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6,025 results for “Science of science”
Enquête par questionnaire humanités "Manipuler des données en Sciences Humaines et Sociales (SHS) : R, Python, ou autre ?"
<p>Ce sondage réalisé avec Framaform https://framaforms.org/manipuler-des-donnees-en-sciences-humaines-et-sociales-shs-r-python-ou-autre-1675889669 était destiné à tous les personnels impliqués dans la recherche et / ou l'enseignement en sciences humaines et sociales mobilisant du traitement de données (humanités numériques, sciences sociales computationnelles, etc.). Il a été diffusé sur la liste de diffusions DH, sur les sites de l'Observatoire des Humanités numériques de l'ENS PSL et de l'INSHS du CNRS.</p><p>L'enquête visait à mieux connaître les usages de la programmation chez les chercheurs, enseignants-chercheurs, étudiants et personnels de soutien à la recherche. Les résultats obtenus permettent de proposer un état des lieux de l'existant afin d'accompagner et d'améliorer les pratiques en proposant des ressources pour s'informer ou se former.</p><p>217 personnes ont répondu à cette enquête ce qui nous a permis de dresser un panorama réaliste des pratiques actuelles relevant de la programmation en SHS.</p><p>Le fichier .json permet de recoder le nom des colonnes.</p><p>Un notebook d'analyse est disponible ici : https://github.com/emilienschultz/digit_hum_2023/blob/main/2023_Digit_Hum_Exploration_sondage_v2.ipynb</p>
Infographics of six key aspects in the development of citizen science projects
<p>These six infographics describe six key aspects in the development of citizen science projects. The six key ideas are: co-creation, communities, tools and methods, data, ethics and inclusion, and action. Each infographics condensates several ideas and messages in three columns: why is the aspect is important, how can this aspect be further develop and finally a set of practical recommendations.</p> <p>The digital material is also available at the Universitat de Barcelona <a href="https://web.ub.edu/en/web/ciencia-ciutadana/">website</a> on citizen science. The material is being used in certified training activities on citizen science and developed by the <a href="http://www.ub.edu/opensystems/">OpenSystems</a> research group. The first use of this material is being done during a certified training program offered by IDP-ICE UB: Training in citizen science: Introduction and deepening in the development of participatory research projects with social commitment. It had a 10 h duration and it was oriented to a wide audience that mostly include universities staff, civil society organisations representatives, university students, and public administration staff.</p> <p>Infographics created under the CSNOW project with the Citizen Science Work Group of the IDP-ICE UB, coordinated by Josep Perelló with the support of Núria Coll-Bonfill. Translations from Catalan to English have been possible with the support of the TORCH EU project. Design: <a href="https://minimalheroes.tv">Minimal Heroes</a>.</p>
Understanding trophic interactions in a warming world by bridging foraging ecology and biomechanics with network science
<p><strong><em><span>Background</span></em></strong></p> <p><span>Leaf-cutter ants (<em>Atta</em> spp. and <em>Acromyrmex </em>spp.) are the principal insect pest and a major ecosystem engineer throughout the Neotropics (Leal et al., 2014; Wirth et al., 2003). They harvest plant matter in the surroundings of their colonies to grow a fungus as crop, and in doing so they cut plant matter on an almost industrial scale: about 15 % of the foliar biomass in the Neotropics, or about every sixth leaf, is consumed by leaf-cutter ant colonies (Costa et al., 2008; Fowler et al., 1989; Herz et al., 2007; Wirth et al., 2003), and more than half of all woody species are attacked by them (Cherrett, 1968; Rockwood, 1976). Leaf-cutter ants are perhaps the most voracious and polyphagous herbivorous insects (Lugo et al., 1973; Wirth et al., 2003), and their foraging activity is affected by a variety of environmental conditions, including wind (Alma et al., 2016b), precipitation (Steadman et al., 2020) and barometric pressure (Sujimoto et al., 2020), all of which will be subject to variation due to climate change. </span></p> <p><span>Although leaf-cutter foraging is clearly a complex, multi-factorial behaviour, it has at its core a biomechanical interaction between ant consumer and plant food resource: the force the ants can apply must exceed the force required to drag the mandible through the tissue (Püffel, Roces, et al., 2023; Püffel, Walthaus, et al., 2023). The magnitude of the available bite force is determined by worker size, and the magnitude of the minimum required cutting force is determined by structural and mechanical properties of the plant leaf; consumer and resource properties interact. This mechanical competition has resulted in extraordinary adaptations in both the anatomy and physiology of the leaf-cutter ant bite apparatus: their disproportionately large heads are filled to the rim with optimally packed mandible closer muscles (Püffel et al., 2021). Both their muscle stress and size-specific bite forces are among the highest measured for any animal (Püffel, Johnston, et al., 2023; Püffel, Roces, et al., 2023), and their mandibles are close to “ideally sharp” (Püffel, Walthaus, et al., 2023). As a result, the vast majority of worker sizes can cut the majority of tropical leafs; without these adaptations, and a bite performance commensurate with their body size, only the largest workers would be able to perform this crucial mechanical task (Püffel, Roces, et al., 2023). How will a warming climate affect resource accessibility for the leaf-cutters?</span></p> <p><span>Temperature increases have various implications for the trophic interactions of ants, including altered search behaviour <span>(Frizzi, 2018),</span> and foraging site selection (Spicer et al., 2017; Traniello et al., 1984). An increase in average temperatures can also drive body size decreases in insects (Tseng et al., 2018), including ants (Molet et al., 2017)<a href="https://www.zotero.org/google-docs/?broken=QmLD4C"><span>,</span></a> concomitantly reducing their available bite force (Püffel, Roces, et al., 2023; Rühr et al., 2022). Since leaf-cutter mandibles are so sharp that they already cut with a force close to the minimum dictated by cutting mechanics, the force required to cut leaves will likely be unaffected (Püffel, Walthaus, et al., 2023), and any change in body size will therefore only significantly impact bite forces. Because the relationship between bite forces and body size in the leaf-cutter is well understood mechanistically (Püffel, Roces, et al., 2023), it is possible to predict how these changes will impact trophic networks. A very rough estimate of the change in network structure serves to illustrate how network science can integrate biomechanics and foraging ecology to study the effect of climate change on trophic interactions. </span></p> <p><span>To demonstrate the potential of network science to integrate biomechanical and foraging data within the context of climate change, we constructed and analysed hypothetical plant-ant networks across six hypothetical temperatures. </span></p> <p> </p> <p><strong><em><span>Datasets and methods</span></em></strong></p> <p><span>All analysis was performed in R version 4.3.1 (R Core Team, 2023), and data processed reproducibly via the ‘tidyverse’ package (Wickham et al., 2019). We compiled two datasets and some additional contextual information. Leaf-cutter ant biomass (a proxy for body size) and bite force data were taken from <span>Püffel et al. (2023)</span> for 248 individual ants across three colonies. Required cutting forces for 1197 individual plants representing 868 taxa available to leaf-cutter ants were taken from <span>Onoda et al. (2011)</span>. Insect temperature-body size relationships were taken from <span>Tseng et al. (2018)</span>; specifically, a body size decrease of 1.56 % per degree Celsius increase for museum specimens, to represent gradual long-term change. Based on these data, edgelists (i.e., pairwise lists of consumers and resources) were generated for ants and plants in which binary interaction weights were applied; where bite forces exceeded the force required to cut leaves, a weighting of 1 was given, and 0 otherwise. This edgelist was then replicated for incremental increases of 1 °C up to a 5 °C increase by adjusting bite forces based on incremental body size decreases of 1.56 %. In order to estimate the change of bite force with body mass, we used direct bite force measurements from Püffel et al. (2023), which suggest that maximum bite force in <em>Atta vollenweideri</em> varies with body mass <em>m</em> as <em>T ~ m^0.9</em>. Thus, if body size decreases by a factor of 0.9844 (i.e., 1.56 % decrease) with every degree Celsius temperature increase, then the maximum bite force decreases by a factor of 0.9844<em><sup>0.9</sup></em>. Consequently, adjusted bite forces were calculated, and new binary edgelist weightings generated based on whether the adjusted bite force was greater than the required cutting force.</span></p> <p><span>Bipartite networks were constructed with consumer nodes and resource nodes representing the three ant colonies and the 868 plant taxa, respectively. All six networks were visualised using ‘ggnetwork’ (Briatte, 2021) via ‘igraph’ (Csardi & Nepusz, 2006) in a single network diagram to highlight persistence of links across temperatures using scaled red colours. Network metrics, specifically consumer degree (the number of plants ants were deemed able to interact with) and generality (the total range of plants accessible across all ants), were generated via the ‘bipartite’ package (Dormann et al., 2008) and visually compared via ‘ggplot2’ (Wickham, 2016).</span></p>
Careers in Science and Healthcare - How changes to medical device regulation have increased training needs
<p>Article contributed to Careers in Science and Healthcare report.</p>
Community-science reveals delayed fall migration of waterfowl and spatiotemporal effects of a changing climate
<p>Climate change has well-documented, yet variable, influences on the annual movements of migratory birds. The effects of climate change on fall migration remains understudied compared to spring, but appears to be less consistent among species, regions, and years. Changes in the pattern and timing of waterfowl migration in particular may result in cascading effects on ecosystem function, and socioeconomic and cultural outcomes. We investigated changes in the migration of 15 waterfowl species along a major flyway corridor of continental importance in northeastern North America using 43 years of community-science data. We built spatially- and temporally-explicit hierarchical generative additive models for each species and demonstrated that climate, specifically the interaction between minimum temperature and precipitation, significantly influences migration phenology for most species. Certain species' migratory movements responded to specific temperature thresholds (climate migrants) and others reacted more to the interaction of temperature and precipitation (extreme event migrants). There are already significant changes in the fall migration phenology of common waterfowl species with high ecological and economic importance, which may simply increase in the context of a changing climate. If not addressed, climate change could induce mismatches in management, regulations, and population surveys which would negatively impact the hunting industry. Our findings highlight the importance of considering species-specific spatiotemporal scales of effect on climate on migration and our methods can be widely adapted to quantify and forecast climate-driven changes in wildlife migration.</p>
Community science enhances modelled bee distributions in a tropical Asian city
<p>Bees and the ecosystem services they provide are vital to urban ecosystems, but little is understood about their distributions, particularly in the Asian tropics. This is largely due to taxonomic impediments and limited inventorying, monitoring, and digitization of occurrence records. While expert collections (EC) are demonstrably insufficient by themselves as a data source to model and understand bee distributions, the boom of community science (CS) in urban areas provides an untapped opportunity to learn about bee distributions within our cities. We used CS observations in combination with EC observations to model the distribution of bees in Singapore, a small tropical city-state in Southeast Asia. To address the restricted spatial context, we performed multiple bias corrections and show that species distribution models performed well when estimating the distribution of habitat specialists with distinct range limits detectable within Singapore. We successfully modelled 37 bee species, where model statistics improved for 23 species upon the incorporation of CS observations. Nine species had insufficient EC observations to obtain acceptable models, but could be modelled with the incorporation of CS observations. This is the first study to combine both EC and CS observations to map and model the occurrences of tropical Asian bee species for a highly urbanised region at such fine resolution. Our results suggest that urban landscapes with impervious surfaces and higher temperatures are less suitable for bee species, and such findings can be used to advise the management of urban landscapes to optimise the diversity of bee pollinators and other organisms.</p>
The FjordPhyto citizen science project in the Antarctic Peninsula
<p>FjordPhyto, funded by the United States National Science Foundation (NSF) in 2016-2019 and by the National Aeronautics and Space Agency (NASA) Citizen Science for Earth Systems Program since 2021, is a citizen science project that examines the impacts of increasing glacier meltwater on local ecosystems at the ice-ocean interface of the Antarctic Peninsula (AP), with an emphasis on the western coast (WAP). The citizen science module is based on a collaboration with the International Association of Antarctica Tour Operators (IAATO). Citizen scientists participate in a "validation safari" in which satellite data informs sampling to validate and refine a new ocean color algorithm to detect the glacial meltwater content of seawater from space. The in-situ measurements are combined with remote sensing data products to address scientific questions related to the impacts of glacial meltwater on phytoplankton community abundance and taxonomic composition. This project implements new field sampling techniques and conducts analyses of phytoplankton diversity through a microscopic and genomics approach.</p> <p>The scientific goals of this Citizen Science project are to determine the spatial extent of glacial meltwater through the seasons and identify concomitant shifts in phytoplankton abundance and community diversity in coastal Antarctic waters. Repeated sampling of this region from November to March along 3-6 degrees of latitude (62<sup>o</sup>S to 65<sup>o</sup>S and down to 68<sup>o</sup>S) is only feasible with tourist ships, or through remote sensing. The addition of a remote sensing component, validated by citizen scientists, is crucial for describing long-term synoptic trends and variability in the abundance and spatio-temporal extent of phytoplankton in this region, and for discerning how these patterns are likely to alter in response to changes in climate. This study provides a foundation to better understand phytoplankton diversity under current and potential future ocean conditions, and lead to more robust predictions on potential impacts to upper trophic levels and biogeochemical cycling within this rapidly changing ecosystem.</p>
Scienza aperta per umanisti (Open Science for Humanities)
<p>In this latest version, we have added a bibliography on the topic of Open Science and its relationship with the humanities:<br><a href="https://www.zotero.org/groups/5451011/scienzaapertaopenscience/library" target="_blank" rel="noopener">Bibliografia condivisa Scienza aperta e Humanities</a></p>
Sustainability Science Papers: Image accompanying social media post
<p>Image accompanying a social media post on the micro-blogging platform called Twitter at the time.</p> <p>Image description/ Alt text:</p> <p>An image of twelve abstracted scientific papers with with only titles readable. The Title of the whole image is "Sustainability Science Papers". The twelve titles are:<br>- A new framework to organize frameworks about human-nature relations<br>- Eating meat is bad<br>- It's capitalism's fault<br>- The economists did not let me publish my degrowth stuff<br>- Turns out businesses are not as green as they claim to be<br>- Here are many different scenarios for the future. Now go cry.<br>- We went to this island and did some workhshops with fishermen and the government. They just don't get it.<br>- This anthropocene concept is mindblowing<br>- Academia sucks, that's why we wrote a paper about it<br>- A social-ecological-art-dentistry reflection on interdisciplinary challenges<br>- You say activist, I say transdisciplinarity<br>- I have a PhD in sustainability science. I still do not know what it is.</p> <p>The social media post text accompanying the image at the time was:</p> <p>"I had to make one for #sustainability science, because a) the others made me laugh a lot and b) gave me a nice unfiltered insight into some fields 😂. #TypesOfScientificPapers #AcademicTwitter <br>(btw, thx @g_levrier) https://t.co/vkaPKsvVtq"</p>
Review dataset "Ethnobiology's contributions to sustainability science"
<p><span>This search was performed on April 2023 and allowed us to identify a total of 280 articles published between 2015 and 2022 (Supplementary Material 21). </span></p>
The role of health sciences libraries in supporting medical image consent standards survey documentation
<p><strong><em>Objective</em>:</strong> To determine if health sciences library workers were familiar with best practices regarding informed consent for the publication of medical images and if they incorporate the recommendations into their professional work.<br><br><strong><em>Methods</em>: </strong>A survey was developed by the authors and distributed to library listservs in the United States. The results of the survey were tabulated in R.<br><br><strong><em>Results</em>: </strong>A total of 90 respondents were included in the data analysis with all respondents reporting multiple responsibilities in their professional role. While the majority of library workers (59%) were familiar with the best practices, few incorporated the recommendations into their everyday professional work.<br><br><strong><em>Conclusions</em>:</strong> The professional work of health sciences library workers does not appear to include a significant inclusion of the best practices for the informed consent for the publication of medical images. There is a need for future research to better understand how library workers can better incorporate their knowledge of medical image publication consent standards into their work.</p>
Successful and timely uptake of artificial intelligence in science in the EU: references
<p>This reference list accompanies the SAPEA evidence review report on the same topic.</p>
Surface science and liquid phase investigations of oxanorbornadiene/oxaquadricyclane ester derivatives as molecular solar thermal energy storage systems on Pt(111) [doi: 10.1063/5.0158124]
<p>Primary data, meta data, and corresponding lists of figures & tables are included. [doi: 10.1063/5.0158124]</p>
Data on soil variables (with plot IDs) and grassland species traits used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. Journal of Vegetation Science, 35, e13259. Available from: https://doi.org/10.1111/jvs.13259
<p>File <a href="../api/records/10983049/draft/files/Plot_IDs_990ua.txt/content" target="_blank" rel="noopener noreferrer">Plot_IDs_990ua.txt</a> contains the IDs of the 1-m2 plots used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. The plot data are stored in the sPlot database (PPBio South Brazilian Grassland Database).</p> <p>File <a href="../api/records/10983049/draft/files/E_990ua_21SoilVar.txt/content" target="_blank" rel="noopener noreferrer">E_990ua_21SoilVar.txt</a> contains data on soil variables evaluated in the 250 m transects, but here expanded to the 990 1-m2 plots (each transect was sampled using 10 1-m2 pots).</p> <p>File <a href="../api/records/10983049/draft/files/B_769spp_4t.txt/content" target="_blank" rel="noopener noreferrer">B_769spp_4t.txt</a> is the species trait database collected in the framework of several research projects in the Quantitative Ecology Lab (EcoQua) and Grassland Vegetation Studies Lab (LevCamp) of Universidade Federal do Rio Grande do Sul (UFRGS). Data gaps were filled by compiled from the TRY database and data imputation.</p> <p> </p> <p> </p>
Dataset for the manuscript "Observation of time-reversal symmetry breaking in the band structure of altermagnetic RuO2" in Science Advances Vol. 10, No. 5
<p>Dataset for publication "Observation of time-reversal symmetry breaking in the band structure of altermagnetic RuO2" in Science Advances Vol. 10, No. 5, https://doi.org/10.1126/sciadv.adj4883.</p> <p>The details corresponding to the dataset of the figures are given in a readme file in the corresponding folders.</p>
Mnemosine Digital Library. Open Science Laboratory
<p>Mnemosine Digital Library functional architecture. </p>
Búsqueda en Web of Science sobre especies nuevas de hongos descritas en Chile en los últimos cinco años (2020–2024)
Open the record for dataset details and reuse information.
Canadian publications in Library and Information Science / Publications canadiennes en bibliothéconomie et sciences de l'information
<p><strong>Overview of Dataset </strong></p> <p>This dataset was developed through a collaboration between Dalhousie University and the University of Montréal. This project aims to help break down the silos in which the two primary target audiences- information science researchers and academic librarians- conduct their research. The Canadian Publications in Library and Information Science dataset makes visible the work that librarians do and allows other Canadian researchers to discover the research of their colleagues. <br><br></p> <p>The dataset contains 1,326 distinct authors, 850 of which were classified as practitioners and 476 as academics. It has a total of 13,775 records out of which 8,230 are authored by at least one academic and 5,740 are authored by at least one practitioner.</p> <p><br><strong>File descriptions</strong></p> <p> </p> <p>Table 1. Canadian LIS authors table (authors)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>author_id</p> </td> <td> <p>Unique identifier for the publication in the LIS database</p> </td> </tr> <tr> <td> <p>first_name</p> </td> <td> <p>First name of author</p> </td> </tr> <tr> <td> <p>last_name</p> </td> <td> <p>Last name of author</p> </td> </tr> <tr> <td> <p>full_name</p> </td> <td> <p>Full name of author</p> </td> </tr> <tr> <td> <p>status</p> </td> <td> <p>Academic (Ph.D. student, a postdoctoral fellow, or a professor (assistant, associate, full, emeritus) in an organizational unit offering an ALA accredited degree) or practitioner (librarian position in a Canadian university)</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 2. Works table (publications)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>pub_id</p> </td> <td> <p>Unique identifier for the publication in the LIS database</p> </td> </tr> <tr> <td> <p>doi</p> </td> <td> <p>Digital object identifiers</p> </td> </tr> <tr> <td> <p>openalex_work_id</p> </td> <td> <p>Identifier of the work in the OpenAlex database (URL format)</p> </td> </tr> <tr> <td> <p>isbn</p> </td> <td> <p>International standard book number (ISBN).</p> </td> </tr> <tr> <td> <p>doc_type</p> </td> <td> <p>Document type. Can take one of the following values: article; review; conference paper, book; edited book; book chapter.</p> </td> </tr> <tr> <td> <p>publication_year</p> </td> <td> <p>Year of publication</p> </td> </tr> <tr> <td> <p>title</p> </td> <td> <p>Title of the document</p> </td> </tr> <tr> <td> <p>source_name</p> </td> <td> <p>Title of the source (journal, conference, or book title for book chapters)</p> </td> </tr> <tr> <td> <p>author_list_full</p> </td> <td> <p>Full text listing of author names</p> </td> </tr> <tr> <td> <p>volume</p> </td> <td> <p>Volume number</p> </td> </tr> <tr> <td> <p>issue</p> </td> <td> <p>Issue number</p> </td> </tr> <tr> <td> <p>pages</p> </td> <td> <p>First and last pages separated by a hyphen.</p> </td> </tr> <tr> <td> <p>bk_edition</p> </td> <td> <p>Book edition</p> </td> </tr> <tr> <td> <p>bk_editor</p> </td> <td> <p>Name of book editor (for book chapters)</p> </td> </tr> <tr> <td> <p>publisher</p> </td> <td> <p>Publisher of the book/journal</p> </td> </tr> <tr> <td> <p>source_id</p> </td> <td> <p>Foreign key to the sources table</p> </td> </tr> <tr> <td> <p>url</p> </td> <td> <p>URL for the publication</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 3. Author publications table (authors_publications)</p> <table> <tbody> <tr> <td> <p><a name="_Hlk155194541"></a><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>author_id</p> </td> <td> <p>Unique identifier for the author in the authors table</p> </td> </tr> <tr> <td> <p>pub_id</p> </td> <td> <p>Unique identifier for the work in the publications table</p> </td> </tr> <tr> <td> <p>author_position</p> </td> <td> <p>Position on the byline.</p> </td> </tr> <tr> <td> <p>role</p> </td> <td> <p>Role of the author on the work (author/editor)</p> </td> </tr> </tbody> </table> <p>Table 4. Author IDs table (authors_ids)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>author_id</p> </td> <td> <p>Unique identifier for the author in the authors table</p> </td> </tr> <tr> <td> <p>source</p> </td> <td> <p>Source for the identifier (e.g., OpenAlex, Scopus, Google Scholar, ORCID)</p> </td> </tr> <tr> <td> <p>identifier</p> </td> <td> <p>Identifier for the author in the source database</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 5. Publication source table (sources)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>source_id</p> </td> <td> <p>Unique identifier for the source</p> </td> </tr> <tr> <td> <p>source_name</p> </td> <td> <p>Name of the source</p> </td> </tr> <tr> <td> <p>publisher</p> </td> <td> <p>Publisher name for the source</p> </td> </tr> <tr> <td> <p>issn</p> </td> <td> <p>ISSN for the source</p> </td> </tr> <tr> <td> <p>source_type</p> </td> <td> <p>OpenAlex source type (e.g., journal, conference)</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 6. Institutions table (institutions)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>institution_id</p> </td> <td> <p>Unique identifier for the institution</p> </td> </tr> <tr> <td> <p>institution_name</p> </td> <td> <p>Name of the Canadian academic institution</p> </td> </tr> <tr> <td> <p>city</p> </td> <td> <p>Name of the city in which the institution is primarily located</p> </td> </tr> <tr> <td> <p>province</p> </td> <td> <p>Two-letter code of the province in which the institution is located</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 7. Institution IDs table (institutions_ids)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>institution_id</p> </td> <td> <p>Unique identifier for the institution in the institutions table</p> </td> </tr> <tr> <td> <p>id_source</p> </td> <td> <p>Source database for the identifier (e.g., OpenAlex)</p> </td> </tr> <tr> <td> <p>identifier</p> </td> <td> <p>Identifier linked to the institution in the source database</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 8. Authorship institutional affiliation table (authors_publications_institutions)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>author_id</p> </td> <td> <p>Author component of the authorship information in the authors_publications table</p> </td> </tr> <tr> <td> <p>pub_id</p> </td> <td> <p>Publication component of the authorship information in the authors_publications table</p> </td> </tr> <tr> <td> <p>institution_id</p> </td> <td> <p>Unique identifier for the affiliated institution in the institutions table</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 9. Citations table (citations)</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>citing_pub_id</p> </td> <td> <p>Unique identifier for the citing work in the publications table</p> </td> </tr> <tr> <td> <p>cited_pub_id</p> </td> <td> <p>Unique identifier for the cited work in the publications table</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>To submit updates </strong></p> <p>For those interested in submitting updates to this dataset, you may send them by email to Philippe Mongeon (PMongeon@dal.ca). Please specify whether you want to modify, add, or delete existing data entries. Files in any format (e.g., XLS, BIB, Word, or a list of DOIs) are accepted.<br><br><strong>Data paper</strong><br><br>Find the corresponding data paper that describes the objectives of this dataset and the steps of its creation here: <a href="https://arxiv.org/abs/6053305">https://arxiv.org/abs/6053305</a>.</p> <p><br><br><strong>How to cite this dataset</strong></p> <p>Sauvé, J.-S., Hare, M., Krause, G., Poitras, C., Riddle, P., & Mongeon, P. (2024). Canadian publications in Library and Information Science / Publications canadiennes en bibliothéconomie et sciences de l'information [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.14302591" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.14302591</a> </p>
Marine litter abundance and composition on Chilean beaches, registered by the Científicos de la Basura citizen science program
<p>Data set generated by means of citizen science, which contains the abundances of the principal litter items registered on Chilean beaches every four years from 2008 to 2020, as well as in 2021. Specifically, the data set contains the numbers of macrolitter items (> 2.5 cm) counted within 3m x 3m sampling stations positioned within the surveyed beaches, grouped according to different material categories (such as papers, plastics, cigarette butts, among others). The data set also contains the sampling dates, the names and coordinates of the surveyed beaches, the zone and region where they are located, the nearest coastal city or town to each beach, the name of the school or the type of volunteers group that conducted each sampling, the total sum of anthropogenic litter items within each sampling station, and the mean abundance per square meter.</p>
Computer code accompanying Schraivogel, D. et al. "High-speed fluorescence image-enabled cell sorting" Science, 2022. doi: 10.1126/science.abj3013
<p>Computer code accompanying Schraivogel et al. "High-speed fluorescence image-enabled cell sorting". Details are provided in the manuscript's data and materials availability section and table 3.</p> <p> </p> <p>We provide three directories:</p> <p>(1) R code to reproduce figures (ICS2021_0.1.0.tar.gz)</p> <p>(2) Python code to reproduce figures (ICS_Fiji_Plugin.zip)</p> <p>(3) Code for ICS/CellView Fiji plugins (ICSPython.zip)</p> <p> </p> <p>Code for (1) and (3) has also been shared via Github:</p> <p>https://github.com/benediktrauscher/ICS</p> <p>https://github.com/embl-cba/ICS</p> <p> </p> <p>We recommend downloading the ICS Fiji plugins via Github or to install them using the Fiji update site to ensure you're using the most recent version.</p>
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.