Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,566
datasets available to search
ShareScore release 0.9.0
Dataset results
1,566 results for “Definitions”
European Collaboration for Healthcare Optimisation (ECHO) Indicators Definition Crosswalks
<p><strong>European Collaboration for Healthcare Optimisation (ECHO) Indicators Definition Crosswalks</strong></p> <p>ECHO indicators rationale and code definition mapped out in ICD-9 and ICD-10 (for diagnoses) and ICD-9, NOMESCO, OPCS-4, ACHI and Leustungkatalog. </p> <p> </p>
Figure data and code used in Inconsistent definitions of GDP: Implications for estimates of decoupling
<p>Figure code in R and underlying data to reproduce all figures in the article "Inconsistent definitions of GDP: Implications for estimates of decoupling".</p>
Content analysis of occupational definitions
<p>The methodological process followed for the competence assignment has considered two main phases. In a first phase, a taxonomic analysis has been carried out, identifying and systematizing the tasks included in around the 1.300 definitions of the two main occupational classification systems SOC-2018 and ISCO-2008. Once systematized, it has been assigned to key competences from the European Reference Framework on Key Competences for Lifelong Learning established by the European Commission (European Council, 2018). In a second phase, and on the basis of the results obtained, an analysis of competences has been developed. To make it possible, it has been established two indexes that measure to what extent a competence is relevant to an occupation, quantifying if such competence is present in all the tasks performed for such occupation or just in some or even if it is not (extension). The second index, specialization, measures to what extent a given competence is the most important of the tasks developed by an occupation, or if on the contrary, it is only one of the required competences.</p>
Multi-Profile Ultra High Definition (UHD) AVC and HEVC 4K DASH Datasets
<p>We present a Multi-Profile Ultra High Definition (¥emph{UHD}) DASH dataset composed of both AVC (H.264) and HEVC (H.265) video content, generated from three well known open-source 4K video clips. The representation rates and resolutions of our dataset range from 40Mbps in 4K down to 235kbps in 320x240, and are comparable to rates utilised by on demand services such as Netflix, Youtube and Amazon Prime. We provide our dataset for both real-time testbed evaluation and trace-based simulation. The real-time testbed content provides a means of evaluating DASH adaptation techniques on physical hardware, while our trace-based content offers simulation over frameworks such as ns-2 and ns-3. We also provide the original pre-DASH MP4 files and our associated DASH generation scripts, so as to provide researchers with a mechanism to create their own DASH profile content locally. Which improves the reproducibility of results and remove re-buffering issues caused by delay/jitter/losses in the Internet.<br> <br> The primary goal of our dataset is to provide the wide range of video content required for validating DASH Quality of Experience (QoE) delivery over networks, ranging from constrained cellular and satellite systems to future high speed architectures such as the proposed 5G mmwave technology.</p>
Weather Regime definition for the Euro-Atlantic sector (Daily, DFJM, 1979-2018) used for ACDC-ESM
<p><strong>Weather Regime definition for the Euro-Atlantic sector at daily resolution from 1979-2018 for December to March in CSV format</strong></p> <p> </p> <p><strong>TL;DR</strong>: this is the weather regime assignment based the method as set out by Swinda K.J. Falkena in 'Revisiting the identification of wintertime atmosphericcirculation regimes in the Euro-Atlantic sector' (<a href="https://doi.org/10.1002/qj.3818">10.1002/qj.3818</a>). Daily data is provided for December to March for the period 1979-2018.</p> <p> </p> <p><strong>Method Description </strong><br> The weather regime assignment can be obtained by applying <em>k</em>-means clustering to the full field data of geopotential height data. Following the observed circulation in reanalysis data, the optimal number of clusters is six. By incorporating a weak persistence constraint in the clustering procedure the assignment is stabilized, without changing the weather regime occurrence rates.</p> <p>The six regimes used have been labelled to indicate atmospheric state. Due to their symmetry, a name (Atlantic Ridge (AR), North Atlantic Oscillation (NAO) and Scandinavian Blocking (SB)) and state (positive (+) and negative (-)) are used to label each of the six weather regimes. It should be noted that the naming convention used, does not imply that the weather associated with these six weather regimes is similar to a definition that uses four or two clusters to classify the weather.</p> <p>Full details on the method can be found in: Swinda K.J. Falkena, et al, 'Revisiting the identification of wintertime atmosphericcirculation regimes in the Euro-Atlantic sector' (DOI:<a href="https://doi.org/10.1002/qj.3818">10.1002/qj.3818</a>). The original implementation and source code can be found on gitHub via: <a href="https://github.com/SwindaKJ/Regimes_Public">github.com/SwindaKJ/Regimes_Public</a>.</p> <p> </p> <p><strong>Data structure description</strong><br> The file is provided in CSV (.csv) format with a semicolon (;) as separator. The first row stores the column labels. The columns contain the following:</p> <ul> <li>first column (or A) contains the valid-time <ul> <li>Label: datetime</li> <li>Contents represent time with text as [DD/MM/YYYY])</li> </ul> </li> <li>second column (or B) contains the assigned weather regime <ul> <li>Label: WR</li> <li>Contents represent the assigned cluster as an interger in the range [0,5]</li> <li>Meaning: 0="SB-", 1="AR+", 2="NAO-", 3="SB+", 4="NAO+", 5="AR-"</li> </ul> </li> </ul> <p> </p> <p><strong>DISCLAIMER</strong>: <em>the content of this dataset has been created with the greatest possible care. However, we invite to use the original assignement of weather regimes for critical applications and studies. </em></p>
Argo-based ocean surface mixed layer depths using the buoyancy gradient definition of Whitt Nicholson and Carranza (2019)
<p>Argo-based mixed layer depth profiles derived from the CORA product as described in Whitt Nicholson Carranza. A binned 2-degree climatology was published previously:</p> <p>https://github.com/danielwhitt/globalimpacts_2019_whittetal/blob/master/MonthlyClimatology_ARGO_MLDbmax_TEOS10_Copernicus_PF_2000-2017_all_jun252019_nc.nc</p> <p>with:</p> <p>Whitt, D. B., Nicholson, S. A., & Carranza, M. M. (2019). Global Impacts of Subseasonal (< 60 Day) Wind Variability on Ocean Surface Stress, Buoyancy Flux, and Mixed Layer Depth. <em>Journal of Geophysical Research: Oceans</em>, <em>124</em>(12), 8798-8831</p> <p>Contact the authors with questions. </p> <p>The chosen mixed layer depth definition is the same as "HMXL", a standard output of the Community Earth System Model (CESM) ocean component.</p>
Review of definitions of Open Peer Review in the scholarly literature 2016
<p>This data set contains:</p> <ul> <li>Full data files of a 2016 review of definitions of Open Peer Review in the scholarly literature in xls and csv formats</li> <li>Description of data collection methodology (txt)</li> <li>Readme file (txt)</li> </ul> <p>The term “open peer review” has neither a standardized definition nor an agreed schema of its features and implementations. Recognising the absence of a consensus view on what OPR is, OpenAIRE has undertaken a systematic review of definitions of “open peer review” or “open review”, to create a corpus of 122 definitions. These definitions have been systematically analysed to build a coherent typology of the many different innovations in peer review signified by the term and hence provide the precise technical definition currently lacking. This quantifiable data offers rich information on the range and extent of differing definitions over time and by broad subject area.</p> <p>Contact:</p> <p>Tony Ross-Hellauer: http://orcid.org/0000-0003-4470-7027 / ross-hellauer@sub.uni-goettingen.de</p>
Data for "A Quantum Definition of Molecular Structure"
<p>Supplemental data for our article "A Quantum Definition of Molecular Structure".</p><p>Version 1.1.0 contains data for additional k-medoids runs performed on different subsets of the complete sample.</p>
The source of energy, the fifth dimension and definition of time
<p>**TITLE: ENERGY SOURCE, THE FIFTH DIMENSION, AND THE DEFINITION OF TIME.**</p><p> </p><p>**INTRODUCTION:** It is known that each object in our universe is defined by these coordinates x, y, z, and that time, as concluded by Albert Einstein, is referred to as the fourth dimension. I am confident that the very existence of each object in our universe, in addition to these four dimensions (x, y, z, t), the energy source is the fifth dimension.</p><p> </p><p>This can be defined as the distance from any object to its energy source, which divides based on the time needed for this energy to reach the object. On our Earth, it is the sun, and in our galaxy, it is the black hole at the center. Thus, as a first deduction, black holes ⚫️ are sources of energy.</p><p> </p><p>These four forces - strong force, weak force, electromagnetic force, gravitational force - have grounded humanity on Earth 🌎, and to leave, it requires a lot of energy and many risks. So, it takes a new approach to physics, starting with an essential element, which is time.</p><p> </p><p>**METHODOLOGY:** The cosmos and universes are eternal; nothing is lost, and nothing is created; everything transforms. Thus, the term time is the beginning of an event or phenomenon, and time does not flow the same way from one star to another, from one galaxy to another, or from one individual to another.</p><p> </p><p>For example, you and I are the same age but show different signs of aging. So, time is sequential and manifests through temporal energy power.</p><p> </p><p>**DEFINITION OF THE ENERGY SOURCE:** The energy source is the speed of any energy to reach the surface of an object while embracing the gravitational lines of that object. We can determine it by a simple physical concept, which is \(S_e = C/G^2\); the energy source is the FIFTH DIMENSION.</p><p> </p><p>**DEFINITION OF TIME:** We can start talking about the moment when temporal energy is just at the point of contact between light and gravitational curves. Light slips between gravitational curves to reach us on Earth 🌎, knowing that light and gravity travel at the same speed in the universe. Thus, the beginning of the term TIME ⌛️ can be expressed in this way:</p><p> </p><p>\[T = cĥ \times \frac{C}{G²}\]</p><p> </p><p>\[E_t = M \times \frac{C}{\pi G²}\]</p><p> </p><p>This new physics conception could one day allow us to leave our Earth 🌎 easily with less energy and fewer risks, making interstellar travel more accessible.</p><p> </p><p>**DISCUSSION:** Rainbows and auroras are visible events to the naked eye of this interaction between light and gravitational curves. In a black hole, gravity is so intense that light does not travel inside, and time stops ⌛️ completely.</p><p> </p><p>This definition of time \(T=cĥ \times \frac{C}{G²}\) summarizes everything. So, time + space + light form the temporal sphere and manifest as temporal energy, which can be called the 5th dimension.</p><p> </p><p>TIME + SPACE = SPACE-TIME = 4TH DIMENSION. TIME + SPACE + LIGHT = TIME SPHERE = 5TH DIMENSION.</p><p> </p><p>In the fifth dimension, light excites gravity (gravitons), and the latter contracts to bend space-time and objects, stars, galaxies, stars... etc. This gives us the ability to bring distances between point A and point B closer without affecting or modifying anything, and this will be the next mechanism for future spacecraft.</p><p> </p><p>**CONCLUSION:** The model I have just published will complete physics in its fifth dimension, allowing humanity to create very sophisticated devices that can shorten routes and interstellar travel by using a space characteristic never used before, which is the CURVATURE OF SPACE.</p><p> </p><p>**PREDICTION AND DEDUCTION:** Each galaxy has its own black hole at the center, and each black hole is a source of energy. Each black hole has two faces, one that gives life to stars, planets, stars, nebulae, etc.</p><p> </p><p>1. A dying world gives birth to another world; nothing is lost, nothing is created, everything transforms.</p><p>2. Black holes dictate the rotation speed of each star and its inclination.</p><p>3. Celestial bodies, stars, planets regularly come from the side of the black hole to take charge of destiny, time, and memory to start their journeys in the universe again.</p><p>4. Just at the exit of the black hole, physically speaking, it's the moment t=0, the beginning of all life.</p><p>5. In the universe, time runs in two directions, one-way and a return to the energy source.</p><p>6. A place in the universe devoid of black holes will see accumulations of galaxies and planets and large voids.</p><p>7. Black holes uniformly distribute matter and energy in all corners of the universe.</p><p>8. On Earth, mass generates energy, but in the universe, energy generates mass for a potential balance. This means that masses already have their own accelerations or are simply fueled by energy present everywhere in the universe. Of course, in contact with an energy source like our sun, all planets around our sun are powered by the energy released by our sun in contact with the dark energy of our universe.</p><p>9. End of the use of fossil fuels and the end of air travel by plane, making way for a practical and non-polluting technique to move in the universe by bending space and bringing distant points closer without altering the texture of space.</p><p>10. End of wars and fights for earthly wealth; each country will have its galaxies to supply essential materials.</p>
Deliverable 2.1 Aero-hydro-elastic model definition - SOFTWIND 10 MW FOWT (wave-tank SIL version)
<p>For the detailed validation and verification of the capabilities of QBladeOcean in work package 2 of FLOATECH, a detailed definition of the models is needed. This database presents the QBladeOcean model of the DTU 10MW Reference Wind Turbine mounted on the SOFTWIND floater.</p> <p>Update V2.0.0: <br>Structure files are modified according to the requirements of the QBladeCE version</p> <p>Update V3.0.0:<br>- Added controller from SOFTWIND experiments (Modified from DTU 10MW to have oO star controller parameters)<br>- Modified mooring line length<br>- Shifted platform COG slightly towards centerline<br>- Modified blade definition to AD14 blade def.<br>- Included STATICBUOYANCY flag</p> <p>Update V3.1.0:<br>- Included ADVANCEDBUOYANCY flag<br>- Corrected excitation file (.3), previously: incorrect assignment of wave headings and excitation force coefficients<br>- Addition of mean drift file (.8)<br>- Corrected error in added mass matrix entry [4,2] (sway-roll coupling)</p> <p>Update V3.2.0:<br>- DELTA_DIR_DIFF 1-->20<br>- STATICBUOYANCY --> true</p> <p>Update V3.3.0:<br>- updated Substructure .txt file to format compatible with new QBlade version 2.0.6.4+<br>- extrapolation stretching activated<br>- depth dependent drag coefficient of 0.6 until z = -4m<br>- adjusted "DAMP_[-]" paremeter in the "MOORELEMENTS" table of ths Substructure .dat file to be zero due to numerical instabilities</p>
Deliverable 2.1 Aero-hydro-elastic model definition - OC5 5MW MSWT
<p>For the detailed validation and verification of the capabilities of QBladeOcean in work package 2 of FLOATECH, a detailed definition of the models is needed. This database presents the QBladeOcean model of the MARIN Stock Wind Turbine mounted on the OC5 floater.</p> <p>Update V2.0.0; Structure files are modified according to the requirements of the QBladeCE version</p> <p>Update V3.0.0; Bugfix mooring line 3 definition</p> <p>Update V4.0.0;<br>- TOWERDRAG activated and set to cd = 0.5<br>- Inlcusion of Non-linear QTF forces<br>- Modified RAYLEIGHDMP 0.05 --> 0.01</p> <p>Update V5.0.0;<br>- updated Substructure .dat file to a format compatible with QBlade version 2.0.6.4+<br>- extrapolation stretching activated<br>- depth dependent drag coefficient of 0.6 until z = -4m<br>- enhanced model to improve low frequency pitch excitation --> additional parameters in HYDROJOINTCOEFF table<br>- adjusted "DAMP_[-]" paremeter in the "MOORELEMENTS" table of the Substructure .dat file to be zero due to numerical instabilities</p>
Definitions of terms extracted from data-related European Union laws, version 3
<p>Collection of definitions of terms in English, French, German, Italian and Spanish extracted from the following data-related European laws:</p> <ol> <li> <p><a href="http://data.europa.eu/eli/dir/2007/2/oj?locale=en">Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (<strong>INSPIRE</strong>)</a></p> </li> <li> <p><a href="http://data.europa.eu/eli/reg/2016/679/2016-05-04?locale=en">Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (<strong>General Data Protection Regulation</strong>) (Text with EEA relevance)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reco/2018/790/oj?locale=en">Commission Recommendation (EU) 2018/790 of 25 April 2018 on <strong>access to and preservation of scientific information</strong></a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg/2018/1807/oj?locale=en">Regulation (EU) 2018/1807 of the European Parliament and of the Council of 14 November 2018 on a framework for the <strong>free flow of non-personal data</strong> in the European Union (Text with EEA relevance)</a></p> </li> <li> <p><a href="https://data.europa.eu/eli/dir/2019/790/oj?locale=en">Directive (EU) 2019/790 of the European Parliament and of the Council of 17 April 2019 on <strong>copyright and related rights in the Digital Single Market</strong> and amending Directives 96/9/EC and 2001/29/EC (Text with EEA relevance)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/dir/2019/1024/oj?locale=en">Directive (EU) 2019/1024 of the European Parliament and of the Council of 20 June 2019 on open data and the re-use of public sector information (recast) (<strong>Open Data Directive</strong>)</a></p> </li> <li><a href="https://eur-lex.europa.eu/eli/reg/2021/695/oj?locale=en">Regulation (EU) 2021/695 of the European Parliament and of the Council of 28 April 2021 establishing <strong>Horizon Europe</strong> – the Framework Programme for Research and Innovation, laying down its rules for participation and dissemination, and repealing Regulations (EU) No 1290/2013 and (EU) No 1291/2013 (Text with EEA relevance)</a></li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg/2022/868/oj?locale=en">Regulation (EU) 2022/868 of the European Parliament and of the Council of 30 May 2022 on European data governance and amending Regulation (EU) 2018/1724 (<strong>Data Governance Act</strong>) (Text with EEA relevance)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg/2022/1925/oj?locale=en">Regulation (EU) 2022/1925 of the European Parliament and of the Council of 14 September 2022 on contestable and fair markets in the digital sector and amending Directives (EU) 2019/1937 and (EU) 2020/1828 (<strong>Digital Markets Act</strong>) (Text with EEA relevance)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg/2022/2065/oj?locale=en">Regulation (EU) 2022/2065 of the European Parliament and of the Council of 19 October 2022 on a Single Market For Digital Services and amending Directive 2000/31/EC (<strong>Digital Services Act</strong>) (Text with EEA relevance)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg_impl/2023/138/oj?locale=en">Commission Implementing Regulation (EU) 2023/138 of 21 December 2022 laying down a list of specific <strong>high-value datasets</strong> and the arrangements for their publication and re-use (Text with EEA relevance)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg/2023/2854/oj?locale=en">Regulation (EU) 2023/2854 of the European Parliament and of the Council of 13 December 2023 on harmonised rules on fair access to and use of data and amending Regulation (EU) 2017/2394 and Directive (EU) 2020/1828 (<strong>Data Act</strong>)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg/2024/903/oj?locale=en">Regulation (EU) 2024/903 of the European Parliament and of the Council of 13 March 2024 laying down measures for a high level of public sector interoperability across the Union (<strong>Interoperable Europe Act</strong>)</a></p> </li> <li> <p><a href="https://eur-lex.europa.eu/eli/reg/2024/1689/oj?locale=en">Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence and amending Regulations (EC) No 300/2008, (EU) No 167/2013, (EU) No 168/2013, (EU) 2018/858, (EU) 2018/1139 and (EU) 2019/2144 and Directives 2014/90/EU, (EU) 2016/797 and (EU) 2020/1828 (<strong>Artificial Intelligence Act</strong>) Text with EEA relevance.</a></p> </li> <li><a href="https://eur-lex.europa.eu/eli/reg/2024/2847/oj?locale=en">Regulation (EU) 2024/2847 of the European Parliament and of the Council of 23 October 2024 on horizontal cybersecurity requirements for products with digital elements and amending Regulations (EU) No 168/2013 and (EU) 2019/1020 and Directive (EU) 2020/1828 (<strong>Cyber Resilience Act</strong>) (Text with EEA relevance)</a></li> </ol>
Youth definitions in governmental, philosophical and social science publications
<p>This datasets provides extracted meta data of youth definitions found in governmental, philosophical and social science publications. The definitions are classified according to different schemas and linked with publication resources and other meta data.</p>
Optical Cluster set definitions associated with CERTO project deliverable 4.2
<p>This set of files consists of pickle and csv files that describe the optical water class sets computed as part of the CERTO project ( https://certo-project.org ). A written description and discussion of these clusters is provided in Deliverable 4.2 from the CERTO project.</p>
Molecular Models and Wave Function Definitions for Models A-G of the [2Fe]F Cluster in FeFe-hydrogenase Maturase Enzyme HydF
<p>The dataset contains all relevant atomic positional coordinates for 2Fe-cluster models, and electronic wave function data (using formatted Gaussian checkpoint files) as described in the related publication (see citation below).</p> <p>The version 2.0 contains additional models for [2Fe-2S] cluster linked [2Fe]F constructs.</p> <p>The top folder contains "analysis.xlsx" electronic spreadsheet that summarizes all the numerical results for absolute and relative electronic energy values, internal coordinates, calculated and scaled vibrational frequencies for diatomic stretching modes. The details of developing scaled quantum forcefields as a function of level of theory and model composition are also given.<br> The schematic structural definitions are given in the "models.pdf" file and keys for abbreviations are provided in "symbols.txt" file.<br> </p>
Exported Definitions, References, Document Structure from EU Legislations
<p>A sample corpus of definitions, references, and document structures extracted from the EUR-LEX corpus of EU Legislations.</p>
Compartment and Hub Definitions Tune Metabolic Networks for Metabolomic Interpretations
<p>This archive contains data for a report by the same title.<br> Data relate to software projects MetaboNet and DyMetaboNet.<br> MetaboNet: https://github.com/tcameronwaller/metabonet<br> DyMetaboNet: https://github.com/tcameronwaller/dymetabonet</p> <p>File descriptions</p> <p>dymetabonet_2019-08-29.mp4 ... raw screen capture video of DyMetaboNet<br> dock_metabonet_2019-08-18.zip ... complete MetaboNet export<br> model_* ... curation of human metabolic model by MetaboNet<br> model_dymetabonet.zip ... format for DyMetaboNet<br> model_compartments* ... compartments<br> model_processes* ... processes<br> model_reactions* ... reactions<br> model_metabolites* ... metabolites<br> measurement_* ... curation of metabolomic measurements by MetaboNet<br> measurement_study_*_report.tsv ... summary of match measurements to metabolites<br> measurement_study_*.tsv ... metabolites' fold changes and probabilities between groups<br> measurement_study_*_metaboanalyst.txt ... format for MetaboAnalyst<br> measurement_study_*_metaboanalyst_pair.txt ... format for MetaboAnalyst with sample pairs<br> network_* ... multiple definitions of metabolic networks<br> network_compartments-true_hubs-true.zip ... compartmental network with hubs<br> network_compartments-true_hubs-false.zip ... compartmental network without hubs<br> network_compartments-false_hubs-true.zip ... noncompartmental network with hubs<br> network_compartments-false_hubs-false.zip ... noncompartmental network without hubs<br> network_compartments-*_hubs_*/network_cytoscape.json ... format for Cytoscape<br> network_compartments-*_hubs_*/network_networkx.pickle ... format for NetworkX<br> network_compartments-*_hubs_*/nodes_reactions.pickle ... network's nodes for reactions<br> network_compartments-*_hubs_*/nodes_metabolites.pickle ... network's nodes for metabolites<br> network_compartments-*_hubs_*/links.pickle ... network's links<br> network_compartments-*_hubs_*/analysis/nodes_reactions.tsv ... nodes' metrics relative to reactions<br> network_compartments-*_hubs_*/analysis/nodes_metabolites.tsv ... nodes' metrics relative to metabolites<br> network_compartments-*_hubs_*/analysis/network_reactions.tsv ... network's metrics relative to reactions<br> network_compartments-*_hubs_*/analysis/network_metabolites.tsv ... network's metrics relative to metabolites<br> network_compartments-*_hubs_*/measurement/metabolites.tsv ... measurements on nodes for metabolites</p>
Supporting information of a study for the definition and evaluation of a graphical user interface for housing co-design
<p>This dataset is from a study that intends to define, prototype and test a graphical user interface for a housing co-design system. To define the requirements of the interface, we conducted interviews with professionals of architecture, urbanism and social sciences areas, as well as with housing cooperatives and inhabitants of these institutions. An interface solution was prototyped, tested and refined. Then we conducted a heuristic evaluation and a summative evaluation. Such evaluations involved the testing of a high-fidelity prototype, to receive feedback from UX/UI experts, potential users (inhabitants) and architects.</p> <p>S1_File refers to the interview protocol used with the three groups of interviewees. We share the English and Portuguese versions of the interviews with professionals and the original (Portuguese) and translated versions of the remaining ones since these were conducted in Portuguese.</p> <p>S2_File is a dataset reporting the results of the interviews. Each question includes the answers given and the identification (anonymized) of the interviewees who responded to that question.</p> <p>S3_File describes the usability issues identified by the experts during the heuristic evaluation of the high-fidelity prototype. The first page organizes the issues by severity (left) and priority (right). The remaining pages have a table for each issue, including rows for problem designation, heuristic violated, problem description, solution proposal, severity degree, and an image of the interface pointing to the referred issue.</p> <p>S4_File refers to the results of the heuristic evaluation. It includes the identification of each issue, which expert (anonymized) identified such issue, and the heuristic it violates, with the sum of the times each heuristic was violated at the end of each column. At the right, a table presents the consolidation of issues, organized by priority, with columns identifying the issue, severity level, frequency, and priority.</p> <p>S5_File is the script given to potential users to experiment with the interface during the summative evaluation. This script guides the user through the tasks to perform since the prototype does not have all the features functioning.</p> <p>S6_File refers to the questionnaires applied during the summative evaluation with inhabitants. It includes a preliminary questionnaire, a Single Ease Question (SEQ) questionnaire, a System Usability Scale (SUS) questionnaire, and a Graphical User Interface (GUI) questionnaire.</p> <p>S7_File refers to the results of the summative evaluation with inhabitants (potential users).</p> <ul> <li>Page A refers to the preliminary questionnaire with demographic information such as age, gender, education, relationship with digital technologies, etc. Each field corresponds with each inhabitant (anonymised) and the sum and percentage. In the middle, a table presents a summary of the consolidation. In the right possible relations are presented. </li> <li>Page B presents the results of the SEQ questionnaire, identifying the ratings each inhabitant (anonymized) gave each task. A summary of such values is at the right. </li> <li>On page C, the result of each rating for the SUS questionnaire given by each inhabitant (anonymized) is shown. At the bottom is the calculation of the SUS score.</li> <li>Page D presents the GUI questionnaire results for each inhabitant (anonymized), with the average and SD identified for each question. A summary of such results is on the right.</li> <li>Page E holds the notes taken by the researchers based on their observations regarding task performance. The information is organized in tables for each step of each task and includes the completeness, attempts, and time taken for each inhabitant (anonymized) to complete such task. Also, the sum, percentage, average, and SD are registered. Next to each task is a table identifying how many participants accomplished the task at the first attempt.</li> <li>Page F refers to the strong and weak aspects identified by the inhabitants. Strong and weak aspects are identified, as well as which inhabitant (anonymized) has identified them. The sum and percentage are also given. At the right, there is a table with the consolidation of results by combining similar answers. </li> </ul> <p>S8_File refers to the results of the discussion with architects after experiencing the interface. Such results relate to the positive and negative aspects that the architects identified in the interface and its usefulness for architecture. The left table identifies the strong and weak aspects that architects (anonymized) identified and the sum and percentage associated with them. The table on the right consolidates such results, with similar responses combined.</p>
Improvement of regulations interpretation and formalisation for information need definition - Municipality of Ascoli Piceno, Italy
<p>CHEK Digital Building Permit Maturity Model (CDBPMM) as developed within the HORIZON EUROPE project 'Change toolkit for Digital Building Permit'.</p> <p>(CHEK) https://chekdbp.eu </p> <p>It is described in the CHEK project deliverable D2.1.</p> <p>This project has received funding from the European Union's Horizon Europe program under Grant Agreement No.101058559.</p> <p>The aim of CHEK is to remove barriers preventing municipalities from adopting digital building permit processes by developing, connecting, and aligning scalable solutions in the regulatory and policy context, in open standards and interoperability (geospatial and BIM), in closing knowledge gaps through education, in renewing municipal processes, and in deploying technology. </p>
SERENA Task 1.4 – Definition of scenarios - Survey results
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</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.