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13,499 results for “researcher”
Questionnaire for the self-assessment of digital preservation activities in institutional research repositories
<p>This dataset includes a questionnaire designed to enable institutional repository managers to conduct a self-assessment of their digital preservation strategies and activities. It consists of 46 evaluation criteria extracted and modified from the NDSA Levels of Digital Preservation and ISO 16363:2017 standards. The questionnaire is provided in queXML format, facilitating its import into various survey applications</p> <p> </p>
Dataset for "Gender and Gender Research in a Research Community: CSTT as a Case Study"
<p>This is the dataset used for and generated during our research for the following publication:<br>Francis Borchardt, Hanna Tervanotko and Saana Svärd "Gender and Gender Research in a Research Community: CSTT as a Case Study." In: Changes in Sacred Texts and Traditions: Methodological Encounters and Debates, eds. Martti Nissinen and Jutta M. Jokiranta. Resources for Biblical Study 106. SBL Press; Atlanta, USA. Pp. 517-544. 2024.<br><br></p>
Research data supporting "Observation of a Topological Edge State Stabilized by Dissipation"
<div> <p>This repository contains the data presented in the manuscript titled "Observation of a Topological Edge State Stabilized by Dissipation" by H. Wetter et al., Phys. Rev. Lett. 131, 083801 (2023). The files contain the final data sets relevant to reproduce all plots shown in the paper. Data types are CSV, TIF, SVG, TXT, PNG. No licensed software is required for opening and reading the files.</p> </div>
OpenAIRE Dataset for SciLake cancer research pilot
<p>This dataset is related to the subset of the OpenAIRE graph relevant to the cancer research pilot. The dataset is built according to the <a href="https://graph.openaire.eu/docs/data-model/">data model</a> of the OpenAIRE Graph dataset. </p>
Research data: Continuity Amid Transformation: An Analysis of Pottery Production from the Late La Tène to Early Roman Periods in Eastern Bohemia
<p>Data used in the research presented in the article titled "Continuity Amid Transformation: An Analysis of Pottery Production from the Late La Tène to Early Roman Periods in Eastern Bohemia".</p> <p><strong>Abstract of the article:</strong></p> <p>At the end of the La Tène period and the beginning of the Roman period in the first century BC, society in Central Europe underwent a significant transformation, which included notable changes in pottery production. This transformation is often attributed to the collapse of the social structures of the La Tène period and the arrival of a new population. Pottery production, in particular, is generally considered to have undergone a complete transformation.</p> <p>However, previous studies on this transition have primarily focused on the stylistic analysis of shapes and decorations, as illustrated by the pottery assemblage from Slepotice (Eastern Bohemia). In order to obtain additional data on the transitional period, this study of pottery from Slepotice incorporates analyses of the materials used and the manufacturing process through macroscopic observation, X-ray fluorescence analysis, and thin-section analysis. These analyses provide new insights into the differences in pottery production and distribution during the first century BC.</p> <p>Our research indicates that while the transformation included the collapse of the La Tène socioeconomic network, it did not result in a complete break in the pottery production process.</p> <p>Link to the article: <a href="https://doi.org/10.1016/j.jasrep.2025.105073">https://doi.org/10.1016/j.jasrep.2025.105073</a></p> <p> </p> <p><strong>List of the files:</strong></p> <p>Supplementary Material 1<br>Settlement structure in the vicinity of Slepotice during the La Tène and Roman periods: 1 – Slepotice, 2 – České Lhotice, 3 – Brčekoly, 4 – Chrudim</p> <p>Supplementary Material 2<br>Values of pottery attributes (Mat, InMn, InVar, In, traces left from the shaping process, Po, Vy, and morphological groups) classified based on macroscopic observation</p> <p>Supplementary material 3<br>Schematic classification of rim attributes, illustrating different variants of rim direction (Op), thickening of the upper part of the rim (Oz), and trimming of the lip (Os)</p> <p>Supplementary material 4<br>Attributes of the 30 samples selected for XRF analysis based on macroscopic observation. These attributes include fabric properties, surface treatment, morphological features, and technological traces</p> <p>Supplementary material 5<br>Figures of ceramic samples (with corresponding IDs) from feature 144/1998 showing preserved rims and bases</p> <p>Supplementary material 6<br>Figures of ceramic samples (with corresponding IDs) from feature 355/2001 showing preserved rims</p> <p>Supplementary Material 7<br>Chemical composition of 30 selected samples according to XRF analysis (main oxides in wt%, and elements in ppm)</p> <p>Supplementary Material 8<br>Principal Component Analysis (PCA) results: The scree plot (top left) visualises the proportion of variance explained by each principal component. The biplots (top right and bottom right) illustrate the distribution of samples, with arrows indicating the contribution of specific elements to the observed variance. The dendrogram (bottom left) shows hierarchical clustering of the samples, aiding in the selection of representative samples for thin-section petrographic analysis</p> <p>Supplementary Material 9<br>Relationships between the dating and other attributes of pottery classified based on macroscopic observation. These attributes include fabric properties, surface treatment, morphological features, and technological traces</p> <p>Supplementary Material 10<br>Relationships between the chemical groups (determined by XRF analysis) and pottery attributes classified based on macroscopic observation. These attributes include fabric properties, surface treatment, morphological features, and technological traces</p> <p>Supplementary Material 11<br>Petrography of fabric groups and subgroups, focusing on their properties. The evaluation begins with a general assessment of each fabric group as a whole, followed by a detailed examination of its subgroups</p> <p>Supplementary Material 12<br>Petrographic characterization of ceramics using a semiquantitative scale, simplified for statistical analysis (0.1 – trace, 0.5 – rare, 1 – occasional, 2 – common, 3 – frequent, 4 – abundant, 5 – dominant)</p> <p>Supplementary Material 13<br>Thin-section samples: Description of the ceramic matrix, natural inclusions, and added tempers</p> <p>Supplementary material 14<br>Variations in chemical composition among different fabric groups</p>
Research compendium for 'Refitting the Context: A Reconsideration of Cultural Change among Early Homo sapiens at Fumane Cave through Blade Break Connections, Spatial Taphonomy, and Lithic Technology'
<div> <h3>Compendium DOI:</h3> <p><a href="../doi/10.5281/zenodo.10965413">https://zenodo.org/doi/10.5281/zenodo.10965413</a> </p> </div> <p>The content available at the above provided URL will reproduce the results as documented in the publication. Instead, the files hosted at <a href="https://github.com/ArmandoFalcucci/Refitting-The-Context">https://github.com/ArmandoFalcucci/Refitting-The-Context</a> represent the developmental versions and might have undergone modifications since the paper's publication.</p> <div> <h3>Maintainer of this repository:</h3> </div> <p>Armando Falcucci (<a href="mailto:armando.falcucci@uni-tuebingen.de">armando.falcucci@uni-tuebingen.de</a>)</p> <div> <h3>Published paper:</h3> </div> <p>Armando Falcucci, Domenico Giusti, Filippo Zangrossi, Matteo De Lorenzi, Letizia Ceregatti, Marco Peresani. Refitting the Context: Revisiting the Aurignacian sequence at Fumane Cave through blade fragment connections, spatial taphonomy, and lithic technology. <em>Journal of Paleolithic Archaeology</em> (2024). DOI: <a href="https://doi.org/10.1007/s41982-024-00203-0" rel="nofollow">10.1007/s41982-024-00203-0</a></p> <div> <h3>Abstract:</h3> </div> <p>High-resolution stratigraphic frameworks are crucial for unraveling the biocultural processes behind the dispersals of Homo sapiens across Europe. Detailed technological studies of lithic assemblages retrieved from multi-stratified sequences allow archaeologists to precisely model the chrono-cultural dynamics of the early Upper Paleolithic. However, it is of paramount importance to verify the integrity of these assemblages before building explanatory models of cultural change. In this study, multiple lines of evidence suggest that the stratigraphic sequence of Fumane Cave in northeastern Italy experienced minor post-depositional reworking, establishing it as a pivotal site for exploring the earliest stages of the Aurignacian. By conducting a systematic search for break connections between blade fragments and applying spatial analysis techniques, we identified three well-preserved areas of the excavation containing assemblages suitable for renewed archaeological investigations. Subsequent technological analyses, incorporating attribute analysis, reduction intensity, and multivariate statistics, have allowed us to discern the spatial organization of the site during the formation of the Protoaurignacian palimpsest A2–A1. Moreover, diachronic comparisons between three successive stratigraphic units prompted us to reject the hypothesis of techno-cultural continuity of the Protoaurignacian in northeastern Italy after the onset of the Heinrich Event 4. Based on the variability of the lithic and osseous artifacts, the most recent assemblage analyzed, D3b alpha, is now ascribed to the Early Aurignacian, aligning the evidence from Fumane with the current understanding of the development of the Aurignacian across Europe. Overall, this study demonstrates the high effectiveness of the break connection method when combined with detailed spatial analysis and lithic technology, providing a methodological tool particularly amenable to be applied to sites excavated in the past with varying degrees of recording accuracy.</p> <div> <h3>Keywords:</h3> </div> <p>Protoaurignacian; Early Aurignacian; Lithics; Refittings; Assemblage integrity; Spatial analysis; Italy</p> <div> <h3>Overview of contents and how to reproduce:</h3> </div> <p>Within this repository, various folders house data (<code>data</code>), code (<code>script</code>), and output files (<code>output</code>) pertinent to the paper. The data folder encompasses the blank and core datasets from the Aurignacian of Fumane Cave and the dataset of the blade fragment connection study. To replicate the results, download the entire repository and employ <code>Refitting-The-Context.Rproj</code> and open the folder <code>script</code>. For ensuring reproducibility, the <code>renv</code> package (v. 1.0.3) was utilized, following the procedures detailed in its vignette. All analyses and visualizations in the paper were conducted using R 4.3.1 on Microsoft Windows 10.0.19045 (64-bit). As the necessary packages are available in the <code>renv</code> folder, they are not explicitly listed here.</p> <div> <h3>Licenses:</h3> </div> <p>Code: <strong>MIT</strong> <a href="http://opensource.org/licenses/MIT" rel="nofollow">http://opensource.org/licenses/MIT</a>, copyright holder: Armando Falcucci (2024).</p> <p>Data and intellectual work: <strong>Creative Commons Attribution 4.0 International License</strong> (<a href="http://creativecommons.org/licenses/by/4.0/" rel="nofollow">http://creativecommons.org/licenses/by/4.0/</a>), copyright holder: the authors (2024).</p>
Reproduction package for paper "How far are we from reproducible research on code smell detection? A systematic literature review"
<p>Checklist and data extracted from publications analyzed for "How far are we from reproducible research on code smell detection? A systematic literature review" paper, together with processing scripts and calculations of Cohen's Kappa.</p> <p>Paper that describes details of the data is available here: https://doi.org/10.1016/j.infsof.2021.106783</p>
Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
<p>This is the first release of Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016. The profile will be used by TERN data editorial system (SHaRED v4).</p>
The open D1NAMO dataset: A multi-modal dataset for research on non-invasive type 1 diabetes management
<p>The description of the dataset is available at <a href="https://doi.org/10.1016/j.imu.2018.09.003">https://doi.org/10.1016/j.imu.2018.09.003</a></p> <p>The usage of wearable devices has gained popularity in the latest years, especially for health-care and well being. Recently there has been an increasing interest in using these devices to improve the management of chronic diseases such as diabetes. The quality of data acquired through <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/wearable-sensor">wearable sensors</a> is generally lower than what medical-grade devices provide, and existing datasets have mainly been acquired in highly controlled clinical conditions. In the context of the <em>D1NAMO</em> project — aiming to detect <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/glycemic">glycemic</a> events through non-invasive <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/ecg-abnormality">ECG pattern</a> analysis — we elaborated a dataset that can be used to help developing health-care systems based on wearable devices in non-clinical conditions. This paper describes this dataset, which was acquired on 20 healthy subjects and 9 patients with type-1 diabetes. The acquisition has been made in real-life conditions with the <em>Zephyr BioHarness 3</em> wearable device. The dataset consists of <em>ECG</em>, <em>breathing</em>, and <em><a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/accelerometer">accelerometer</a></em> signals, as well as <em>glucose</em> measurements and annotated <em>food pictures</em>. We open this dataset to the scientific community in order to allow the development and evaluation of diabetes management algorithms.</p>
Music Data Sharing Platform for Computational Musicology Research (CCMUSIC DATASET)
<p>This platform is a multi-functional music data sharing platform for Computational Musicology research. It contains many music datas such as the sound information of Chinese traditional musical instruments and the labeling information of Chinese pop music, which is available for free use by computational musicology researchers.</p> <p>This platform is also a large-scale music data sharing platform specially used for Computational Musicology research in China, including 3 music databases: Chinese Traditional Instrument Sound Database (CTIS), Midi-wav Bi-directional Database of Pop Music and Multi-functional Music Database for MIR Research (CCMusic). All 3 databases are available for free use by computational musicology researchers. For the contents contained in the database, we will provide audio files recorded by the professional team of the conservatory of music, as well as corresponding labelled files, which have no commodity copyright problem and facilitate large-scale promotion. We hope that this music data sharing platform can meet the one-stop data needs of users and contribute to the research in the field of Computational Musicology.</p> <p> </p> <p>If you want to know more information or obtain complete files, please go to the official website of this platform:</p> <p><a href="https://ccmusic-database.github.io/en/">Music Data Sharing Platform for Academic Research</a></p> <p> </p> <ul> <li> <p><strong>Chinese Traditional Instrument Sound Database (CTIS)</strong></p> </li> </ul> <p>This database is developed by Prof. Han Baoqiang's team for many years, which collects sound information about Chinese traditional musical instruments. The database includes 287 Chinese national musical instruments, including traditional musical instruments, improved musical instruments and ethnic minority musical instruments.</p> <ul> <li> <p><strong>Multi-functional Music Database for MIR Research</strong></p> </li> </ul> <p>This database collects sound materials of pop music, folk music and hundreds of national musical instruments, and makes comprehensive annotation to form a multi-purpose music database for MIR researchers.</p> <ul> <li><strong>Midi-wav Bi-directional Database of Pop Music</strong></li> </ul> <p>This database contains hundreds of Chinese pop songs, and each song contains the corresponding midi-audio-lyric information. Among them, recording the vocal part and accompaniment part of audio independently is helpful to study the MIR task under the ideal situation. In addition, the information of singing techniques consistent with vocal part (such as breath sound, falsetto, breathing, vibrato, mute, slide, etc.) is marked in MuseScore, which constitutes a Midi-Wav bi-direction corresponding pop music database.</p>
WikiMed and PubMedDS: Two large-scale datasets for medical concept extraction and normalization research
<p>Two large-scale, automatically-created datasets of medical concept mentions, linked to the <a href="https://uts.nlm.nih.gov/uts/umls/home">Unified Medical Language System (UMLS)</a>.</p> <p><strong>WikiMed</strong></p> <p>Derived from Wikipedia data. Mappings of Wikipedia page identifiers to UMLS Concept Unique Identifiers (CUIs) was extracted by crosswalking Wikipedia, Wikidata, Freebase, and the NCBI Taxonomy to reach existing mappings to UMLS CUIs. This created a 1:1 mapping of approximately 60,500 Wikipedia pages to UMLS CUIs. Links to these pages were then extracted as mentions of the corresponding UMLS CUIs.</p> <p>WikiMed contains:</p> <ul> <li>393,618 Wikipedia page texts</li> <li>1,067,083 mentions of medical concepts</li> <li>57,739 unique UMLS CUIs</li> </ul> <p>Manual evaluation of 100 random samples of WikiMed found 91% accuracy in the automatic annotations at the level of UMLS CUIs, and 95% accuracy in terms of semantic type.</p> <p><strong>PubMedDS</strong></p> <p>Derived from biomedical literature abstracts from <a href="https://pubmed.ncbi.nlm.nih.gov/">PubMed</a>. Mentions were automatically identified using distant supervision based on Medical Subject Heading (MeSH) headers assigned to the papers in PubMed, and recognition of medical concept mentions using the high-performance <a href="https://allenai.github.io/scispacy/">scispaCy</a> model. MeSH header codes are included as well as their mappings to UMLS CUIs.</p> <p>PubMedDS contains:</p> <ul> <li>13,197,430 abstract texts</li> <li>57,943,354 medical concept mentions</li> <li>44,881 unique UMLS CUIs</li> </ul> <p>Comparison with existing manually-annotated datasets (NCBI Disease Corpus, BioCDR, and MedMentions) found 75-90% precision in automatic annotations. Please note this dataset is <em>not </em>a comprehensive annotation of medical concept mentions in these abstracts (only mentions located through distant supervision from MeSH headers were included), but is intended as data for <em>concept n</em><em>ormalization</em> research.</p> <p>Due to its size, PubMedDS is distributed as 30 individual files of approximately 1.5 million mentions each.</p> <p><strong>Data format</strong></p> <p>Both datasets use JSON format with one document per line. Each document has the following structure:</p> <pre><code class="language-json">{ "_id": "A unique identifier of each document", "text": "Contains text over which mentions are ", "title": "Title of Wikipedia/PubMed Article", "split": "[Not in PubMedDS] Dataset split: <train/test/valid>", "mentions": [ { "mention": "Surface form of the mention", "start_offset": "Character offset indicating start of the mention", "end_offset": "Character offset indicating end of the mention", "link_id": "UMLS CUI. In case of multiple CUIs, they are concatenated using '|', i.e., CUI1|CUI2|..." }, {} ] }</code></pre> <p><strong>Version history</strong></p> <table align="left"> <thead> <tr> <th scope="col">Version</th> <th scope="col">Notes</th> </tr> </thead> <tbody> <tr> <td>1.0.0</td> <td>Initial release</td> </tr> <tr> <td>1.0.1</td> <td>Corrected duplication error in WikiMed.zip file</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p>
HiMAT Thesaurus for Mining Research
<p>This datasets contains the Thesaurus for HiMAT-datasets including informations related to skos-concepts and the triples of the Thesaurus' RDF representation.</p>
Medieval manuscripts and their migrations: Using SPARQL to investigate the research potential of an aggregated Knowledge Graph
<p>This dataset contains the <strong>SPARQL queries</strong> presented and discussed in our article published in <em>Digital Medievalist</em> 2022 (as a PDF file), together with the <strong>results of those queries</strong> as CSV files. The query and step numbering follows that given in the article.</p> <p>The queries can be run against the SPARQL endpoint for the <strong>Mapping Manuscript Migrations</strong> project: <a href="https://ldf.fi/mmm/sparql">https://ldf.fi/mmm/sparql</a></p> <p>The full <strong>Mapping Manuscript Migrations dataset </strong>can also be downloaded from the Zenodo repository and installed in your own triple store: <a href="https://zenodo.org/record/4440464">https://zenodo.org/record/4440464</a></p> <p>When copying and pasting these SPARQL queries into a SPARQL client like <a href="https://yasgui.triply.cc/">YASGUI</a>, please check that the line numbering has been copied over correctly. Copying from a PDF file can sometimes break a single long line into multiple separate lines, which will cause a SPARQL validation error.</p> <p>The CSV files contain the results of the queries when run against the Mapping Manuscript Migrations SPARQL endpoint as of 17 December 2021. Please note that Query 2, Step 2, produces no results, so a CSV file has not been provided.</p> <p>The<strong> Mapping Manuscript Migrations portal </strong>can be found at <a href="https://mappingmanuscriptmigrations.org/en/">https://mappingmanuscriptmigrations.org/en/ </a></p> <p>SPARQL tutorials are included in the project's <strong>GitHub documentation</strong>: <a href="https://mapping-manuscript-migrations.github.io/">https://mapping-manuscript-migrations.github.io/</a></p>
Mapping Building BioData.pt Indicators against the performance and impact assessment frameworks for research infrastructures of OECD, ESFRI and RI-PATHS project
<p>"Buiding BioData.pt" indicators observed in international frameworks for performance and impact assessment of research infrastructures, namely, OECD, ESFRI and RI-PATHS.</p>
How does moving Public Engagement with Research Online Change Audience Diversity? Comparing Inclusion Indicators for 2019 & 2020 European Researchers' Night events
<p>Taking place annually in more than 400 cities, European Researchers’ Night is a pan- European synchronized event that aims to bring researchers closer to the public. In this paper audience profiles are compared from events in 2019 and 2020. In 2019, face-to-face events reached an estimated 1.6 million attendees, while in 2020, events shifted online due to the COVID-19 pandemic and reached an estimated 2.3 million attendees. Focusing on social inclusion metrics, survey data is analyzed across two national contexts (Ireland and Malta) in 2019 (n=656) and 2020 (n=506). The results from this exploratory, descriptive study shed light on how moving public engagement with research online shifted audience profiles. Based on prior research about the digital divide in access and use of online media, hypotheses were proposed that online European Researchers’ Night events would attract audiences with higher educational attainment levels and greater self-reported, subjective economic well-being. While changes were observed from 2019 to 2020, results for each hypothesis show a mixed picture. The first hypothesis was upheld for the highest education levels but failed for the lowest levels suggesting that the pivot to online events simultaneously attracted participants with no formal education and those with postgraduate qualifications, while attracting less of those with undergraduate or lower levels of education. The second hypothesis was not upheld, with online European Researchers’ Night events attracting audiences with slightly higher levels of economic well-being compared to face-to-face events. The findings of this study indicate that European Researchers’ Night events present a clear opportunity to measure the effects of the digital divide in relation to public engagement with research across Europe.</p>
Supplementary Figures. "In silico research of new therapeutics rotenoids derivatives against Leishmania amazonensis infection"
<p>Supplementary figures corresponding to the submitted manuscript entitled "In silico research of new therapeutics rotenoids derivatives against Leishmania amazonensis infection"</p>
2019 search and interaction log from the data catalogue: Research Data Australia
<p>In order to provide a better support to user's data discovery activity, we analysed a data search log in order to understand how data seekers interact with a data search system when they search for data. The data search log is from the research data discovery portal: <a href="https://researchdata.edu.au">Research Data Australia (RDA)</a>. RDA is the data discovery service of the Australian Research Data Commons (ARDC). ARDC is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program.</p> <p>Please read the research paper "<a href="https://doi.org/10.1108/JD-12-2021-0245">Large-scale Analysis of Query Logs to Profile Users for Dataset Search</a>" for detailed description and analysis of the datasets, and the software "<a href="https://zenodo.org/record/6321621#.Yh79Tt9xUmA">Python code for processing and clustering a data search log</a>" for the data process and analysis.</p> <p>The search log consists of the entire user-front activity log data for the duration of January to December 2019. During this period, the catalogue contained about 150,000 metadata records of datasets.</p> <p>The dataset (2019_search_log_sessioned.txt) was generated from raw log data with following steps:</p> <ul> <li>Remove entries that were likely from machines instead of human users. Those recorded machine activities may result from downstream aggregators who harvested metadata from RDA by directly sending queries to the catalogue URL instead of using the API endpoint.</li> <li>Identify search sessions from a user - a search session includes all activities a user conducts with a search system in order to satisfy a (information/data) search needs. We followed the following steps to identify search sessions. First, we identified a user by IP address, where a unique IP address was considered a single user. We recognise the limitation of this approach, as several users may share the same IP address, however the IP address is the only information available for identifying a user. <br> Past research in log analysis usually apply the following two methods to identify a session: 30 minutes from the same IP address, and/or more than 30 minutes of inactivity between the current activity event and its immediate preceding event. We examined both methods carefully for our log data and concluded that both ended with large unwanted sessions from machine activities. Therefore, we take a brutal approach, by taking only a session from an IP address with a maximum 30 minutes duration.</li> <li>We also removed sessions whose 40% of activities resulted in ’page not found’ or whose activities were all about accessing grants. Within a session, we removed "duplicated" activities that were exactly as their precedent activity with less than one second time span (this could have been a result of reloading a page).</li> </ul> <p>The dataset (id_to_title_subject.csv) lists title and subject headings per record id.</p> <p> </p>
Research Infrastructure Contact Zones
<p>The landscape of biodiversity data infrastructures and organisations is complex and fragmented. Many occupy specialised niches representing narrow segments of the multidimensional biodiversity informatics space, while others operate across a broad front but differ from others by data type(s) handled, their geographic scope and the life cycle phase(s) of the data they support. To characterise the various dimensions of the biodiversity informatics landscape, we developed a framework to survey these dimensions for ten organisations (<a href="https://www.dissco.eu/">DiSSCo</a>, <a href="https://www.gbif.org/">GBIF</a>, <a href="https://ibol.org/">iBOL</a>, <a href="https://www.catalogueoflife.org/">Catalogue of Life</a>, <a href="https://www.inaturalist.org/">iNaturalist</a>, <a href="https://www.biodiversitylibrary.org/">Biodiversity Heritage Library</a>, <a href="https://geocase.eu/">GeoCASe</a>, <a href="https://www.lifewatch.eu/">LifeWatch</a>, <a href="https://www.lter-europe.net/elter-esfri">eLTER</a>, <a href="https://elixir-europe.org/">ELIXIR</a>), relative to both their current activities and long-term strategic ambitions.</p> <p>The results of the survey are presented in this dataset. Details of the assessment methodology, data model, scope and high-level results are described in an accompanying paper, which is currently under review and will be linked to this dataset on publication.</p>
Participatory Research Lifecycle
<p>This is a wheel that represents the participatory research lifecycle designed in the ACTION project (H2020)</p>
MastaBase: a research tool for the study of 'daily life' scenes in Old Kingdom elite tombs
<p><em>Mastabase: a research tool for the study of the secular or 'daily life' scenes and their accompanying texts in the elite tombs of the Memphite area in the Old Kingdom</em></p> <p>The Leiden Mastaba Project was initiated in 1998 to develop a coherent database of iconographic programmes in Old Kingdom elite tombs from the Memphite area (c. 2600-2150 BCE). It was published as a CD-ROM in 2008 by Peeters Publishers in Leuven.</p> <p>The project was directed by dr. René van Walsem at Leiden University, and partly funded by NWO and LUF/Gratama. Hans van den Berg and drs. Marije Vugts played a vital role in its development.</p> <p>The ISO was uploaded by Nicky van de Beek.</p> <p>Project page: https://digitalegyptology.org/mastabase/</p> <p>---</p> <p>The Leiden Mastaba Project (LMP) concerns an integral and analytic study of the secular or 'daily life' scenes and their accompanying texts in the elite tombs of the Memphite area in the Old Kingdom (c. 2600-2150 B.C.). The project has the aim to get insight in the developments of number, size, internal organization and shape of the various (sub)themes, their location in the tomb, their wall position (upper/middle/lower level), and their orientation (north/east/south/west) on the walls. This reflects the dynamics of Old Kingdom funerary culture in general aspects (collective) and in specific cases (individual). Simultaneously it reveals possible local variations, mainly among the large necropoleis of Saqqara and Giza.</p> <p>The data are digitized in a database called MastaBase, published on this cd-rom. Thanks to the standardisation of the material offered in the MastaBase, with this cd-rom it is now possible to gain quick oversights into various different aspects of these tombs and their decoration via extensive selection procedures.</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.