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43 results for “science mapping”
Raw Data for Mapping Repositories and their Institutional Open Science Policies in Asia
<p>Persistent Identifiers (PIDs), particularly Digital Object Identifiers (DOIs), are crucial for establishing a robust and globally accessible research infrastructure. In Asia, a diverse array of research outputs and resources are produced and published in repositories. However, a significant number of these repositories, and outputs remain undiscoverable in global registries and aggregators. <br><br>These three datasets provides comprehensive information on the adoption of repositories, Open Access mandates, and DOIs adoption in Asian countries. It includes detailed records from different registry sources and repository platforms.<br><br>You can read the full report titled 'Mapping Repositories and their Institutional Open Science Policies in Asia' at <a href="https://doi.org/10.5281/zenodo.12566244">https://doi.org/10.5281/zenodo.12566244</a></p>
Raw Data for Mapping Repositories and their Institutional Open Science Policies in the Middle East and North Africa (MENA)
<div> <p>Persistent Identifiers (PIDs), particularly Digital Object Identifiers (DOIs), are crucial for establishing a robust and globally accessible research infrastructure. In the Middle East and North Africa (MENA) region, a diverse array of research outputs and resources are produced and published in repositories. However, a significant number of these repositories, and outputs remain undiscoverable in global registries and aggregators. <br><br>These three datasets provides comprehensive information on the adoption of repositories, Open Access mandates, and DOIs adoption in MENA countries. It includes detailed records from different registry sources and repository platforms.<br><br>You can read the full report titled 'Mapping Repositories and their Institutional Open Science Policies in MENA' at <a href="https://doi.org/10.5281/zenodo.11370031">https://doi.org/10.5281/zenodo.11370031</a></p> </div>
Dataset: Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication
<p>The rainbow color map is scientifically incorrect and hinders people with color vision deficiency to view visualizations in a correct way. Due to perceptual non-uniform color gradients within the rainbow color map the data representation is distorted what can lead to misinterpretation of results and flaws in science communication. Here we present the data of a paper survey of 797 scientific publication in the journal Hydrology and Earth System Sciences. With in the survey all papers were classified according to color issues. Find details about the data below.</p> <ul> <li><code>year</code> = year of publication (YYYY)</li> <li><code>date</code> = date (YYYY-MM-DD) of publication</li> <li><code>title</code> = full paper title from journal website</li> <li><code>authors</code> = list of authors comma-separated</li> <li><code>n_authors</code> = number of authors (integer between 1 and 27)</li> <li><code>col_code</code> = color-issue classification (see below)</li> <li><code>volume</code> = Journal volume</li> <li><code>start_page</code> = first page of paper (consecutive)</li> <li><code>end_page</code> = last page of paper (consecutive)</li> <li><code>base_url</code> = base url to access the PDF of the paper with <code>/volume/start_page/year/</code></li> <li><code>filename</code> = specific file name of the paper PDF (e.g. <code>hess-9-111-2005.pdf</code>)</li> </ul> <p>Color classification is stored in the <code>col_code</code> variable with:</p> <ul> <li><code>0</code> = chromatic and issue-free,</li> <li><code>1</code> = red-green issues,</li> <li><code>2</code>= rainbow issues and</li> <li><code>bw</code>= black and white paper.</li> </ul> <p> </p> <p>See more details (e.g., sample code to analyse the survey data) on https://github.com/modche/rainbow_hydrology</p> <p>Paper: Stoelzle, M. and Stein, L.: Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication, Hydrol. Earth Syst. Sci., 25, 4549–4565, https://doi.org/10.5194/hess-25-4549-2021, 2021.</p> <p> </p> <p> </p>
TIME4CS WP4 Mapping of citizen science training resources
<p>This dataset was compiled as part of the TIME4CS project, WP4, and lists identified citizen science training resources, as of July 2022.</p> <p>The <a href="https://eu-citizen.science/">EU-citizen.science</a> platform provided the basis for mapping CS training in Europe, as the team behind the platform has put considerable effort into compiling, and encouraging the CS community to contribute, CS training resources. Additionally, training courses were identified based on the case studies in WP1, as most universities do not list their courses on the EU-citizen.science platform.</p>
Supplementary data to `Do science maps from open access literature capture the overall topic structure of an academic field?`
<p>The dataset contains the 8,528 academic articles records related to Sustainable Food research sourced with the query `TS=("sustainab*" NEAR/2 "food*")` .</p> <p>They are the records present in the largest component of the citation network, as specified in the manuscript. </p> <p>The dataset was sourced from OpenAlex based on the original data used in the manuscript and it is composed of the following columns:</p> <table> <tbody> <tr> <td><em><strong>Column</strong></em></td> <td><em><strong>Description</strong></em></td> </tr> <tr> <td>Id</td> <td>OpenAlex ID</td> </tr> <tr> <td>DOI</td> <td>Document Object Identifier</td> </tr> <tr> <td>display_name</td> <td>The article title</td> </tr> <tr> <td>publication_year</td> <td>The publication year of the article</td> </tr> <tr> <td>open_access</td> <td>An object with details of the open access status of the article</td> </tr> </tbody> </table> <p>We choose the `.rdata` format for easy loading in R. Use the function `load()` to add the data frame to the enviroment. </p>
X-ray Fluorescence Mapping dataset for use in Heritage Science
<p>The following data sets were collected to support the potential uses of opensource data in the context of digital humanities and heritage sciences. </p> <p>This proposed experiment is conducted by the UCL Institute for Sustainable Heritage in collaboration with the Centre for Digital Humanities. Imaging methods including Photography, Multispectral Imaging, Hyperspectral Imaging and Xray Fluorescence Mapping have been collected along with the complete readout metadata of the instrumentation. </p> <p>We hope that you find the data helpful, and we welcome you to use the data in any way you wish, for all and any analysis development purposes. For us to build upon this research, we ask that in return you would be willing to share in some regard your experiences in using open-source data, using our data, successes and issues. </p> <p>If you would be willing to engage with us in this endeavor, please feel free to contact us so that we may be able to follow up with you. </p> <p>Other Data sets available <a href="https://zenodo.org/record/7319696#.Y3NuOXbP2Uk">Here</a></p> <p>E: <a href="mailto:molly.fort.21@ucl.ac.uk">molly.fort.21@ucl.ac.uk</a> </p> <p>Object Paradata; </p> <ul> <li><strong>Postcard – c. Early 1900's </strong></li> <li><strong>Language – Eng. </strong></li> <li><strong>Materials – colour print on card, metallic leafing. </strong></li> <li><strong>Front transcription - </strong></li> <li><strong> ‘Greetings’ </strong></li> <li><strong> ‘May your Birthday bring you Peace & perfect Happiness, Golden hopes & Love of Friends, And every Happiness this world can send.’ </strong></li> <li><strong>Object Dimensions – 138mm X 88mm</strong></li> </ul> <p>The postcard is an item of ephemera donated to the UCLDH Digitisation Suite by Prof Melissa Terras, for teaching and training purposes in 2015.</p> <p>This folder contains:</p> <p>X-ray fluorescence imaging map collected from a <a href="https://www.bruker.com/en/products-and-solutions/elemental-analyzers/micro-xrf-spectrometers/m4-tornado-plus.html">Bruker M4+ Tornado Micro-XRF System</a></p> <ul> <li>Postcardmap1.bcf - Bruker composite file containing full fluorescence spectral and mapping data with some other information. Can be read by Bruker software or using freely dowloadable <a href="https://hyperspy.org/">Hyperspy</a>.</li> <li>EDX.hdf5 - full fluorescence spectral and mapping data in open format, created and readable via. Hyperspy.</li> <li>Postcard_data.txt - metadata saved in ASCII format by Bruker system.</li> <li>postcardmap1_*.png - individual png images of mapped elements, listed in filename. </li> </ul> <p> </p>
Package and Dependency Metadata for CZI Hackathon: Mapping the Impact of Research Software in Science
<p>A collection of useful datasets extracted from <a href="https://packages.ecosyste.ms">https://packages.ecosyste.ms</a> and <a href="https://repos.ecosyste.ms/">https://repos.ecosyste.ms</a> for use at the CZI Hackathon: Mapping the Impact of Research Software in Science.</p><p>All data is provided as NDJSON (new line delimited JSON), each line represents a valid JSON object, and they are separated by newline characters. There are <a href="https://pypi.org/project/ndjson/">python</a> and <a href="https://www.rdocumentation.org/packages/ndjson/versions/0.9.0/topics/stream_in">R</a> libraries for reading these files, or you can maually read each line and parse each line as a single JSON object.</p><p>Each ndjson file has been compressed with gzip (actual command: `tar -czvf`) to reduce download size, they expand to significantly bigger files after extraction.</p><h4>Package Data</h4><p>Package names from cran, bioconductor and pypi that have been parsed by the <a href="https://github.com/chanzuckerberg/software-mentions">software-mentions</a> project (data: <a href="https://datadryad.org/stash/dataset/doi:10.5061/dryad.6wwpzgn2c">https://datadryad.org/stash/dataset/doi:10.5061/dryad.6wwpzgn2c</a>) are collected together with their latest release at time of publishing along with the names of their dependencies, those dependency names have then also been recursively fetched with latest release and dependencies until the full list of transitive dependencies is included. </p><p>Note: This approach uses a simplified method of dependency resolution, always picking the latest version of each package rather than taking into account each dependencies specific version range requirements, this is primarily due to time constraints and allows all software ecosystems to be processed in the same way. A future improvement would be to use each package ecosystem's specific dependency resolution algorithm to compute the full transitive dependency tree for each mentioned software package.</p><h4>GitHub Data</h4><p>Two different approaches were taken for collecting data for referenced GitHub mentions:</p><p>1. `github.ndjson` is metadata for each repository from GitHub, including "manifest" files which are known files that contain dependency information for a project such as requirements.txt, DESCRIPTION and package.json, parsed using <a href="https://github.com/ecosyste-ms/bibliothecary">https://github.com/ecosyste-ms/bibliothecary</a>, which may include transitive dependencies that have been discovered in a `lockfile` within the repository.</p><p>2. `github_packages.ndjson` is metadata for each package that was found on any package manager that references the GitHub url as it's repository url/source/homepage, these packages, like the cran and pypi data above, include the latest release and their direct dependencies. There may be more than one package for each GitHub URL as it is a one to many relationship. `github_packages_with_transitive.ndjson` follows the same format but also includes the extra resolved transitive dependencies of all packages using the same approach as with cran and pypi data above with the same caveats. </p><p>There are also many more ecosystems referenced in these files than just cran, bioconductor and pypi, https://packages.ecosyste.ms provides a standardized metadata format for all of them to enable comparison and simplification of automation.</p><h4>Contact</h4><p>If you would like any help, support or more data from Ecosyste.ms please do get in touch via email: hello@ecosyste.ms or open an issue on GitHub: https://github.com/ecosyste-ms/packages/issues</p>
Text-fig. 5. Vegetation zones in P. R. China (Editorial Committee of Vegetation Map of China, The Chinese Academy of Sciences 2007), and assumed location of extant reference vegetation type of Wiesa fossil assemblage (rectangle), as revealed from qualitative floristic analysis. Extant reference vegetation type present in southern belt of zone of subtropical evergreen broadleaved forest, with minor overlap into zone of tropical forest. in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)
Text-fig. 5. Vegetation zones in P. R. China (Editorial Committee of Vegetation Map of China, The Chinese Academy of Sciences 2007), and assumed location of extant reference vegetation type of Wiesa fossil assemblage (rectangle), as revealed from qualitative floristic analysis. Extant reference vegetation type present in southern belt of zone of subtropical evergreen broadleaved forest, with minor overlap into zone of tropical forest.
Data for: Image-based evaluation of beers at an online Pint of Science festival using Projective Mapping, Check-All-That-Apply and Acceptability
<p>Data obtained from n=67 untrained attendants at an outreach Pint of Science festival, online because of the COVID-19 pandemic but usually held at bars. The participants used images of brand logos to evaluate eight beers among the most commonly consumed in Spain. Three sensory analysis techniques were used: Projective Mapping, Acceptability and Check-All-That-Apply (CATA).</p>
Map of articles about "Teaching Open Science"
<p>This description is part of the blog post "Systematic Literature Review of teaching Open Science" https://sozmethode.hypotheses.org/839</p> <p>According to my opinion, we do not pay enough attention to teaching Open Science in higher education. Therefore, I designed a seminar to teach students the practices of Open Science by doing qualitative research.About this seminar, I wrote the article ”<a href="https://osf.io/preprints/socarxiv/b3zf7">Teaching Open Science and qualitative methods</a>“. For the article ”Teaching Open Science and qualitative methods“, I started to review the literature on ”Teaching Open Science“. The result of my literature review is that certain aspects of Open Science are used for teaching. However, Open Science with all its aspects (Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools) is not an issue in publications about teaching.</p> <p>Based on this insight, I have started a systematic literature review. I realized quickly that I need help to analyse and interpret the articles and to evaluate my preliminary findings. Especially different disciplinary cultures of teaching different aspects of Open Science are challenging, as I myself, as a social scientist, do not have enough insight to be able to interpret the results correctly. Therefore, I would like to invite you to participate in this research project!</p> <p>I am now looking for people who would like to join a collaborative process to further explore and write the systematic literature review on “Teaching Open Science“. Because I want to turn this project into a Massive Open Online Paper (MOOP). According to the <a href="https://osf.io/preprints/socarxiv/b3zf7">10 rules of Tennant et al (2019) on MOOPs</a>, it is crucial to find a core group that is enthusiastic about the topic. Therefore, I am looking for people who are interested in creating the structure of the paper and writing the paper together with me. I am also looking for people who want to search for and review literature or evaluate the literature I have already found. Together with the interested persons I would then define, the rules for the project (cf. Tennant et al. 2019). So if you are interested to contribute to the further search for articles and / or to enhance the interpretation and writing of results, please get in touch. For everyone interested to contribute, the list of articles collected so far is freely accessible at Zotero: <a href="https://www.zotero.org/groups/2359061/teaching_open_science">https://www.zotero.org/groups/2359061/teaching_open_science</a>. The figure shown below provides a first overview of my ongoing work. I created the figure with the free software <a href="https://www.yworks.com/products/yed">yEd</a> and uploaded the file to zenodo, so everyone can download and work with it:</p> <p>To make transparent what I have done so far, I will first introduce what a systematic literature review is. Secondly, I describe the decisions I made to start with the systematic literature review. Third, I present the preliminary results.</p> <p><strong>Systematic literature review – an Introduction </strong></p> <p>Systematic literature reviews “are a method of mapping out areas of uncertainty, and identifying where little or no relevant research has been done.” (Petticrew/Roberts 2008: 2). Fink defines the systematic literature review as a “systemic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners.” (Fink 2019: 6). The aim of a systematic literature reviews is to surpass the subjectivity of a researchers’ search for literature. However, there can never be an objective selection of articles. This is because the researcher has for example already made a preselection by deciding about search strings, for example “Teaching Open Science”. In this respect, transparency is the core criteria for a high-quality review. </p> <p>In order to achieve high quality and transparency, Fink (2019: 6-7) proposes the following seven steps:</p> <ol> <li>Selecting a research question.</li> <li>Selecting the bibliographic database.</li> <li>Choosing the search terms.</li> <li>Applying practical screening criteria.</li> <li>Applying methodological screening criteria.</li> <li>Doing the review.</li> <li>Synthesizing the results.</li> </ol> <p>I have adapted these steps for the “Teaching Open Science” systematic literature review. In the following, I will present the decisions I have made.</p> <p><strong>Systematic literature review – decisions I made</strong></p> <ol> <li><strong>Research question</strong>: I am interested in the following research questions: How is Open Science taught in higher education? Is Open Science taught in its full range with all aspects like Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools? Which aspects are taught? Are there disciplinary differences as to which aspects are taught and, if so, why are there such differences?</li> <li><strong>Databases</strong>: I started my search at the <a href="https://doaj.org/">Directory of Open Science (DOAJ)</a>. “DOAJ is a community-curated online directory that indexes and provides access to high quality, open access, peer-reviewed journals.” (https://doaj.org/) Secondly, I used the <a href="http://base-search.net">Bielefeld Academic Search Engine (base)</a>. Base is operated by Bielefeld University Library and “one of the world’s most voluminous search engines especially for academic web resources” (base-search.net). Both platforms are non-commercial and focus on Open Access publications and thus differ from the commercial publication databases, such as Web of Science and Scopus. For this project, I deliberately decided against commercial providers and the restriction of search in indexed journals. Thus, because my explicit aim was to find articles that are open in the context of Open Science.</li> <li><strong>Search terms</strong>: To identify articles about teaching Open Science I used the following search strings: “teaching open science” OR teaching “open science” OR teach „open science“. The topic search looked for the search strings in title, abstract and keywords of articles. Since these are very narrow search terms, I decided to broaden the method. I searched in the reference lists of all articles that appear from this search for further relevant literature. Using Google Scholar I checked which other authors cited the articles in the sample. If the so checked articles met my methodological criteria, I included them in the sample and looked through the reference lists and citations at Google Scholar. This process has not yet been completed.</li> <li><strong>Practical screening criteria</strong>: I have included English and German articles in the sample, as I speak these languages (articles in other languages are very welcome, if there are people who can interpret them!). In the sample only journal articles, articles in edited volumes, working papers and conference papers from proceedings were included. I checked whether the journals were predatory journals – such articles were not included. I did not include blogposts, books or articles from newspapers. I only included articles that fulltexts are accessible via my institution (University of Kassel). As a result, recently published articles at Elsevier could not be included because of the special situation in Germany regarding the Project DEAL (https://www.projekt-deal.de/about-deal/). For articles that are not freely accessible, I have checked whether there is an accessible version in a repository or whether preprint is available. If this was not the case, the article was not included. I started the analysis in May 2019.</li> <li><strong>Methodological criteria</strong>: The method described above to check the reference lists has the problem of subjectivity. Therefore, I hope that other people will be interested in this project and evaluate my decisions. I have used the following criteria as the basis for my decisions: First, the articles must focus on teaching. For example, this means that articles must describe how a course was designed and carried out. Second, at least one aspect of Open Science has to be addressed. The aspects can be very diverse (FOSS, repositories, wiki, data management, etc.) but have to comply with the principles of openness. This means, for example, I included an article when it deals with the use of FOSS in class and addresses the aspects of openness of FOSS. I did not include articles when the authors describe the use of a particular free and open source software for teaching but did not address the principles of openness or re-use.</li> <li><strong>Doing the review</strong>: Due to the methodical approach of going through the reference lists, it is possible to create a map of how the articles relate to each other. This results in thematic clusters and connections between clusters. The starting point for the map were four articles (Cook et al. 2018; Marsden, Thompson, and Plonsky 2017; Petras et al. 2015; Toelch and Ostwald 2018) that I found using the databases and criteria described above. I used yEd to generate the network. „<strong>yEd</strong> is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams.” (<a href="https://www.yworks.com/products/yed">https://www.yworks.com/products/yed</a>) In the network, arrows show, which articles are cited in an article and which articles are cited by others as well. In addition, I made an initial rough classification of the content using colours. This classification is based on the contents mentioned in the articles’ title and abstract. This rough content classification requires a more exact, i.e., content-based subdivision and evaluation by others, who are experts in the respective fields/disciplines.</li> </ol>
Database Publication - Exploring adult age-at-death research in anthropology: Bibliometric mapping and content analysis, Forensic Sciences, 2023
<p>The dataset contains the publications' ID and DOI numbers used in the bibliometric analysis for the paper "Exploring adult age-at-death research in anthropology: Bibliometric mapping and content analysis," which was published in Forensic Sciences. Dimensions only granted the authors permission to disclose the publication IDs and DOIs for this study. However, using the identification codes, it is possible to extract titles' full metadata through Dimensions (<a href="https://www.dimensions.ai/">https://www.dimensions.ai/</a>).</p>
Drawing the Boundaries Around Borderline Personality Disorder: A Science Mapping Study
<p><strong>Objective: </strong>The objective of this study was to conduct a bibliometric investigation of borderline personality disorder (BPD) including performance analysis, science mapping, and network visualization. <strong>Methods: </strong>Publications relating to BPD were retrieved from the Web of Science™ by entering the term “borderline personality disorder(all-fields)” and analyzed with the Bibliometrix.. R<strong>esults: </strong>A total of 10,368 documents on BPD were published from 1980 to 2022. Publication volume increased by an average annual rate of 13.7%. The total number of citations of the period was 361,184, with an average citation per document of 34.8. Articles in “medical” journals tended to cite articles in the “medical” ones, while those in “psychological” journals did the same with their “psychological” counterparts. The list of the most cited articles includes predominantly studies on several modalities of psychotherapy for BPD. Articles about psychotherapy formed a separate co-citation cluster from the main body of publications and authors with stronger research imprinting on cognitive, dialectical, and mentalization- and schema-based psychotherapies formed a separate cluster from other authors, possibly reflecting the pivotal role played by psychotherapies in the treatment of BPD. European countries collaborated among themselves, while the USA stood relatively apart. German, Dutch, and Swiss institutions, headed by the Heidelberg University, cooperated mainly among themselves while the USA ones formed separated networks around Harvard University. <strong>Conclusions: </strong>Our results indicate that research on BPD is a conceptually and thematically heterogeneous, geographically and institutionally diversified, integrated collaborative enterprise.</p> <p> </p>
Mind Map of The European Bioinformatic infrastructure for the Life Sciences (ELIXIR) activities
<p>This diagram showcases the organisation of the different components of the ELIXIR network, with brief description of the activities therein.</p>
MapOSR - A Mapping Review Dataset of Empirical Studies on Open Science
<p>Research that investigates respective researchers’ engagement in Open Science varies widely in the topics addressed, methods employed, and disciplines investigated, which makes it difficult to integrate and compare its results. To investigate current outcomes of Open Science research, and to get a better understanding on topicswell-researched and on research gaps we aim at providing an openly accessible overview of empirical studies that focus on different aspects of Open Science in different scientific disciplines, academic groups and geographical regions. The present data set of studies about Open Science practices was retrieved following a PRISM approach to compile a literature review. We include studies from the Scopus and Web of Science databases with keywords relating to Open Science between the years 2000 and 2020, as well as a snowball search for relevant articles. Studies that did not investigate any aspect of Open Science, or weren’t peer reviewed were excluded, resulting in a total of 695 remaining studies. The data set was collaboratively annotated to ensure intercoder reliability of the coded data.</p>
A Systematic Mapping of the Classification of Open Educational Resources for Computer Science Education in Digital Sources (Data)
<p>Data from a Systematic Mapping of the classification of Open Educational Resources for Computer Science Education.</p> <p>Content:</p> <ul> <li>Studies selected</li> <li>Digital sources used to classify Open Educational Resources for Computer Science Education</li> <li>Computer Science domains explored by Open Educational Resources</li> <li>Approaches for the classification of Open Educational Resources for Computer Science Education</li> </ul>
Supplementary Material to "Identifying major research themes in Sport Science" (Interactive Science Maps)
<p><strong>Links to interactive maps</strong></p> <p>(1) Link: <strong><a href="https://app.vosviewer.com/?map=https://drive.google.com/uc?id=182n1HEZygAoS_9Caxj83hi27y41N6SWm&item_size=4">World Map</a></strong> (<a href="https://tinyurl.com/2zufzslg">https://tinyurl.com/2zufzslg</a>)</p> <p>(2) Link: <strong><a href="https://app.vosviewer.com/?map=https://drive.google.com/uc?id=182n1HEZygAoS_9Caxj83hi27y41N6SWm&item_size=5&item_size_variation=0.4&scale=0.9">Sport Science Map</a></strong> (<a href="https://tinyurl.com/2fztyjhf">https://tinyurl.com/2fztyjhf</a>)</p>
The data of "A comparison of citation-based clustering and topic modeling for science mapping"
<p>These files consist of the data used in "A comparison of citation-based clustering and topic modeling for science mapping". </p> <p> </p>
MAPS Trial: Matrix And Platinum Science
ClinicalTrials.gov study NCT00396981. IPD Sharing: Not stated. Countries: 11. Publications: 2.
Louse flies (Diptera: Hippoboscidae): United Kingdom, Republic of Ireland and Isle of Man: Citizen science data: Part 1, mapping
Open the record for dataset details and reuse information.
Data from: Mapping wing morphs of Tetrix subulata using citizen science data: flightless groundhoppers are more prevalent in grasslands near water
<p>To analyse the correlation between groundhopper wing morph and landscape characteristics, we collected the following data. GBIF observations of <em>Tetrix subulata</em> (Linnaeus, 1758) in the Netherlands were annotated with wing morph and sex (based on the images), and weather and landscape information (based on the location). The weather information is based on an interpolation of data from the Royal Netherlands Meteorological Institute (KNMI). Landscape and habitat information was characterised by determining the area of different area types, from the Basisregistratie Topografie (BRT) TOP10NL dataset, in a radius around the observation. The landscape information also includes Dutch physical-geographical regions. To check for possible effects of seasonality, the event date of the observation is included. To check for the effect of the landscape radius on the analysis, those analyses were repeated for different radiuses. Depending on the precision of the coordinate location, some radiuses could not be tested for some observations. </p> <p>The file "data.csv" contains one row per observation-radius combination, with the following columns (* repeated for each radius):</p> <table> <tbody> <tr> <td><strong>Columns</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>gbifID*</td> <td>ID of the observation on GBIF</td> </tr> <tr> <td>eventDate*</td> <td>Date of observation (YYYY-MM-DD)</td> </tr> <tr> <td>wing_morph*</td> <td>Wing morph annotation (long; short)</td> </tr> <tr> <td>sex*</td> <td>Sex annotation (female; male; obscured; multiple; reevaluate i.e. unknown)</td> </tr> <tr> <td>region*</td> <td>Physical-geographical region in which the observation was made</td> </tr> <tr> <td>temperature*</td> <td>Predicted temperature (average over 1991-2020; degrees Celsius)</td> </tr> <tr> <td>windspeed*</td> <td>Predicted windspeed (average over 1991-2020; meters per second)</td> </tr> <tr> <td>precipitation*</td> <td>Predicted precipitation (average over 1991-2020; millimeters)</td> </tr> <tr> <td>landscape_radius</td> <td>Landscape radius (50, 100, 200, 500, or 1000 meters)</td> </tr> <tr> <td>deciduous forest, grass, mixed forest, ...</td> <td>Total surface area of given area type in given radius around observation (square meters)</td> </tr> </tbody> </table>
ScienceDex guides
Understand access before you commit
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.