p>Using a methodological, evidence-based approach (including the survey results posted in this repository), the study presents possible legislative and non-legislative measures to improve the current EU copyright and data framework and align it with the needs of scientific research and open research data principles. </p> <p>The data sets include the raw data of the three surveys (survey 1 targeted at researchers, survey 2 targeted at research-performing organisations, and survey 3 targeted at publishers). All surveys have two major parts: one concerning copyright legislation and another concerning data and digital legislation. In addition, we provide interview notes, they are also organised into two parts: one concerning copyright legislation and another concerning data and digital legislation. </p> <p>The data collection effort was partially supported by our colleagues from the Institute for Information Law (IVIR) and KU Leuven CiTIP. </p>
Results of the Web-Delphi process to INAMI stakeholders (three rounds)
<p>IMPACT HTA, WP7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 3 (Testing the framework with empirical applications), Results of the Web-Delphi process to INAMI stakeholders (three rounds), about the views of stakeholders regarding “The relevance of the following value aspects for the evaluation of new medicines in this disease context is” (2020)</p> <p>For details on the Web-Delphi process, see: IMPACT HTA, Work Package 7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 3, Deliverable 7.3 (Testing the framework with empirical applications), Testing the IMPACT-HTA Value Framework in collaboration with HTA agencies: Case studies on Non-Small Cell Lung Cancer and Spinal Muscular Atrophy (2021), Aris Angelis (LSHTM, LSE), Mónica Oliveira (IST), Teresa Rodrigues (IST), Liliana Freitas (IST), Carlos Bana e Costa (IST), Panos Kanavos (LSE)</p>
IMPACT HTA, WP7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2 (Multi-criteria evaluation framework), Results of the 2nd Web-Delphi process to HTA stakeholders, organized in a single panel
<p>IMPACT HTA, WP7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2 (Multi-criteria evaluation framework), Results of the 2<sup>nd</sup> Web-Delphi process to HTA stakeholders, organized in a single panel (all stakeholder groups in a single panel, 2 rounds), about the views of stakeholders regarding “This aspect should be considered in the evaluation of new medicines on a common basis” (2019)</p> <p>For details on the Web-Delphi process, see: IMPACT HTA, Work Package 7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2, Deliverable 7.2 (Multi-criteria evaluation framework), Advancing knowledge and MCDA tools to assist HTA agencies in evaluating medicines on a common basis (2021) Oliveira, M.D. (IST), Panos Kanavos (LSE), Bana e Costa, C. (IST)</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
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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.