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96 results for “FAIR data”
Raw data for the computation of ExPaNDS facilities maturity wrt FAIR data catalogues
<p>Raw data for the computation of ExPaNDS facilities maturity wrt FAIR data catalogues.</p> <p>The method is explained in the <a href="https://doi.org/10.5281/zenodo.4146819">report on status, gap analysis and roadmap towards harmonised and federated metadata catalogues for EU national Photon and Neutron RIs</a>.</p>
Copper Tribology FAIR Data Experiments - Sapphire Counterbody
<p><strong>Abstract: </strong>This digital artefact documents the results of experiments in metals tribology. It is constructed strictly observing the FAIR data principles. The experiments test the reciprocation sliding of a 10-mm single-crystal sapphire sphere against a polycrystal (average size ~45 µm) copper base body. The range of normal loads is 0–4.5 N, the sliding velocity is always 0.5 mm/s, and the experiments are performed in ambient 50% RH atmosphere.</p> <p><strong>How to work with this data: </strong>The files in this Zenodo record carry the metadata and descriptions associated with the experiments. They are serialized in RDF. All raw and processed data is collected into RO-Crates (<a href="https://doi.org/10.3233/DS-210053">10.3233/DS-210053</a>), and are stored at institutional servers with the following addresses (these are also semantically linked using Zenodo's schema on the right):</p> <ol> <li><a href="https://dx.doi.org/10.35097/1028">https://dx.doi.org/10.35097/1028</a></li> <li><a href="https://dx.doi.org/10.35097/1029">https://dx.doi.org/10.35097/1029</a></li> <li><a href="https://dx.doi.org/10.35097/1030">https://dx.doi.org/10.35097/1030</a></li> <li><a href="https://dx.doi.org/10.35097/1036">https://dx.doi.org/10.35097/1036</a></li> <li><a href="https://dx.doi.org/10.35097/1037">https://dx.doi.org/10.35097/1037</a></li> <li><a href="https://dx.doi.org/10.35097/1038">https://dx.doi.org/10.35097/1038</a></li> <li><a href="https://dx.doi.org/10.35097/1039">https://dx.doi.org/10.35097/1039</a></li> <li><a href="https://dx.doi.org/10.35097/1041">https://dx.doi.org/10.35097/1041</a></li> <li><a href="https://dx.doi.org/10.35097/1043">https://dx.doi.org/10.35097/1043</a></li> <li><a href="https://dx.doi.org/10.35097/1045">https://dx.doi.org/10.35097/1045</a></li> <li><a href="https://dx.doi.org/10.35097/1047">https://dx.doi.org/10.35097/1047</a></li> <li><a href="https://dx.doi.org/10.35097/1049">https://dx.doi.org/10.35097/1049</a></li> <li><a href="https://dx.doi.org/10.35097/1051">https://dx.doi.org/10.35097/1051</a></li> <li><a href="https://dx.doi.org/10.35097/1052">https://dx.doi.org/10.35097/1052</a></li> <li><a href="https://dx.doi.org/10.35097/1053">https://dx.doi.org/10.35097/1053</a></li> <li><a href="https://dx.doi.org/10.35097/1054">https://dx.doi.org/10.35097/1054</a></li> <li><a href="https://dx.doi.org/10.35097/1057">https://dx.doi.org/10.35097/1057</a></li> <li><a href="https://dx.doi.org/10.35097/1058">https://dx.doi.org/10.35097/1058</a></li> <li><a href="https://dx.doi.org/10.35097/1059">https://dx.doi.org/10.35097/1059</a></li> <li><a href="https://dx.doi.org/10.35097/1060">https://dx.doi.org/10.35097/1060</a></li> <li><a href="https://dx.doi.org/10.35097/1061">https://dx.doi.org/10.35097/1061</a></li> <li><a href="https://dx.doi.org/10.35097/1063">https://dx.doi.org/10.35097/1063</a></li> <li><a href="https://dx.doi.org/10.35097/1065">https://dx.doi.org/10.35097/1065</a></li> <li><a href="https://dx.doi.org/10.35097/1066">https://dx.doi.org/10.35097/1066</a></li> <li><a href="https://dx.doi.org/10.35097/1067">https://dx.doi.org/10.35097/1067</a></li> <li><a href="https://dx.doi.org/10.35097/1070">https://dx.doi.org/10.35097/1070</a></li> <li><a href="https://dx.doi.org/10.35097/1071">https://dx.doi.org/10.35097/1071</a></li> <li><a href="https://dx.doi.org/10.35097/1072">https://dx.doi.org/10.35097/1072</a></li> <li><a href="https://dx.doi.org/10.35097/1073">https://dx.doi.org/10.35097/1073</a></li> <li><a href="https://dx.doi.org/10.35097/1074">https://dx.doi.org/10.35097/1074</a></li> <li><a href="https://dx.doi.org/10.35097/1075">https://dx.doi.org/10.35097/1075</a></li> <li><a href="https://dx.doi.org/10.35097/1076">https://dx.doi.org/10.35097/1076</a></li> <li><a href="https://dx.doi.org/10.35097/1077">https://dx.doi.org/10.35097/1077</a></li> <li><a href="https://dx.doi.org/10.35097/1078">https://dx.doi.org/10.35097/1078</a></li> <li><a href="https://dx.doi.org/10.35097/1079">https://dx.doi.org/10.35097/1079</a></li> <li><a href="https://dx.doi.org/10.35097/1080">https://dx.doi.org/10.35097/1080</a></li> <li><a href="https://dx.doi.org/10.35097/1082">https://dx.doi.org/10.35097/1082</a></li> <li><a href="https://dx.doi.org/10.35097/1083">https://dx.doi.org/10.35097/1083</a></li> <li><a href="https://dx.doi.org/10.35097/1085">https://dx.doi.org/10.35097/1085</a></li> <li><a href="https://dx.doi.org/10.35097/1086">https://dx.doi.org/10.35097/1086</a></li> <li><a href="https://dx.doi.org/10.35097/1087">https://dx.doi.org/10.35097/1087</a></li> <li><a href="https://dx.doi.org/10.35097/1088">https://dx.doi.org/10.35097/1088</a></li> <li><a href="https://dx.doi.org/10.35097/1089">https://dx.doi.org/10.35097/1089</a></li> <li><a href="https://dx.doi.org/10.35097/1090">https://dx.doi.org/10.35097/1090</a></li> <li><a href="https://dx.doi.org/10.35097/1091">https://dx.doi.org/10.35097/1091</a></li> <li><a href="https://dx.doi.org/10.35097/1092">https://dx.doi.org/10.35097/1092</a></li> <li><a href="https://dx.doi.org/10.35097/1093">https://dx.doi.org/10.35097/1093</a></li> <li><a href="https://dx.doi.org/10.35097/1094">https://dx.doi.org/10.35097/1094</a></li> <li><a href="https://dx.doi.org/10.35097/1095">https://dx.doi.org/10.35097/1095</a></li> <li><a href="https://dx.doi.org/10.35097/1096">https://dx.doi.org/10.35097/1096</a></li> <li><a href="https://dx.doi.org/10.35097/1097">https://dx.doi.org/10.35097/1097</a></li> <li><a href="https://dx.doi.org/10.35097/1098">https://dx.doi.org/10.35097/1098</a></li> <li><a href="https://dx.doi.org/10.35097/1099">https://dx.doi.org/10.35097/1099</a></li> <li><a href="https://dx.doi.org/10.35097/1100">https://dx.doi.org/10.35097/1100</a></li> </ol> <p>Records have been anonymized prior to publishing.</p> <p><strong>Statistics about the data:</strong></p> <ul> <li>151,045 RDF triples</li> <li>51 Experimental Series, 542 Individual Events</li> <li>89 Lab Equipment Descriptions</li> <li>108 Experimental Object Descriptions</li> <li>412.1 GB in Total Size</li> </ul> <p><strong>Types of procedures and equipment involved (and count):</strong></p> <ul> <li>Data Processing: 293</li> <li>Block Specimen: 89</li> <li>Light Microscopy: 76</li> <li>Data Publication: 54</li> <li>Tribological Experiment: 50</li> <li>Optical Surface Profilometry: 33</li> <li>Metal Sawing: 30</li> <li>Polishing: 27</li> <li>Electron Microscopy: 26</li> <li>Grinding: 25</li> <li>Electropolishing: 18</li> <li>Heat Treatment: 8</li> <li>Software: 6</li> <li>Tribometer: 6</li> <li>Ultrasonic Cleaner: 3</li> <li>Cup Grinding Machine: 2</li> <li>Electropolishing Machine: 2</li> <li>Furnace: 2</li> <li>Grinding Machine: 2</li> <li>Optical Surface Profilometer: 2</li> <li>Band Saw: 1</li> <li>Demagnetizing Plate: 1</li> <li>Electrolyte: 1</li> <li>Hardness Tester: 1</li> <li>Light Microscope: 1</li> <li>Scanning Electron Microscope: 1</li> <li>Tactile Surface Profilometer: 1</li> <li>Wire Saw: 1</li> </ul> <p><strong>Vocabulary Schema Used:</strong> Schema.org, <a href="https://doi.org/10.5281/zenodo.7709546">Vocabulary of Tribological Experiments</a></p> <p><strong>Versions:</strong></p> <ul> <li>0.2.0 Added reverse links into metadata to published DOIs; other minor fixes</li> <li>0.1.0 First Publication</li> </ul> <p><strong>Related Documents:</strong></p> <ul> <li>Bachelor's and Master's theses (to be published)</li> </ul> <p> </p> <p><strong>For any questions, suggestions, or anything else:</strong> <a href="mailto:nikolay.garabedian@kit.edu">nikolay.garabedian@kit.edu</a> or <a href="https://www.linkedin.com/in/nick-garabedian/">linkedin.com/in/nick-garabedian/</a></p> <p><strong>More information will be continuously updated.</strong></p> <p> </p> <p><strong>Metadata Preview:</strong></p> <pre><code>@prefix k4m784: <https://kadi4mat.iam-cms.kit.edu/records/784#> . @prefix ns1: <https://purls.helmholtz-metadaten.de/vp/kitmtxx-41732562-vp/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix schema: <https://schema.org/> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . <https://kadi4mat.iam-cms.kit.edu/records/784> a schema:Dataset ; rdfs:isDefinedBy [ ns1:gen_inf_equ-de13e7d124b44501a2f75fe330ac1704-vp [ ns1:com_orx_ven-d0357c2850b345cbb8e0185605de3faa-vp "Centre Suisse d'Electronique et de Microtechnique" ; ns1:equ_idx_xxx-55f9296489064da2b4839d6c2d27b3e3-vp "10-157" ; ns1:equ_orx_pro-bb4767e222854d6dae67280595736f6a-vp "Pin-on-Disc Machine" ; ns1:loc_inf_xxx-b24999e0e7264fa29369c967a3843d82-vp [ ns1:bui_xxx_xxx-9f2db0860b7f459f87a29b49c906bc25-vp "MZE, 30.48" ; ns1:flo_xxx_xxx-43fbb63ac5a44d7dbc9670fb37ff8216-vp [ a schema:QuantitativeValue ; schema:value 0 ] ; ns1:ins_loc_xxx-541d1514f1c64a1ba20c8a039cda319a-vp "Karlsruhe Institute of Technology (KIT)" ; ns1:roo_num_xxx-6c175c129e0a4b8a85008af4925882ac-vp "005" ] ; ns1:ope_inx_cha-a975eb0936f449b781eda6b2090c1f91-vp [ ns1:fir_nam_xxx-bbecf3efe21c4237803d09ed15981e2a-vp "***" ; ns1:ins_nam_xxx-81d6c0ba2f1d4dee805ba5c9b2aab29f-vp "Karlsruhe Institute of Technology (KIT)" ; ns1:las_nam_xxx-1be0c624e4114f38872871e5885535f5-vp "***" ; ns1:use_rol_xxx-3d0c936c282b4568ab1c5afcca84a413-vp "Technician" ; ns1:use_tok_xxx-f927a3e2e3d54a7da9526ce37964fdda-vp "***" ] ] ; ns1:per_inf_xxx-104611d1741a4c0680280d10c6d074c3-vp [ ns1:con_pcx_xxx-e43d8b226042456c90b95cb5ed076397-vp [ ns1:arr_ofx_sof-3109a4d5e7d2403eb4d11e3c82bbb7e1-vp [ ns1:sof_nam_xxx-cf5c9ddddb4e4cf0b406e56219af75e6-vp "LabVIEW" ; ns1:sof_ver_xxx-f712859d56484eb9a977ce1ee44d5250-vp "6.1" ] ; ns1:equ_idx_xxx-55f9296489064da2b4839d6c2d27b3e3-vp "00-30-84-6c-0c-bd" ; ns1:lis_ofx_equ-e1d2a3c6048645acaf3864d8ad05ac70-vp ( [ rdf:object [ ns1:equ_rol_xxx-1a1ac062807c4c2497789eee0ab9c3a0-vp "Signal Recording" ] ] [ rdf:object [ ns1:equ_rol_xxx-1a1ac062807c4c2497789eee0ab9c3a0-vp "Motion Control" ] ] ) ; ns1:ope_sys_nam-9a654273d201480f89bffe5473c98e0f-vp "Windows 98" ] ] ; ns1:tec_spe_tri-94e2c75e46434abfaad7f3edeb7982b5-vp [ ns1:arr_ofx_inf-55504fb383534ab397da31ddd82ab9c5-vp ( [ rdf:object [ ns1:con_amp_inf-ed869401a24a4a2eac2bddb2c8b6bf00-vp [ ns1:daq_con_por-e3bb88450b4a46188ad7137b9f285f9a-vp "ai1" ; ns1:equ_orx_pro-bb4767e222854d6dae67280595736f6a-vp "MW 210-13-3" ] ; ns1:equ_rol_xxx-1a1ac062807c4c2497789eee0ab9c3a0-vp "Measure the Height of the Base Body's Surface of Tribological Interest - Respectively Its Waviness" ; ns1:mea_pri_xxx-2c1313b7c58a457b9b2515a0f3e485c7-vp "Capacitive Sensing" ] ] [ rdf:object [ ns1:con_amp_inf-ed869401a24a4a2eac2bddb2c8b6bf00-vp [ ns1:daq_con_por-e3bb88450b4a46188ad7137b9f285f9a-vp "ai2" ; ns1:equ_orx_pro-bb4767e222854d6dae67280595736f6a-vp "MW 210-13-3" ] ; ns1:equ_rol_xxx-1a1ac062807c4c2497789eee0ab9c3a0-vp "Measure the Height of the Counter Body's Bulk - Respectively Its Wear" ; ns1:mea_pri_xxx-2c1313b7c58a457b9b2515a0f3e485c7-vp "Capacitive Sensing" ] ] [ rdf:object [ ns1:con_con_inf-83f4146732e9405da9032e9389b4bd71-vp [ ns1:com_orx_ven-d0357c2850b345cbb8e0185605de3faa-vp "Centre Suisse d'Electronique et de Microtechnique" ; ns1:daq_con_por-e3bb88450b4a46188ad7137b9f285f9a-vp "ai0" ; ns1:equ_idx_xxx-55f9296489064da2b4839d6c2d27b3e3-vp "10-157" ; ns1:equ_orx_pro-bb4767e222854d6dae67280595736f6a-vp "Pin-on-Disc Machine" ] ; ns1:equ_rol_xxx-1a1ac062807c4c2497789eee0ab9c3a0-vp "Measure Load Cell Displacement - Respectively the Friction Force" ; ns1:mea_pri_xxx-2c1313b7c58a457b9b2515a0f3e485c7-vp "Linear Variable Differential Transformer (LVDT) Sensing" ] ] ) ; ns1:arr_ofx_inf-dd899488f1414b4fa1b4e44307b3fc92-vp ( [ rdf:object [ ns1:daq_att_xxx-4214a14bf863452ca6271f2bb08f6f17-vp [ ns1:com_orx_ven-d0357c2850b345cbb8e0185605de3faa-vp "National Instruments" ; ns1:equ_orx_pro-bb4767e222854d6dae67280595736f6a-vp "USB-6212" ] ; ns1:daq_int_nam-2ead3c13b6884332a5d212595b039cc7-vp "USB" ] ] ) ; ns1:mot_ind_sub-64d48ea342d4415b9c20a13297050f90-vp ( [ rdf:object [ ns1:axi_nam_xxx-7c10343c04934f05a583f21b2a927499-vp "Base Body Rotation" ; ns1:mot_ind_sub-93a6d6b8c5c748a585f94cd37a2d6256-vp [ ns1:com_orx_ven-d0357c2850b345cbb8e0185605de3faa-vp "CSEM" ; ns1:equ_orx_pro-bb4767e222854d6dae67280595736f6a-vp "Build-in Drive" ] ; ns1:pri_ofx_mot-3c829fbb032845d8b7a202d7cce9e2cd-vp "DC Motor" ] ] ) ; ns1:str_inf_xxx-e9298074c4be472798076fcf5efbbca3-vp [ ns1:bas_bod_cla-ad66c57967a048db811d6c64db25f2bc-vp "Bolt" ; ns1:cou_bod_cla-a45820b32a1d498195988b9c468f4110-vp "Bolt (Mandrel)" ; ns1:hou_met_xxx-765e29fc1f65482b90b9c0da6c76815a-vp "Climate Box" ; ns1:pri_ofx_loa-000c058b7b324521a13bc44f8cdbb210-vp "Dead Weight(s)" ; ns1:sam_sub_met-d0762a0ba7964091b0e9da84932345a2-vp "Rim around Disc" ; ns1:vib_mit_met-2cc6a1c2302b4ceda57a78c553f8867d-vp "Lab Bench" ] ] ] ; schema:additionalType k4m784:lab%20equipment ; schema:author <https://kadi4mat.iam-cms.kit.edu/users/65> ; schema:dateCreated "2021-02-17T15:23:52.448311+00:00"^^xsd:dateTime ; schema:dateModified "2023-04-29T14:17:13.990908+00:00"^^xsd:dateTime ; schema:identifier "7addb4cda29d4f80b3e63df5ac674e7c-vp-aaazd-kitmt" ; schema:keywords "001066-79dfbfc9fd3882a1c2d10053800c6306-vp", "09aa26cf985681760020f32222a06c25-vp", "7addb4cda29d4f80b3e63df5ac674e7c-vp", "csem", "d879a97efd724dedbc16e6b223b8e961-vp", "kitmtxx-41732562-vp", "tri_xxx_xxx-c98170df4aa14cd38e9ba0d1b94ebdf0-vp", "tribometer" ; schema:license <https://creativecommons.org/licenses/by/4.0/> ; schema:name "Tribometer CSEM" ; schema:text """*Info:* A unidirectional pin-on-disc tribometer that can be used to conduct tribological experiments. It allows monitoring and recording of friction force and linear wear (via capacitive distance sensors)""".</code></pre> <p> </p>
How to Ensure Researchers Share Their FAIR Data: Practical Tips and Tools [Online Workshop, Recording]
<p>The online hands-on workshop was aimed at trainers and support staff covering critical elements of data sharing and available tools and resources for supporting Open Science including:<br> • Open Science resources and Data Management Planning<br> • Consent and Ethical considerations<br> • Legislation and Licence frameworks<br> The objectives of the workshop were i) to raise awareness of key tools and resources available for Open Science training ii) to enable a platform to exchange ideas regarding key training topics and iii)n to provide training materials and worksheets for future reuse.<br> The workshop consisted of presentations, demos, a roundtable discussion on ethical considerations, a showcase of licence frameworks at different European archives and an exercise with all participants fostering an exchange of experiences focused on learnt lessons.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=uztTCRFRZHg"> the CESSDA Training YouTube channel</a>.</p>
Orphanet catalog FAIR Data Point
<pre>This is POC FAIR Data Point to describe biobank and patient registry. The content of this FAIR Data Point is extracted via EJPRD LDP</pre>
Data and code for EDI overview paper, data collection characteristics, FAIR evaluation, downloads, and citations
The Environmental Data Initiative (EDI) is a trustworthy, stable data repository and data management support organization for the environmental scientist. EDI provides tools and support that allow the environmental researcher to easily integrate data publishing into the research workflow. Almost ten years since going into production, these data and code were used to provide a general description of EDI’s collection of data and its data management philosophy and placement in the repository landscape. They show how comprehensive metadata and the repository infrastructure lead to highly findable, accessible, interoperable, and reusable (FAIR) data by evaluating compliance with specific community proposed FAIR criteria. Finally, they provide measures and patterns of data (re)use, assuring that EDI is fulfilling its stated premise.
Data for D7.1 FAIR in European Higher Education
<p>As part of the EOSC project family the FAIRsFAIR - Fostering Fair Data Practices in Europe - project aims to supply practical solutions for the use of the FAIR data principles throughout the research data life cycle. The FAIRsFAIR project runs from March 2019-February 2022.</p> <p>FAIRsFAIR Work Package 7 “FAIR Data Science and Professionalisation” aims to develop resources and build communities that support the uptake of RDM and FAIR practice within higher education curricula.</p> <p>The data published here stems from a both a web-based questionnaire with 90 responses conducted within FAIRsFAIR WP7 between 19 September and 15 November 2019.</p> <p>The questionnaire covered several dimensions of research data management at HEIs relevant for the implementation of FAIRsFAIR WP7, as well as WP3 “FAIR Data Policy Practice” and WP6 “FAIR Competence Centre”. These dimensions included:</p> <ul> <li>Institutional research data management policies </li> <li>Support services for research data management</li> <li>Competence development of students and graduates</li> <li>Universities and EOSC</li> <li>FAIRsFAIR support for universities</li> </ul> <p>The data resulting from the survey has been used as the basis for <a href="http://doi.org/10.5281/zenodo.3629683">D7.1 FAIR in European Higher Education</a>.</p> <p>The following files are available:</p> <ul> <li>Codebook including original questionnaire</li> <li>Dataset</li> </ul>
FAIR Data Point
<h2>What's Changed</h2> <ul> <li>Set permit ACCEPTED for existing index entries by @dennisvang in https://github.com/FAIRDataTeam/FAIRDataPoint/pull/774</li> </ul> <p><strong>Full Changelog</strong>: https://github.com/FAIRDataTeam/FAIRDataPoint/compare/v1.18.0...v1.18.1</p>
How Fair Is Bioarchaeological Data
<p>Data collected for conference proceeding accessible here :<br>Lien-Talks, A. (2024). How FAIR is Bioarchaeological Data: with a particular emphasis on making archaeological science data Reusable. https://doi.org/10.5281/zenodo.10935099</p>
Dataset shown on the HMC FAIR Data Dashboard as of June 2023
<p>This dataset contains literature metadata harvested for 15 research centers of the Helmholtz Association of German research centers (KIT, FZJ, DESY, AWI, DLR, GFZ, HZB, GEOMAR, MDC, UFZ, HZDR, DZNE, GSI, CISPA, HMGU) during the first two quarters of 2023 as well as metadata of linked data publications, as extracted from the ScholExplorer API. F-UJI scores for these data publications are based on F-UJI version 1.4.7 using the FAIRsFAIR metrics 0.4. The status of the data represents the data shown on the HMC Dashboard on Open and FAIR Data in Helmholtz (<a title="https://fairdashboard.helmholtz-metadaten.de/" href="https://fairdashboard.helmholtz-metadaten.de/">https://fairdashboard.helmholtz-metadaten.de/</a>) as of June 2023.</p>
Metadata Profile for FAIR Sensor Data based on the SensOr Interfacing Language
<p>Metadata profile to provide FAIR sensor data. The profile is created using SHACL and is based on the SOSA ontology which accurately specifies restrictions on the properties of specific sensors using the QUDT and the SSN ontology. Generic metainformation is modeled using DCTerms. </p>
Generating FAIR Research Data in Experimental Tribology
<p><strong>Stream video at:</strong> <a href="http://youtu.be/xwCpRDnPFvs">https://youtu.be/xwCpRDnPFvs</a></p> <p>To assess the feasibility of producing FAIR data via the integration of a controlled vocabulary, an ontology, and an ELN, this dataset demonstrates the implementation of a tribological experiment while accounting for as many details as possible. The showcase experiment had a lubricated pin-on-disk arrangement, ran at 15 N normal load and a velocity range of 20 to 170 mm/s. With this dataset, we hope to provide a possible blueprint for FAIR data publication in experimental tribology.</p> <p><a href="http://www.nature.com/articles/s41597-022-01429-9">https://www.nature.com/articles/s41597-022-01429-9</a> - Garabedian, N.T., Schreiber, P.J., Brandt, N., Greiner, C., et al.</p> <p>Abstract: Generating FAIR research data in experimental tribology. Sci Data 9, 315 (2022). Digital solutions for the generation of FAIR (Findable, Accessible, Interoperable and Reusable) data and metadata in experimental tribology are currently lacking, despite the looming challenge of integrating cutting-edge data science techniques – a promising scientific route for any field that often relies on phenomenology and empiricism. Additionally, the broad interdisciplinarity of tribology is probably a main contributing factor for the lack of community-wide data and metadata standards, and the heavy reliance on custom workflows and equipment. This paper, first, outlines a sample framework for scalable generation of FAIR data, and second, delivers a showcase FAIR data package for a pin-on-disk tribological experiment. The resulting curated data, consisting of 2,008 key-value pairs and 1,696 logical axioms, is the result of (1) the close collaboration with developers of a virtual research environment, (2) crowd-sourced controlled vocabulary, (3) ontology building and (4) numerous – seemingly – small-scale digital tools. Thereby, this paper demonstrates a collection of scalable non-intrusive techniques that extend the life, reliability and reusability of experimental tribological data beyond typical publication practices.</p> <p><a href="https://doi.org/10.5281/zenodo.5720626">https://doi.org/10.5281/zenodo.5720626</a> - FAIR Data Package of a Tribological Showcase Pin-on-Disk Experiment</p> <p><a href="https://doi.org/10.5281/zenodo.5720198">https://doi.org/10.5281/zenodo.5720198</a> or <a href="https://github.com/nick-garabedian/TriboDataFAIR-Ontology">https://github.com/nick-garabedian/TriboDataFAIR-Ontology</a> or <a href="https://fairsharing.org/3597">https://fairsharing.org/3597</a> - TriboDataFAIR Ontology</p> <p><a href="https://doi.org/10.5281/zenodo.5720218">https://doi.org/10.5281/zenodo.5720218</a> or <a href="https://github.com/nick-garabedian/SurfTheOWL">https://github.com/nick-garabedian/SurfTheOWL</a> - SurfTheOWL</p> <p><a href="https://kadi4mat.iam-cms.kit.edu/">https://kadi4mat.iam-cms.kit.edu/</a> - Kadi4Mat Virtual Research Environment and Electronic Lab Notebook </p>
FAIR Data sharing à la FBM : garantie d'une recherche plus transparente et reproductible
<p>Nouveaux services développés à la FBM UNIL/CHUV pour répondre aux principes FAIR/ Open Research Data</p>
FAIRness Assessment of Biomedical Data Using Automated Tools (Dataset)
<p>The data were collected as part of a Master's thesis project aimed at evaluating various automated FAIR assessment tools, applying them to biomedical data. The data sets identifiers were gathered as part of the Open Data LoM and IoM incentivization at Charité Universitätsmedizin Berlin, available at <a title="Dataset of the results of data validation for articles from 2021" href="https://doi.org/10.5281/zenodo.8249758">https://doi.org/10.5281/zenodo.8249758</a>, and reused in this project.</p> <p>The data represents cleaned, aggregated, and transformed results obtained from the API services of the following FAIR assessment tools: F-UJI, FAIR Enough, FAIR-Checker, and FAIR EVA.</p> <p>The raw data in .Rdata format will be shared on GitHub repository at <a title="FAIR Tools Analysis" href="https://github.com/anastasiabright/fair-tools-analysis">https://github.com/anastasiabright/fair-tools-analysis</a>.</p>
Assessment of Fair Trade education programs in France: data 2022 from the control group and those from the two experimental fields (the Fair Generation scheme and the Fair Trade Universities Label)
<p><span>see the technical report (period 2019-2021) on researchgate:</span></p> <p><span><a href="https://www.researchgate.net/publication/380823820_Evaluation_of_the_fair-trade_education_programs_Results_of_the_first_phase_of_the_Fair_Future_program">(PDF) Evaluation of the fair-trade education programs. Results of the first phase of the Fair Future program (researchgate.net)</a></span></p>
Assessment of Fair Trade education programs in France: high school data (2019-2022)
<p>see the technical report (period 2019-2021) on researchgate:</p> <p><a href="https://www.researchgate.net/publication/380823820_Evaluation_of_the_fair-trade_education_programs_Results_of_the_first_phase_of_the_Fair_Future_program">(PDF) Evaluation of the fair-trade education programs. Results of the first phase of the Fair Future program (researchgate.net)</a></p> <p> </p>
Assessment of Fair Trade education programs in France: data 2021 from the control group and those from the two experimental fields (the Fair Generation scheme and the Fair Trade Universities Label)
<p><span>see the technical report (period 2019-2021) on researchgate:</span></p> <p><span><a href="https://www.researchgate.net/publication/380823820_Evaluation_of_the_fair-trade_education_programs_Results_of_the_first_phase_of_the_Fair_Future_program">(PDF) Evaluation of the fair-trade education programs. Results of the first phase of the Fair Future program (researchgate.net)</a></span></p>
M4.4 (associated data) - FAIR-IMPACT Review of Semantic Artefact Catalogues and technologies
<p>This dataset (version 1) takes the form of a spreadsheet corresponding to the associated data described by <a href="../records/12799796" target="_blank" rel="noopener"><strong>M4.4 - Review of Semantic Artefact Catalogues and guidelines for serving FAIR semantic artefacts in EOSC</strong></a></p> <p>The spreadsheept (available here in ODS format) contains the listing of Semantic Artefact Catalogues (SACs) done within FAIR-IMPACT's WP4, their classifications (by status, type, discipline and technology) and the evaluation of their FAIR-enabling dimensions. </p> <p>A "live" version of this spreadsheet is available as an open Google Sheet open for comments and suggestions. We will take external contributions and comments into consideration when producing new verion of this dataset. Contributions could be of several types: </p> <ul> <li>New SAC or modification of the ones currently identified;</li> <li>New SAC technology or modification of the ones currently identified;</li> <li>New FAIR-enabling assessment or modification of the ones currently available.</li> </ul> <p>For more information, interested parties may contact the authors.</p> <p> </p>
Experiment Result Plots of Data Stewardship (FAIR - Assignment 1)
<p>These plots show the results of the experiment by creating a scatterplot of the variables and a line plot.</p>
F-UJI and FAIR Enough tool comparison dataset (European Research Data Landscape study)
<p>Dataset used to compare the assessment results on the levels of Findability, Accessability, Interoperability and Reusability of datasets in a sample of repositories, by means of the F-UJI FAIR data assessment tool and FAIR-Enough assessment tool. Assessment carried out for the European Research Data Landscape study.</p>
Is data sharing in LCA FAIR
<p>Data for Setac Abstract - </p> <p>In the light of rising awareness, and growing need of better data management across disciplines, it is pertinent to investigate how the FAIR principles are utilized in the LCA domain. The purpose of this research is to investigate the status quo of data sharing by LCA practitioners. This study will look into data shared in relation to research outputs (e.g. peer reviewed articles). The life cycle inventory (LCI) is the most common data that is re-used, hence this study investigates how the LCI is shared in peer reviewed articles. A review of the findability, accessibility, interoperability and re-usability of the LCI data of 25 peer reviewed articles was performed. This study highlights although there is growing awareness on the importance of data sharing , the lack of a clear guidelines within the LCA domain as well as limited infrastructure is a major barrier in implementing FAIR principles. Research data sharing is beyond the sole responsibility of individual researchers. The overall research and funding infrastructure must consider the diversity of practices, differences in fields, facilitate the sharing of a broad range of research outputs. Current gaps in academic data sharing can be seen as opportunities to build a common framework</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.