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6,025 results for “science”
Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research (Supplementary Material: Full Paper Listing and Analysis)
<p>Supplementary material of the paper:</p> <p>Title: "Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research"<br>Subtitle: "A Survey of the IPIN's Reference Papers of 2022 and 2023 Editions"</p> <p>The paper is accepted to the "14th International Conference on Indoor Positioning and Indoor Navigation, IPIN 2024, Hong Kong, October 14-17, 2024, IEEE, 2024.</p> <p>An Author's accepted version of the manuscript is available here: <a href="../records/13684170" target="_blank" rel="noopener">https://zenodo.org/records/13684170</a> </p> <p>If you want to refer to this work, please cite this Zenodo entry as well as the published conference version.</p> <p> </p> <p>---------------------------------------</p> <p>This entry contains two files:</p> <ul> <li>"Paper Characterization Spreadsheet.xlsx": <strong>The spreadsheet of the full analysis of this work</strong>, as described in the paper. It characterizes various features of the analyzed papers and forms the raw data on which the analyses of our work were based.</li> <li>"Main features of the manuscripts analysed in Zenodo Record #12088175.pdf": A document summarizing the main features of the IPIN's Reference Papers of the 2022 and 2023 Editions, that contain some form of open resources (Open Data, Code, or Material).</li> </ul> <p> </p> <p> </p> <p> </p>
Why Science is Important
<p>This is a 3-minute video to promote science engagement and the Multispecies Ovary Tissue Histology Electronic Repository (MOTHER) project.</p> <p>Disclaimer: The MOTHER project was funded by the U.S. National Science Foundation (DBI-2054061). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.</p>
Experimental data for nonlinear dynamics and energy harvesting of bistable cantilever shells (grant 2021/41/B/ST8/03190 from the National Science Centre, Poland)
<p>An experimental tests on a cantilever composite bistable shell with a piezoelectric patch is reported. The shell is characterized by two stable configurations. Periodic force is applied at the shell’s clamped side through an electrodynamic shaker and the dynamic response is measured through an embedded strain gauge. Selected dynamic regimes are recorded by performing excitation frequency and amplitude sweeps. The resonance scenarios around the two natural frequencies corresponding to the stable configurations show different softening behavior. The excitation amplitude threshold level for snap-through motion is identified. The thested thin-walled pseudo-conical shell has been made of carbon-epoxy composite prepreg tape (AS4-GP-12K_40gsm-<br>300mm-ThinPreg135EP). The composite single layer is characterized by unidirectional reinforcement, thickness 0.04 mm. The manufacturing standard samples for strength tests in the autoclave process reduces to about 0.038 mm. </p>
Survey on the social impact of the citizen science in the projects LIFE MIPP and InNat
<p>The present dataset consists in a sociological survey addressed to the volunteers involved in MIPP and InNat projects, a citizen science initiative aimed at the collection of distribution data of protected species and habitats all over Italian national territory. In particular, two different files are provided: </p> <ol> <li>the original survey (questions and answers) addressed to the volunteers in Italian</li> <li>the English translation of the questionnaire </li> </ol> <p>The survey covers different topics: socio-demographic data (section 1), opinions on the role of volunteering in a citizen science project (section 2), possible previous citizen science experience (section 3), test on the acquired skills on the monitored insect species with MIPP/InNat (section 4), opinions concerning the ecological crisis and the trust in the ability of humankind to solve environmental issues (section 5), possibility to be further contacted for additional interviews (section 6).</p> <p>A total of 364 completed questionnaires have been collected and relative results are provided here. Moreover, the above-mentioned results are thoroughly investigated and analysed in a scientific paper which also explores drivers that might keep volunteers active in a biodiversity monitoring project. Indeed, the engagement of volunteers in citizen science projects is a remarkable issue to address in order to ensure long-term sustainability, scientific relevance and public participation.</p> <p>The MIPP/InNat initiative started in 2012, with the project MIPP “Monitoring of insects with public participation” (LIFE11 NAT/IT/000252) which ended in 2017, and was then continued by the InNat project thanks to Italian National fundings. Data gathered in both projects converged in the same database. This research was supported by the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union – 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP B83D21014060006, Project title “National Biodiversity Future Center” – NBFC.</p>
Data accessibility in the chemical sciences: an analysis of recent practice in organic chemistry journals
<div> <p>Data is the analysis of the data outputs of 240 randomly selected research papers from 12 top-ranked journals published in early 2023. We investigate author compliance with recommended (but not compulsory) data policies, whether there is evidence to suggest that authors apply FAIR data guidance in their data publishing, and if the existence of specific recommendations for publishing NMR data by some journals encourages compliance. Files in the data package have been provided in both human and machine-readable forms. The main dataset is available in the Excel file Data worksheet.XLSX, the contents of which can also be found in Main_dataset.CSV, Data_types.CSV, and Article_selection.CSV with explanations of the variable coding used in the studies in Variable_names.CSV, Codes.CSV, and FAIR_variable_coding.CSV. The R code used for the article selection can be found in Article_selection.R. Data about article types from the journals that contain original research data is in Article_types.CSV. Data collected for analysis in our sister paper[4] can be found in Extended_Adherence.CSV, Extended_Crystallography.CSV, Extended_DAS.CSV, Extended_File_Types.CSV, and Extended_Submission_Process.CSV. A full list of files in the data package and a short description for each is given in README.TXT.</p> </div>
PhasAGE Training School 1 -Overview of bioinformatics tools for the life sciences & Classification and evolution of non-globular proteins- LECTUREs
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
Visualization and perception of data gaps in the context of Citizen Science projects: Gradation of Reporting Activity
<p>Online experiment about the influence of different numbers of levels of representation of reporting activity (total number of reports for all birds in the given time span and region) on proportion of correct responses and subjective evaluation of the task (NASA-TLX). Effects of representation with three (3) levels and effects of representation with five (5) levels are investigated. Two groups of members of ornitho.de were tested: experts - persons with access to database (more than 10 reports per month in average) and novices - persons without access to database (less than 10 reports per month in average). Two different tasks were given. The evaluation of statements on a map and the selection of grid fields that met a given requirement.</p>
Visualization and perception of data gaps in the context of Citizen Science projects: Video tutorial support
<p>Online experiment about the influence of the availability of a video tutorial on proportion of correct responses and subjective evaluation of the task (NASA-TLX). Two different tasks were given. The evaluation of statements on a map and the selection of grid fields that met a given requirement.</p>
Open Science Team 7 Data Set and Bibliography
<p>As a small exercise before delving into a group research project we generated a small data set based on the review of 7 websites ranging in subject matter. We provide the Data set and bibliography here. </p>
Normalisation of Early Modern Science: Inventory of 17th- and 18th-Century Sources
<p>This dataset contains a corpus of early modern natural philosophy works that underlie the European Research Commission-funded Starting Grant “The Normalisation of Natural Philosophy: How Teaching Practices Shaped the Evolution of Early Modern Science,” (grant agreement No. 801653 NaturalPhilosophy), led by Dr. Andrea Sangiacomo at the Faculty of Philosophy at the University of Groningen.</p> <p> </p> <p>The methodology behind the retrieval, cleaning, and annotation of this repository is described in the paper:</p> <p> </p> <ul> <li>Sangiacomo, Andrea; Tanasescu, Raluca; Donker, Silvia; Hogenbirk, Hugo. 2021. “Mapping the Evolution of Early Modern Natural Philosophy: Corpus Collection and Authority Acknowledgement,” published in the <em>Annals of Science</em> (DOI: 10.1080/00033790.2021.1992502; permanent link: <a href="https://doi.org/10.1080/00033790.2021.1992502">https://doi.org/10.1080/00033790.2021.1992502</a> [forthcoming on the date of the upload]</li> </ul> <p> </p> <p>The difference between the total number of entries in this data set and the number of titles we ran our analyses on comes from listing multiple volumes of the same work as one single entry. The work on this corpus continues and further versions will be gradually uploaded, with supplementary information about publishers and publication places.</p> <p> </p> <p>The dictionaries from which we selected the data in worksheets 2-5 are the following:</p> <p> </p> <ul> <li>Wiep van Bunge, Henri Krop, Bart Leeuwenburgh, Paul Schuurman, Han van Ruler and Michiel Wielema, <em>Dictionary of Seventeenth- and Eighteenth-Century Dutch Philosophers</em> (London: Bloomsbury, 2003);</li> <li>John Yolton, Valdimir Price and John Stephens. <em>Dictionary of Eighteenth-Century British Philosophers</em> (London: Bloomsbury, 1999);</li> <li>Andrew Pyle. <em>Dictionary of Seventeenth-Century British Philosophers</em> (London: Bloomsbury, 2000);</li> <li>Luc Foisneau. <em>Dictionary of Seventeenth-Century French Philosophers</em> (London: Bloomsbury, 2008);</li> <li>Heiner F. Klemme and Manfred Kuehn. <em>Dictionary of Eighteenth-Century Philosophers</em> (London: Bloomsbury, 2011).</li> </ul> <p> </p> <p>University of Groningen Team:</p> <ul> <li>Andrea Sangiacomo (principal investigator)</li> <li>Raluca Tanasescu (postdoctoral researcher)</li> <li>Silvia Donker and Hugo Hogenbirk (PhD students)</li> <li>Cristian A. Marocico (scientific programmer, Center for Information Technology)</li> <li>Wim Breakman (bibliographer, University of Groningen Library)</li> </ul> <p> </p> <p>Special thanks to</p>
BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops
<h2>Overview</h2> <p>In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation has created a void in available data.</p> <p>BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text.</p> <p>The current version of the dataset contains <em>~4.3M citations</em> made by approximately <em>211K open access Computer Science conference or workshop papers</em> that, according to DBLP, do not have a DOI. The DBLP snapshot used for this version was the one released on <em>September 2025</em>. </p> <h2>Dataset files</h2> <h3>1. Core Non-DOI Citation Dataset - bip_ndr_{version}.tar.gz</h3> <p>The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. </p> <p>Each JSON object has three main fields:</p> <ul> <li> <p>“_id”: a unique identifier,</p> </li> <li> <p>“citing_paper”, the “dblp_id” of the citing paper,</p> </li> <li> <p>“cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields:</p> <ul> <li> <p>“dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present.</p> </li> <li> <p>“doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present.</p> </li> <li> <p>“bibliographic_reference”: the raw citation string as it appears in the citing paper.</p> </li> </ul> </li> </ul> <p>Changes from previous version:</p> <ul> <li>Added more papers from DBLP.</li> </ul> <h3>2. Citation Intents Dataset - bip_ndr_ci_{version}.tar.gz</h3> <p>This file enriches the BIP! NDR dataset with citation-level intent classification.<br>It preserves the same base structure of the previous file, while adding a nested array of "citations" with each element of "cited_papers".</p> <p>Each "citation" provides the local textual context, section, and intent of the citation in the following format:</p> <ul> <li>"citation_id": Unique identifier in the format {citing_id}>{cited_id}_CIT{index} linking the citing and cited entities.</li> <li>"section": The section of the citing paper where the citation occurs (e.g., Introduction, Methods, Results).</li> <li>"intent": Inferred purpose of the citation based on textual context (see classification schema below).</li> </ul> <p>The "intent" field follows the SciCite classification schema, which categorizes citations into three high-level functional types:</p> <ol> <li>background information: The citation states, mentions, or points to the background information giving more context about a problem, concept, approach, topic, or importance of the problem in the field.</li> <li>method: Making use of a method, tool, approach or dataset.</li> <li>results comparison: Comparison of the paper's results/findings with the results/findings of other work.</li> </ol> <p>The classification is done with the <a href="https://huggingface.co/sknow-lab/Qwen2.5-14B-CIC-SciCite">Qwen2.5-14B-CIC-SciCite fine-tuned Large Language Model, published by Athena RC</a>. </p> <p>Changes from previous version: </p> <ul> <li>Added more papers with intent</li> </ul>
Graphic for Twitter - Call for Open Science Success Stories
<p>This graphic was created to share on Twitter to encourage people to submit compelling stories about open science practices in research to the TOPS team. This graphic was tweeted out on Dr. Chelle Gentemann's Twitter account on August 23, 2022. <a href="https://twitter.com/ChelleGentemann/status/1562049765566709764?s=20&t=kkxyz4dx1vA6obyveL5WNA">Link to tweet</a>.</p>
Data and figures for "A half-century of global collaboration in science and the 'Shrinking World'"
<p>This package supplements the paper entitled <i>"A half-century of global collaboration in science and the 'Shrinking World'"</i> published in <i>Quantitative Science Studies</i> (doi: <a href="https://doi.org/10.1162/qss_a_00268">10.1162/qss_a_00268</a>).</p><p>It contains the datasets and figures used in the original paper based on bibliometric data from a broad set of scientific publications (works), including journal articles, preprints and datasets; see the subfolder named "all_works".</p><p>In addition, for reference, it also contains datasets and figures based on bibliometric data from journal articles only; see the subfolder named "journal_only". The bottom-level files in this subfolder are suffixed with '_j' for identification.</p><p> </p><p><strong>Contents and Instructions</strong></p><p>The datasets and figures in this package are based on the data obtained via <a href="https://docs.openalex.org/api/">OpenAlex API</a>. See the original paper for details. The following file and folders are found at the next level of the subfolders named "all_works" or "journal_only".</p><p> </p><p><strong>- nworks_intlrate_master</strong> (.csv file)</p><ul><li>This file contains information on the number of works ('nworks_all') produced in each of the 15 research disciplines ('discipline' and 'disc_ID'; see below) by 18 countries (Australia, Canada, China, France, Germany, India, Indonesia, Iran, Italy, Japan, Netherlands, Poland, Russia, South Korea, Spain, Switzerland, UK and US) ('country' and 'country_code') from 1970 to 2021 ('year'), the number of international collaborative works among them ('nworks_intl'), and the international collaboration rate ('intlrate') calculated from the ratio of the two.</li><li>The 15 disciplines are Artificial Intelligence ('disc_ID' = 1; 'ai'), Quantum Science (2; 'quantum'), Biotechnology (3; 'bio'), Nanotechnology (4; 'nano'), Agricultural Engineering (5; 'agri'), Particle Physics (6; 'particle'), Aerospace Engineering (7; 'aerospace'), Nuclear Engineering (8; 'nuclear'), Marine Engineering (9; 'marine'), Neuroscience (10; 'neuro'), Condensed Matter Physics (11; 'condensed'), Environmental Engineering (12; 'envi'), Earth Science (13; 'earth'), Astronomy (14; 'astro') and Pure Mathematics (15; 'math'). See the original paper for the definitions of these disciplines.</li><li>The figures contained in the folders '[line]_nworks' and '[line]_intlrate' are based on this dataset.</li></ul><p> </p><p><strong> - [line]_nworks</strong> (Folder)</p><ul><li>This folder contains line plots (.pdf/.png) representing the trends in the number of works by discipline and country, corresponding to the left-hand side diagrams of Fig. 1 and Suppl. Fig. S2 in the v1 preprint.</li></ul><p> </p><p><strong>- [line]_intlrate</strong> (Folder)</p><ul><li>This folder contains line plots (.pdf/.png) representing the trends in the international collaboration rate by discipline and country, corresponding to the right-hand side diagrams of Fig. 1 and Suppl. Fig. S2 in the v1 preprint.</li></ul><p> </p><p><strong>- [chord]_bilateral</strong> (Folder)</p><ul><li>This folder contains chord diagrams (.pdf/.png) representing the bilateral collaborative relationships by discipline and period, corresponding to Fig. 2 and Suppl. Fig. S4 in the v1 preprint. The number at the end of the file name indicates the period represented by the diagram; specifically, '1' = 1971–1990, '2' = 1991–2000, '3' = 2001–2010 and '4' = 2011–2020.</li><li>The raw data (.xlsx) to reproduce the contained diagrams are also provided by discipline in the accompanied 'Data' folder. The file named '[list]_nworks_(discipline name).xlsx' shows, for the top 30 countries ('country' and 'country_code') in work production during the period indicated by the sheet name, their work production ('nworks_all'), the number of international collaborative works among them ('nworks_intl'), and the international collaboration rate ('intlrate') calculated from the ratio of the two. The file named '[mat]_bilat_nworks_(discipline name)' shows the number of works produced by each country pair during the period indicated by the sheet name. Country names are abbreviated by two-letter country codes (ISO 3166-1 alpha-2).</li></ul><p> </p><p><strong>- [dend]_hcluster</strong> (Folder)</p><ul><li>This folder contains circularised dendrograms (.pdf/.png) representing the international research collaboration clusters by discipline and period, corresponding to Fig. 3 and Suppl. Fig. S5 in the v1 preprint.</li><li>The raw data (.xlsx) to reproduce the contained diagrams are also provided by discipline in the accompanied 'Data' folder. The file named '[mat]_bilat_dist_(discipline name)' shows the distance between each country pair for the period indicated by the sheet name, calculated based on the formula presented in the original paper. Country names are abbreviated by two-letter country codes (ISO 3166-1 alpha-2).</li></ul>
Wie Open Science die globale Wissenskooperation revolutionieren kann
<p>Wissen muss weltweit zugänglich sein, um die Krisen unserer Zeit - von Klima und Energie bis hin zu Gesundheit und Ernährungssicherheit - zu bekämpfen. Cloud-Server und satellitengestütztes Internet könnten umfänglichen Zugang ermöglichen. Neben technologischen Lösungen bedarf es jedoch politischen Willens, internationale Kooperationsstrukturen so auszurichten, dass sie die freie Verbreitung von Wissen nicht behindern.</p>
Sustainable Development Goals (SDG) in citizen science - Dataset
<p>The assignment results of SDGs to CS project descriptions are provided in the following dataset. The analysis was conducted based on data retrieved from the CSTRack database on 2022/09/15. </p> <p>See further detail about the study in D2.2 section 7.3.</p> <p><strong>Content and grouping: </strong></p> <ul> <li> <p>The dataset contains the following details: Platform ID (from which platform the CS project descriptions were retrieved), Project Title (Name of the CS project), SDG assignment results (More details about the assignment technique can be found in D3.2 ‘Web Analytics Toolset and Workbench’ - ESA backend), SDG assignment reported in section 7.2 of D2.2 (which only considered the SDG assignment with the highest similarity).</p> </li> </ul>
Research areas in citizen science - Dataset
<p>The dataset contains the following details:</p> <ul> <li>Platform ID (from which platform the CS project descriptions were retrieved)</li> <li>Project Title (Name of the CS project)</li> <li>Research area assignment results (More details about the assignment technique can be found in D3.2 ‘Web Analytics Toolset and Workbench’ - ESA backend)</li> <li>Research Area assignment reported in section 7.2 of D2.2 (which only considered the research area assignment with the highest similarity)</li> <li>Sub research area assignment ((which only considered the sub research area assignment with the highest similarity)</li> </ul>
Report on a Survey among Organisers of Citizen Science Projects - Dataset and Report
<p>In this publication you will find the report on a survey among organisers of citizen science projects developed by Michael Strähle & Christine Urban (alphabetical order), Wissenschaftsladen Wien - Science Shop Vienna. You will also find, the datasets which contain the responses obtained from the very short questionnaire "VSQ" and the responses used for the report.</p>
Image Data sets 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><a href="https://doi.org/10.5281/zenodo.7292917">Photographs</a> </p> <p><a href="https://doi.org/10.5281/zenodo.7292961">X-Ray Fluorescence</a> </p> <p><a href="https://doi.org/10.5281/zenodo.7322908">Hyperspectral Imaging</a> </p> <p><a href="https://doi.org/10.5281/zenodo.7292714">Multispectral Imaging</a></p> <p> </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 have collected this as an example of typical, unprocessed imaging datasets that would be found in standard image conditions. This data is not optimized, nor do we claim it to be perfect quality, our aim is to provide users with access to a range of imaging data sets. We have included the data with minimum processing, as it is read straight from our systems, with the accompanying metadata provided from capture alone.</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>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>
Multispectral Spectral Imaging 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> <ul> <li>Images captured using a <a href="https://photography.phaseone.com/xf-camera-system/">PhaseOne XF Multispectral Camera System.</a> <ul> <li>Image filenames are arranged as postacards_postcardmsi-<strong>Postcard</strong>- <strong>(Wavelength No.)(Filter)</strong>_*sequence order number*_R.tif where wavelength number is the nominal central illumination wavelength in nm (365, 385, 410, 420, 450, 480, 510, 550, 600, 630, 640, 660, 740, 850, 940), Filter is the colour of the long-pass filter (N - no filter, I - Infrared filter, G - Green filter, R - Red filter) and sequence order number is a count from 0001 denoting the order in which the image was acquired)</li> <li>Complementary flats for each of the object images, used typically to process even illumination distribution, captured of white, flat, smooth, non-chemically processed imaging standard flat paper with the same naming convention as above. </li> </ul> </li> <li>postcard_postcardmsi-Postcard.json - Metadata read out collected from MS camera system</li> <li>Truecolour RGB reference image</li> </ul>
Imaging 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> <ul> <li>Photographs at various conditions</li> <li>Flats at matching conditions</li> <li>Metadata stored within image file</li> </ul> <p>Reading file names: </p> <p>(Flat or postcard)<strong>-exp</strong>(exposure value). format</p> <p>*.Jpg - compressed JPEG readout, saved straight from camera</p> <p>*.tiff - non-compressed TIFF readout- saved straight from camera</p> <p>Exposure values (time {sec}): 1/<strong>30</strong>, 1/<strong>60</strong>, 1/<strong>125</strong>, 1/<strong>200</strong>, 1/<strong>400</strong></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.