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Quantitative and qualitative aspects of dissolved organic carbon leached from plant biomass in Taylor Slough, Shark River and Florida Bay (FCE) for samples collected in July 2004
Plant biomass was collected from Taylor Slough, Shark River and Florida Bay in Everglades National Park. Samples were taken to the lab and incubated with Milli-Q water in the dark for a period of 36 days. NaN3 was added to half the bottles to test the role of microbial activity on the leaching rates and composition of leachate. Every three days the water was decanted and replaced with fresh Milli-Q water. The decanted samples were filtered and analyzed for DOC concentration, sugar content, and total phenol content.
Qualitative Data on 60 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain)
<h2><span lang="EN-US">Dataset name</span></h2> <p><span lang="EN-US">Small_Scale_Fishery_Data_2023_v2 </span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Title</span></h2> <p><span lang="EN-US">Qualitative Data on 60 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain). </span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Description </span></h2> <p><span lang="EN-US"> This dataset was created for the Fish2Sustainability research project, which aims to evaluate how small-scale fisheries (SSF) contribute to Sustainable Development Goals (SDGs). The dataset includes 60 case studies across eight countries and was developed using a rapid appraisal framework. The framework includes a four-step process: </span></p> <p><span lang="EN-US"> 1. Identifying specific SDG targets influenced by SSF;</span></p> <p><span lang="EN-US"> 2. Extracting relevant variables from UN indicators;</span></p> <p><span lang="EN-US"> 3. Gathering expert input via a questionnaire to score these variables;</span></p> <p><span lang="EN-US"> 4. Creating composite indicators to measure SSF performance against SDGs.</span></p> <p><span lang="EN-US"> The dataset contains raw data from step 3, case study details, variable scores, and comments from data collectors (contributing authors). The dataset is valuable for researchers interested in small-scale fisheries and socio-ecological systems. By incorporating expert judgments from individuals with expertise in SSF, particularly in data-poor contexts, the dataset offers a wealth of knowledge for conducting comparative analyses across different contexts.</span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Authors </span></h2> <p><span lang="EN-US">Léopold, M.1, Bitoun, R.E.2, Beckensteiner, J.3, Chuenpagdee, R.4, Fondo, E.N.5, Akintola, S.L.6, Bach, P.7, Frangoudes, K.8, Gaibor, N.9, Gutierrez-Cala, L.10, Massey, Y.7, Randrianandrasana, R.11, Razanakoto, T.11, Saavedra-Díaz, L.M.10, Schreiber Arias, M.12,13, Salas, S.14, Devillers, R.2,4 </span></p> <h3><span lang="EN-US">Affiliations </span></h3> <p><span lang="EN-US">1 ENTROPIE (IRD, University of La Reunion, CNRS, University of New Caledonia, Ifremer), c/o IUEM, Plouzané, France </span></p> <p><span lang="EN-US">2 Espace-Dev (IRD, Univ. </span>Montpellier, Univ. Guyane, Univ. La Réunion, Univ. Antilles, Univ. Nouvelle Calédonie), Montpellier, France</p> <p>3 AMURE (Ifremer, UBO, CNRS), Plouzané, France</p> <p><span lang="EN-US">4 Department of Geography, Memorial University of Newfoundland, St. John’s, NL, Canada</span></p> <p><span lang="EN-US">5 Kenya Marine and Fisheries Research Institute, Mombasa, Kenya</span></p> <p><span lang="EN-US">6 Department of Fisheries, Faculty of Science, Lagos State University, Nigeria</span></p> <p><span lang="EN-US">7 MARBEC, University of Montpellier, CNRS, Ifremer, IRD, Sète, France</span></p> <p>8 Université de Bretagne Occidentale: Brest, France</p> <p>9 Instituto Público de Investigación de Acuicultura y Pesca (IPIAP), Universidad del Pacifico (UPAC), Guayaquil, Ecuador</p> <p>10 Grupo de Investigación en Sistemas Socioecológicos para el Bienestar Humano (GISSBH), Programa de Biología, Universidad del Magdalena, Colombia</p> <p>11 Centre d’Etudes et de Recherches Economiques pour le Développement (CERED), Université d’Antananarivo, Madagascar</p> <p><span lang="EN-US">12 EqualSea Lab, Universidad Santiago de Compostela, A Coruña, Spain</span></p> <p><span lang="EN-US">13 School of Global Studies, University of Gothenburg, Gothenburg, Sweden</span></p> <p>14 Centro de Investigación y de Estudios Avanzados (CINVESTAV), IPN, Unidad Mérida, Mexico </p> <h2><span lang="EN-US">Method </span></h2> <p><span lang="EN-US">Case studies were selected in eight countries by national SSF experts, based on specific criteria and research priorities. Case studies were not selected to represent the full diversity of SSF globally or even nationally. Instead, they were chosen to capture a range of fisheries that could showcase different contributions to SDGs. SSF were defined based on various characteristics, such as resources harvested, gear used, and location of the fishery. </span><span lang="EN-US"> </span></p> <h3><span lang="EN-US">Geographical Coverage </span></h3> <p><span lang="EN-US">60 small-scale fisheries located in seven countries are documented in the data:</span></p> <ul> <li><span lang="EN-US">Colombia (4 case studies) – Pacifico: La Guajira, San Andrés y Providencia; Caribe: Chocó, Cauca, Valle del Cauca, Nariño.</span></li> <li><span lang="EN-US">Ecuador (3) – Region: Esmeraldas, Manabi, Guayas, El Oro.</span></li> <li><span lang="EN-US">France (2) – Region: Bretagne, Occitanie.</span></li> <li><span lang="EN-US">Kenya (22) – County: Kilifi, Kwale, Lamu, Mombasa, Tana River.</span></li> <li><span lang="EN-US">Madagascar (20) – Region: Analanjirofo, Anosy, Atsimo Andrefana, Boeny, Diana, Menabe, Vatovavy Fitovinany.</span></li> <li><span lang="EN-US">Mexico (2) – State: Baja California Sur, Campeche, Yucatan.</span></li> <li><span lang="EN-US">Nigeria (6) – State: Bayelsa, Cross River, Lagos, Ondo, Ogun. </span></li> <li><span lang="EN-US">Spain (1) – State: Galicia.</span> </li> </ul> <h3><span lang="EN-US">Data Collection </span></h3> <p><span lang="EN-US">Data collection took place from November 30, 2022, to July 3, 2023, spanning approximately seven months. The data presented serve as a snapshot of the conditions within a specific small-scale fishery during the assessment period. To consider the evolution of trends such as exports, economic growth, and income, we considered any relevant variables over the past decade. </span></p> <p><span lang="EN-US">Data collection approaches varied depending on the context, and data collectors received training to ensure survey consistency. We used primary data sources such as interviews, observations, and measurements whenever possible. In cases where resources were limited, we preferred secondary sources such as existing datasets and literature. Our methods were standardized, but data collectors could adjust them based on their resources. We primarily used direct observation, focus groups, and interviews to collect data. Scoring in interviews and focus groups was done directly or through group analysis by interviewers. Disagreements were resolved through additional interviews or group discussions, with secondary data used if needed. Please refer to the methods in : </span></p> <p><strong><span lang="EN-US">Bitoun et al., (2024). A methodological framework for capturing marine small-scale fisheries’ contributions to the sustainable development goals. Sustainability Science, 19(4), 1119–1137. https://doi.org/10.1007/s11625-024-01470-0. </span></strong><span lang="EN-US"><strong> </strong> </span></p> <h3><span lang="EN-US">Ethics </span></h3> <p><span lang="EN-US">Participants had the option to join of their own accord, were fully briefed on the research goals, and were given the opportunity to review interview guidelines before proceeding. Depending on the circumstances, interviews could last 45 minutes to 4.5 hours. Participants were guaranteed confidentiality and anonymity in the handling and reporting of their data.</span><span lang="EN-US"> </span></p> <h3><span lang="EN-US">Suggested citation</span></h3> <p><span lang="EN-US">Léopold, M., Bitoun, R., & Devillers, R. (2023). Qualitative Data on 61 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain) (Version 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.16077739</span></p> <h2><span lang="EN-US">Data Files</span></h2> <p><span lang="EN-US">The dataset includes the following:</span></p> <ul> <li><span lang="EN-US">The raw dataset (.xls format).</span></li> <li><span lang="EN-US">A data dictionary describing and defining each dataset column (.xls format).</span></li> </ul>
Qualitative Larval Fish Sampling at the California Department of Water Resource’s State Water Project
The California Department of Water Resource’s State Water Project utilizes the John E. Skinner Delta Fish Protective Facility (Skinner Fish Facility) to salvage fishes that would otherwise become entrained during operations to divert water from the Sacramento-San Joaquin River Delta (Delta). Water is diverted from the Delta to meet California’s agricultural, municipal, industrial, and environmental needs. The Skinner Fish Facility, located in Contra Costa County and situated ahead of the Harvey O. Banks Pumping Plant, began salvaging fish in 1968 but historically, only recorded fork length measurements for fish greater than 20 millimeters. Beginning in 2009, the Skinner Fish Facility implemented qualitative larval sampling in response to the 2008 U.S. Fish and Wildlife Service Biological Opinion on the coordinated operations of the Central Valley Project (CVP) and State Water Project (SWP). This entailed collecting, retaining, and identifying larval fishes to better understand SWP impacts on Delta Smelt. Qualitative larval sampling took place annually from 2009 through 2025, during the Old and Middle River management period and based upon Delta Smelt spawning (typically mid-February to June). The California Department of Water Resources collected and processed samples from 2020 through 2025. Data from 2009 through 2019 were processed and retained by others and are not included in this dataset.
MiRoR5 - P2- Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
<p>Anonymised data of respondents to an open-ended online survey on their experience with collective intelligence</p>
Empirical data, qualitative codes, analysis: Schuur J.S. et al. Identifying levers of urban neighbourhood transformation. npj Urban Sustainability (2023)
<p>Please refer to the stand-alone "2023_SchuurJS_UrbanSustainabilityfinal.html" file where the analysis and results corresponding to the article titled: "Identifying levers of urban neighbourhood transformation using serious games" is presented. The underlying data sets and Rmarkdown script used for the analysis can be used to re-run the analysis. Ensure to read the "0_README.txt" file to build the appropriate folder structure to do so.</p>
Survey: Qualitative FGI research on the processing, sourcing, utilisation and management of wood biomass (NCN) DEC-2020/39/I/HS4/03533
<p>The dataset contains the proceedings of a qualitative FGI of representatives of wood biomass processing and harvesting companies. The research was conducted from 5 July 2022 to 7 July 2022 using only the FGI method. The survey was conducted in face-to-face meetings among respondents.<br>The study was funded by National Science Centre in Poland under agreement National Center of Science (NCN) through grant DEC-2020/39/I/HS4/03533</p>
Educational transformation and network learning dataset – qualitative data from an international collaborative EU-project
<p>We are releasing our dataset of workshop outcomes acquired from the annual consortium conferences organized by the international “NextFood” consortium. The purpose of this project is to develop new ways of educating the future sustainability leaders of the agrifood sector, making sure that the professionals (farmers, advisers, businesses, students) have the right set of skills and competences needed to tackle the sustainability challenges we face ahead. Data gathering started from May 2018 yielding considerable amount of data on achievements, challenges and action plans related to educational transformation. This dataset will be updated by the time of project finalization. This work was funded by the European Union, through the Horizon 2020 project “NextFood”, Grant agreement No. 771738.</p>
Qualitative coding of brief videos that teach about the h-index
<p><strong>Dataset of qualitative coding of 31 Youtube videos on the h-index. </strong>The study aimed to characterize educational videos about the h-index to understand available resources and provide recommendations for future educational initiatives.</p> <p><em>Data.csv</em>: contains the metadata and qualitative coding for 31 videos.</p> <p><em>ReadMe.csv</em>: contains the codebook including a description of variables.</p> <p><strong>Abstract. </strong>The authors analyzed videos on the h-index posted to YouTube. Videos were identified by searching YouTube and were screened by two authors. To code the videos the authors created a coding sheet, which assessed content and presentation style with a focus on the videos’ educational quality based on Cognitive Load Theory. Two authors coded each video independently with discrepancies resolved by group consensus. Thirty-one videos met inclusion criteria. Twenty-one videos (68%) were screencasts and seven used a “talking head” approach. Twenty-six videos defined the h-index (83%) and provided examples of how to calculate and find it. The importance of the h-index in high-stakes decisions was raised in 14 (45%) videos. Sixteen videos (52%) described caveats about using the h-index, with potential disadvantages to early researchers the most prevalent (n=7; 23%). All videos incorporated various educational approaches with potential impact on viewer cognitive load. Most videos (n=21; 68%) displayed amateurish production quality. The videos featured content with potential to enhance viewers’ metrics literacies such that many defined the h-index and described its calculation, providing viewers with skills to recognize and interpret the metric. However, less than half described the h-index as an author quality indicator, which has been contested, and caveats about h-index use were inconsistently presented, suggesting room for improvement. While most videos integrated practices to facilitate balancing viewers’ cognitive load, few (32%) were of professional production quality. Some videos missed opportunities to adopt particular practices that could benefit learning. </p>
Sharing research data and findings relevant to the novel coronavirus (COVID-19) outbreak - Thematic coding of qualitative research findings
<p>The spreadsheet in the present dataset (CSV format) includes the anonymised thematic coding that has been applied to our interview and literature review findings to inform the preparation of the report: From intent to impact: Investigating the effects of open sharing commitments.</p> <p>The thematic coding has been applied by using <a href="https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home">NVivo</a>, a professional qualitative analysis software, and then exported in spreadsheet form for public sharing.</p> <p>Find out more about this project in our dedicated <a href="https://zenodo.org/communities/data-sharing-in-public-health-emergencies">Zenodo project community</a>.</p>
Dataset: Multi-level network dataset of social-ecological interdependencies in ten Swiss wetlands based on qualitative interviews and quantitative surveys
<p>The dataset originated from quantitative online surveys and qualitative expert interviews with organizational actors relevant to the governance of ten Swiss wetlands from 2019 till 2021. Multi-level networks represent the wetlands governance for each of the ten cases. The collaboration networks of actors form the first level of the multi-level networks and are connected to multiple other network levels that account for the social and ecological systems those actors are active in. 521 actors relevant to the management of the ten wetlands are included in the collaboration networks; quantitative survey data exists for 71% of them. A unique feature of the collaboration networks is that it differentiates between positive and negative forms of collaboration specified based on actors' activity areas. Therefore, the data describes not only if actors collaborate but also how and where actors collaborate. Further additional two-mode networks (actor participation in forums and involvement in other regions outside the case area) are elicited in the survey and connected to the collaboration network. Finally, the dataset also contains data on ecological system interdependencies in the form of conceptual maps derived from 34 expert interviews (3-4 experts per case).</p>
Birdwatching, eBird and citizen science in India: qualitative interviews with participants, practitioners and ecologists
<h1>Abstract</h1> <p>This study consists of qualitative interviews about birdwatching, citizen science, and the use of the birdwatching data platform <em>eBird </em>in India. Interview partners are birdwatchers, citizen science practitioners, and ecologists who have used eBird data. Some of the main topics covered include: the nature of the birdwatching community and styles of birdwatching in India; the history of the adoption of eBird in India; the value of birdwatching and citizen science; challenges involved in conducting or participating in citizen science; opportunities and limitations of using data from eBird and citizen science; processes of data collection and quality control in eBird; and ecological research, conservation priorities, and environmental activism in India. This study is part of the project A Philosophy of Open Science for Diverse Research Environments (PHIL_OS).</p> <h1>Methods</h1> <p>The data in this study was collected using semi-structured qualitative interviews.</p> <p>Interview partners were recruited by snowball sampling through their engagement with eBird India and related organisations. There were 17 interview partners, interviewed either once or several times. 19 interviews were conducted in total.</p> <p>Interview guides/questionnaires were designed for each interviewee depending on their status as birdwatchers, citizen science coordinators, and eBird data users.</p> <p>Interviews were conducted between April 2022 and June 2023. The interviews took place online using Zoom videoconferencing software. Interviews lasted 35-70 minutes. When participants provided their written consent, interviews were audio-recorded and transcribed smart verbatim using otter.ai and manual proofreading. Sensitive information was removed before publishing transcripts.</p> <p>Transcripts were analysed using semi-grounded coding. Codes were organised into parent codes using an inductive approach based on emergent categories.</p> <h1>Description of the data and file structure</h1> <p>Documentation files include interview guides, the information sheet and consent form, ethics approval, and the data narrative. Documentation files are named according to the structure: authorname_filename_DOCUMENTATION.</p> <p>Data files consist of a summary of participants, 17 of the interview transcripts, and a code list. Interview transcript files are named according to the structure: authorname_interviewnumber_date.</p> <p>A full list of files is provided in the README file.</p> <h1>Notes</h1> <p>This study was conducted as part of the project A Philosophy of Open Science for Diverse Research Environments (PHIL_OS). More information can be found at <a href="https://opensciencestudies.eu/">https://opensciencestudies.eu</a></p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101001145).</p>
Dataset for: Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manusript:<br> Perrier L, Blondal E, MacDonald H. Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies. 2018; 40(3-4): 173-183. doi: 10.1016/j.lisr.2018.08.002</p> <p>Full-text available at: <a href="https://doi.org/10.1016/j.lisr.2018.08.002">https://doi.org/10.1016/j.lisr.2018.08.002</a> </p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset:</p> <ol> <li>Data Dictionary: RDMMetaEthnography_DataDictionary_v1.pdf</li> <li>Data Abstraction Sheet: RDMMetaEthnography_StudyCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_ParticipantCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_Outcomes.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_COREQ,csv</li> </ol> <p>Contact: Laure Perrier: <a href="https://orcid.org/0000-0001-9941-7129">orcid.org/0000-0001-9941-7129</a></p>
Qualitative Data on Effects of Early and Prolonged Parent-Child Separation: Understanding Mental Health of Separated-Reunited Chinese American Children
<div> <div> <div> <div>Early and prolonged parent-child separation due to parental migration or immigration may result in attachment disruption that can threaten the long-term mental health and functioning of affected children, and these risks can persist following reunification and through adulthood. Although sending infants back to the home country for rearing is often practiced among <em>Chinese</em> immigrants, especially low-income families, research has been sparse in understanding the long-term impact of early and prolonged parent-child separation and reunification on disparities in mental health and functioning among separated-reunited children and the mechanism through which such relationships may operate.</div> <div>Funded by National Institute on Minority Health and Health Disparities (NIMH), we collected semi-structured interview data from 24 parent-child dyads who have experienced separation. The data included interview scrpits with primary coding to understand the mental health impacts, risk/protective factors, and service needs among separated-reunited <em>Chinese</em> American children.</div> </div> </div> </div> <div> </div>
Qualitative dataset - Social justice-oriented narratives in European urban food strategies: Bringing forward redistribution, recognition and representation (Smaal et al., 2021)
<p>This qualitative dataset contains the English translations of the plain texts of the urban food strategy documents or webpages of 16 European medium-sized cities: Basel [CH]; Bristol [UK]; Bruges [BE]; Cordoba [ES]; Donostia - San Sebastián [ES]; Ede [NL]; Geneva [CH]; Ghent [BE]; Grenoble [FR]; Groningen [NL]; Montpellier [FR]; Nantes [FR]; Rennes [FR]; Tours [FR]; Uppsala [SE]; and Vitoria-Gasteiz [ES]. The search for and translation of the urban food strategy documents and webpages have been performed in early 2019. The files have been analysed in NVivo (qualitative data analysis software). The upload also includes figures and a table with the authors' assessments connected to the resources and services codes and radar diagram visualisations presented in the following paper: </p> <p>Smaal, S. A. L., Dessein, J., Wind, B. J., & Rogge, E. (2021). Social justice-oriented narratives in European urban food strategies: Bringing forward redistribution, recognition and representation. <em>Agriculture and Human Values</em>, 38(3), 709–727. <a href="http://doi.org/10.1007/s10460-020-10179-6">https://doi.org/10.1007/s10460-020-10179-6</a> </p> <p><strong>Abstract: </strong>More and more cities develop urban food strategies (UFSs) to guide their efforts and practices towards more sustainable food systems. An emerging theme shaping these food policy endeavours, especially prominent in North and South America, concerns the enhancement of social justice within food systems. To operationalise this theme in a European urban food governance context we adopt Nancy Fraser’s three-dimensional theory of justice: economic redistribution, cultural recognition and political representation. In this paper, we discuss the findings of an exploratory document analysis of the social justice-oriented ambitions, motivations, current practices and policy trajectories articulated in sixteen European UFSs. We reflect on the food-related resource allocations, value patterns and decision rules these cities propose to alter and the target groups they propose to support, empower or include. Overall, we find that UFSs make little explicit reference to social justice and justice-oriented food concepts, such as food security, food justice, food democracy and food sovereignty. Nevertheless, the identified resources, services and target groups indicate that the three dimensions of Fraser are at the heart of many of the measures described. We argue that implicit, fragmentary and unspecified adoption of social justice in European UFSs is problematic, as it may hold back public consciousness, debate and collective action regarding food system inequalities and may be easily disregarded in policy budgeting, implementation and evaluation trajectories. As a path forward, we present our plans for the RE-ADJUSTool that would enable UFS stakeholders to reflect on how their UFS can incorporate social justice and who to involve in this pursuit.</p> <p><em>This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 765389. </em></p> <p>Project webpage: <a href="https://recoms.eu/">https://recoms.eu/</a></p>
Qualitative dataset - Socially just urban food policy implementation: a case study in Groningen (NL)
<p>This qualitative dataset contains the transcripts of 43 interviews that have been conducted with members of social food initiatives (e.g. community gardens and orchards, food assistance, social restaurants, food education projects, social employment trajectories, fair trade campaigns, and so on) in the city of Groningen, as well as the interview guide and the information sheet and consent form that have been used during data collection. In addition, the upload includes the interview guide, posters, assessment table, information sheet and consent form that have been used in a two-part focus group with 3 food policy coordinators of the municipality of Groningen. The data was collected from November 2019 till March 2020. The transcripts have been analysed in NVivo (qualitative data analysis software).The link to and abstract of the paper based on this dataset will be provided when our manuscript gets published.</p> <p><em>This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 765389. </em></p> <p>Project webpage: <a href="https://recoms.eu/">https://recoms.eu/</a></p>
Open4DE Textsample: Datenbasis qualitative Dokumentenanalyse
<p>Im Verbundprojekt "<strong>Stand und Perspektiven einer Open-Access-Strategie für Deutschland – Open4DE</strong>" (Förderkennzeichen 16TOA024A-C) wurde für eine qualitative Dokumentenanalyse ein <strong>Sample von 116 Textdokumenten</strong> erstellt. Im Zeitraum Juli 2021 bis Januar 2022 wurden Open-Access-Policies und thematisch verwandte Textdokumente zur Open-Access-Transformation der Stakeholdergruppen "Bund & Bundesländer", "Universitäten", "Hochschulen", "Wissenschaftsorganisationen" und "Fachgesellschaften" recherchiert. Das Sample umfasst für die Stakeholdergruppe Bund & Bundesländer 8 Dokumente, für die Stakeholdergruppe Universitäten 45 Dokumente, für die Stakeholdergruppe Hochschulen 20 Dokumente, für die Stakeholdergruppe Wissenschaftsorganisationen 11 Dokumente und für die Stakeholdergruppe Fachgesellschaften 32 Dokumente. Die Dokumente wurden in MAXQDA (Software zur qualitativen Text- und Datenanalyse) kodiert und analysiert. Nähere Informationen zur Vorgehensweise der Sample-Erstellung und der qualitativen Datenanalyse finden sich im Open4DE Studienreport: https://doi.org/10.5281/zenodo.7737209.</p> <p>Um einen dauerhaften Zugriff auf die Datenbasis des Samples zu gewährleisten, wurden alle Dokumente im .txt-Dateiformat archiviert. Diese Datenbasis wird hier zugänglich gemacht. Eins der 116 Dokumente unterliegt einer Bezahlschranke. Die archivierte .txt-Datei dieses Dokuments kann deshalb nicht öffentlich zugänglich gemacht werden. Es handelt sich dabei um den Artikel "Open Access" erschienen 2013 in Nachrichten aus der Chemie 61, https://doi.org/10.1002/nadc.201390100. Die Datei "<strong>Open4DE_2021-2023_Sample_Metadatei</strong>" erläutert auf dem Tabellenblatt "Info" die Benennungskonvention der archivierten .txt-Dateien des untersuchten Samples und beschreibt den Dateiaufbau und ihre Struktur. Auf den folgenden Tabellenblättern sind alle im Sample enthaltenen Textdokumente pro Stakeholdergruppe aufgelistet.</p> <p><strong>Bennungskonvention der archivierten .txt-Dateien</strong></p> <p>Für jedes der 116 Textdokumente wurde eine separate .txt-Datei angelegt. Alle 116 .txt-Dateien starten mit dem Dateinamen "Open4DE_Sample_". Es folgt eine Abkürzung für die jeweilige Stakeholdergruppe:</p> <ul> <li>"BBL" = Stakeholdergruppe Bund & Bundesländer</li> <li>"UNI" = Stakeholdergruppe Universitäten</li> <li>"HS" = Stakeholdergruppe Hochschulen</li> <li>"WO" = Stakeholdergruppe Wissenschaftsorganisationen</li> <li>"FG" = Stakeholdergruppe Fachgesellschaften </li> </ul> <p>Innerhalb der Stakeholdergruppen sind die Dokumente alphabetisch sortiert und fortlaufend nummeriert. Dazu folgt auf das Kürzel für die Stakeholdergruppe eine numerische Angabe gemäß dem Schema "01-XX". Für die jeweiligen Stakeholdergruppen ergibt sich damit folgende Benennungskonvention:</p> <ul> <li>Die 8 Open-Access-Strategien und verwandten Dokumente der Stakeholdergruppe Bund und Bundesländer sind benannt als "Open4DE_Sample_BBL01" bis "Open4DE_Sample_BBL08".</li> <li>Die 45 Open-Access-Policies der Stakeholdergruppe Universitäten sind benannt als "Open4DE_Sample_UNI01" bis "Open4DE_Sample_UNI45".</li> <li>Die 20 Open-Access-Policies der Stakeholdergruppe Hochschulen sind benannt als "Open4DE_Sample_HS01" bis ""Open4DE_Sample_HS20".</li> <li>Die 11 Open-Access-Stellungnahmen, Positionspapiere, Polices u.ä. der Stakeholdergruppe Wissenschaftsorganisationen sind benannt als "Open4DE_Sample_WO01" bis "Open4DE_Sample_WO11".</li> <li>Die 32 Open-Access-Positionspapiere, Stellungnahmen und verwandte Dokumente der Stakeholdergruppe Fachgesellschaften sind benannt als "Open4DE_Sample_FG01" bis "Open4DE_Sample_FG32".</li> </ul>
Qualitative dataset based on ancestral knowledge about coffee crops
<p> </p> <p>The qualitative dataset is about coffee pests based on the ancestral knowledge of coffee farmers in the Department of Cauca, Colombia. The dataset has been obtained from a survey applied to coffee growers with 432 records and 41 variables collected weekly from September 2020 to August 2021. The qualitative dataset includes climatic conditions, productive activities, external conditions, and coffee bio-aggressors. This dataset allows researchers to find patterns for coffee crop protection by means of ancestral knowledge not detected by real-time agricultural sensors. As far as we are concerned, there are no datasets like the one presented in this paper with similar characteristics of qualitative value that express the empirical knowledge of coffee farmers used to detect triggers of causal behaviors of pests and diseases in coffee crops.</p>
Tree species identity, diameter and qualitative canopy health measurements (full, partial or dead) from 2005 to 2023 on 12 experimental oak loss plots in Black Rock Forest, NY.
Black Rock Forest established a series of 12, 0.56 ha plots in 2005 to assess impacts of the loss of tree in the genus Quercus on the forest ecosystem (entitled the Future of Oak Forests experiment). Three trunk girdling treatments, with control plots were instituted in 2008. Each plot also contained an ~10m by ~15m deer exclosure to assess the impact of herbivory post-disturbance. Trees were measured twice per year from 2008 to 2013 (except 2009 when trees were measured once) and once per year from 2014 to 2023. Data include tree species identity, diameter at breast height (DBH), canopy health (a qualitative assessment of approximate cover as full, partial or dead), presence/absence of sprouts, and location within the plot. All live trees equal to or larger than 2.5 cm DBH are included in the dataset.
Artifact for the EASE 2020 Paper: How Can I Contribute? A Qualitative Analysis of Community Websites of 25 Unix-Like Distributions
<p>Artifact for the EASE 2020 Paper: How Can I Contribute? A Qualitative Analysis of Community Websites of 25 Unix-Like Distributions</p> <p>Jacob Krüger, Sebastian Nielebock, Robert Heumüller</p> <p> </p> <p>Please refer to the readme for more details</p>
Heatmaps of quantitative and qualitative phenotypes of zebrafish pronephroi upon compound exposure
<p>Heatmaps of quantitative and qualitative phenotypes of embryonic zebrafish pronephroi after exposure to compounds from the Prestwick library.</p> <p>For further details please see:</p> <p><em>Westhoff JH, Steenbergen PJ, Thomas LSV, Heigwer J, Bruckner T, Cooper L, Tönshoff B, Hoffmann GF and Gehrig J (2020) In vivo High-Content Screening in Zebrafish for Developmental Nephrotoxicity of Approved Drugs. Front. Cell Dev. Biol. 8:583. doi: 10.3389/fcell.2020.00583</em></p> <p>The images represent full resolution versions of the thumbnails presented in: </p> <ol> <li>Supplementary Figure 3 | Fully annotated heat map of quantitative features.</li> <li>Supplementary Figure 4 | Fully annotated heat map of qualitative features.</li> </ol> <p> </p> <p> </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)
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.