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.
36
datasets available to search
ShareScore release 0.9.0
Dataset results
36 results for “building systems”
Sensor deployment to support the integrated energy management system in residential buildings in ReCO2ST LoRa Dataset
<p>LoRa Radio Testing Datasets for preliminary performance tests. These datasets were taken in order to ensure that the LoRa radios were capable of transmitting through concrete and testing various preamble settings of the radio. As per the paper,</p> <p>"Although these testing methodologies were indicative but not exact or perfect, to test in a manner that was qualitative would have been both costly and beyond the scope of the project." </p> <p>These tests were to help us verify feasibility of the chosen LoRa Radio</p>
3D model of antenna system embedded into building envelope for improved cellular signal transmission through load-bearing walls
<p>The purpose of this dataset is to supplement the data presented in our journal publication "Electromagnetic–Thermal Analyses of Distributed Antennas Embedded Into a Load-Bearing Wall" (see <a href="https://ieeexplore.ieee.org/document/10151683">https://ieeexplore.ieee.org/document/10151683</a>).</p> <p>This dataset contains the 3-D discretized model, without the internal numerical mesh, of the unit cell of the spiral antenna system embedded in a load bearing wall. The 3D model is in .STP format (see ISO 10303-21:2016), which can be imported into most commercial computer-aided design (CAD) software. The wall's dielectric properties are calculated using the model described in ITU-R P.2040-2 (<a href="https://www.itu.int/rec/R-REC-P.2040/en">https://www.itu.int/rec/R-REC-P.2040/en</a>, material parameter and calculation model are on pages 22-23). Materials used in the antenna system and their electrical and thermal parameters are given in the file materials.txt</p>
Optimised household consumption profiles through a smart building energy mangement system TABEDE
<p>In the context of the TABEDE project (<a href="https://www.tabede.eu/">https://www.tabede.eu/</a>) several synthetic profiles simulating the consumption and generation of residential buildings, whose appliances were controlled by our proposed Energy Management System (i.e., the TABEDE solution), were simulated. Their construction process was characterised by the following:</p> <ul> <li>Consumption profiles were generated via a bottom-up approach capable of emulating the consumption of individual household appliances. These last ones correspond to the most used appliances in the UK, which were randomly distributed among the buildings based on their average utilisation rate and ownership observed in residential buildings in the country.</li> <li>The physics in terms of heat exchange between neighbouring buildings and the environment were considered, together with the size of the buildings and their physical characteristics. A total of 66 houses and apartments, according to 8 type or building archetypes were created.</li> <li>PV generation profiles were generated according to the meteorological condition of the simulated day.</li> </ul> <p>Together with this, the profiles feature how the TABEDE solution optimised the flexible part of the consumption (i.e., appliances that were controllable by the solution and whose consumption could be shifted in time without sacrificing user comfort) to minimize the electricity bill of the buildings.</p> <p>The information contained in the actual database features the following variables:</p> <ul> <li>TABEDE penetration: percentage of buildings owning the TABEDE solution. Buildings with TABEDE will observe their flexible consumption being optimised.</li> <li>PV penetration: percentage of buildings with a PV system installed on them.</li> <li>Simulation day: one day in summer (19/06/2019) featuring the highest solar radiation of the year, and a day in winter (19/12/2019) with the lowest.</li> <li>Batteries: whether the PV systems is installed alongside household batteries.</li> </ul> <p>Details on the formulation can be found in: <a href="https://urldefense.com/v3/__https:/www.energy-proceedings.org/an-intelligent-infrastructure-for-enabling-demand-response-ready-buildings/__;!!La4veWw!khYBEaeJY85mX5yQUrp0PwoXcg5U10dEdgZ296hONYGyBS5xg91Z8MoDUQy34a4f9Lo$">https://www.energy-proceedings.org/an-intelligent-infrastructure-for-enabling-demand-response-ready-buildings/</a></p>
Measured data and calculations of pilot RES system for a 103-m2 building in Athens, Greece
<p>This dataset contains complete measurements of an energy system for a building in Athens, Greece (temperatures, flow rates, power, solar radiation, etc.). This system includes a vapour compression heat pump, 4 PVT collectors, a virtual BTES (emulated via a tank with controllable temperature) and three water tanks. A winter and summer day are included. The system operated for space cooling and hot water during the summer day and for space heating and hot water during the winter day.</p> <p>An in-house Python code of NCSR Demokritos has been applied to simulate the energy system operation during these two days for validation purposes. The calculated results are also given in this dataset.</p>
Seasonal analysis comparison of three air-cooling systems in terms of thermal comfort, air quality and energy consumption for school buildings in Mediterranean climates
<p>Efficient air-cooling systems for hot climatic conditions, such as Southern Europe, are required in the context of nearly Zero Energy Buildings, nZEB. Innovative air-cooling systems such as regenerative indirect evaporative coolers, RIEC and desiccant regenerative indirect evaporative coolers, DRIEC, can be considered an interesting alternative to direct expansion air-cooling systems, DX. The main aim of the present work was to evaluate the seasonal performance of three air-cooling systems in terms of air quality, thermal comfort and energy consumption in a standard classroom. Several annual energy simulations were carried out to evaluate these indexes for four different climate zones in the Mediterranean area. The simulations were carried out with empirically validated models. The results showed that DRIEC and DX improved by 29.8% and 14.6% over RIEC regarding thermal comfort, for the warmest climatic conditions, Lampedusa and Seville. However, DX showed an energy consumption three and four times higher than DRIEC for these climatic conditions, respectively. RIEC provided the highest percentage of hours with favorable indoor air quality for all climate zones, between 46.3% and 67.5%. Therefore, the air-cooling systems DRIEC and RIEC have a significant potential to reduce energy consumption, achieving the user’s thermal comfort and improving indoor air quality.</p>
Cost and cost distribution of policy-driven investments in decentralized heating systems in residential buildings in Germany - Supplementary material
<p>This repository holds supplementary material for research concerning the <em>Cost and cost distribution of policy-driven investments in decentralized heating systems in residential buildings in Germany</em></p> <p>which was published as a working paper as</p> <p>Czock, Berit, Cordelia Frings, and Fabian Arnold. <em>Cost and cost distribution of policy-driven investments in decentralized heating systems in residential buildings in Germany</em>. No. 2024-4. Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI), 2024.</p> <p>and is available at</p> <p>https://www.ewi.uni-koeln.de/de/publikationen/cost-and-cost-distribution-of-policy-driven-investments-in-decentralized-heating-systems-in-residential-buildings-in-germany/</p> <p>This repository includes the following documents</p> <ol> <li>building list</li> <li>description of technical and economic assumptions</li> <li>detailed description of results</li> </ol> <p>Further material can be made available on request.</p> <p> </p> <p> </p> <div> <p>Cost and cost distribution of policy-driven investments in decentralized heating systems in residential buildings in Germany - Supplementary material Creators Czock, Berit1 © 2024 by Berit Hanna Czock is licensed under <a href="https://creativecommons.org/licenses/by/4.0/?ref=chooser-v1" target="_blank" rel="license noopener noreferrer"> CC BY 4.0 </a></p> </div>
BRAIN Journal-Automatic Anthropometric System Development Using Machine Learning-Figure 6. The result of building a 3D model based on RF and SVM classification with "Important features".
<p>From the chart of figure 6, we found that "Important Features" gave the best 3D model, which fits with the object in the image. The pattern is close to 90% compared with the true size. Apply classification algorithm RF increases the accuracy of the results and reduces computing time for the program. There are many methods for data classifying. One of them is the method of the support vector machine (SVM). The SVM method is represented by Vladimir N. Vapnik (1995) in Support Vector Machines (SVM) - a set of learning algorithms similar with the supervisor has two main tasks: the classification and the regression analysis. In this article we use the method of the SVM classification problem for the size of the human body with 5 classes to compare the performance between SVM methods and Random Forest algorithm. </p>
#nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems
<p>Music recommender systems can offer users personalized and contextualized recommendation and are therefore important for music information retrieval. An increasing number of datasets have been compiled to facilitate research on different topics, such as content-based, context-based or next-song recommendation. However, these topics are usually addressed separately using different datasets, due to the lack of a unified dataset that contains a large variety of feature types such as item features, user contexts, and timestamps. To address this issue, we propose a large-scale benchmark dataset called #nowplaying-RS, which contains 11.6 million music listening events (LEs) of 139K users and 346K tracks collected from Twitter. The dataset comes with a rich set of item content features and user context features, and the timestamps of the LEs. Moreover, some of the user context features imply the cultural origin of the users, and some others—like hashtags—give clues to the emotional state of a user underlying an LE. In this paper, we provide some statistics to give insight into the dataset, and some directions in which the dataset can be used for making music recommendation. We also provide standardized training and test sets for experimentation, and some baseline results obtained by using factorization machines.</p> <p>The dataset contains three files:</p> <ul> <li>user_track_hashtag_timestamp.csv contains basic information about each listening event. For each listening event, we provide an id, the user_id, track_id, hashtag, created_at </li> <li>context_content_features.csv: contains all context and content features. For each listening event, we provide the id of the event, user_id, track_id, artist_id, content features regarding the track mentioned in the event (instrumentalness, liveness, speechiness, danceability, valence, loudness, tempo, acousticness, energy, mode, key) and context features regarding the listening event (coordinates (as geoJSON), place (as geoJSON), geo (as geoJSON), tweet_language, created_at, user_lang, time_zone, entities contained in the tweet).</li> <li>sentiment_values.csv contains sentiment information for hashtags. It contains the hashtag itself and the sentiment values gathered via four different sentiment dictionaries: AFINN, Opinion Lexicon, Sentistrength Lexicon and vader. For each of these dictionaries we list the minimum, maximum, sum and average of all sentiments of the tokens of the hashtag (if available, else we list empty values). However, as most hashtags only consist of a single token, these values are equal in most cases. Please note that the lexica are rather diverse and therefore, are able to resolve very different terms against a score. Hence, the resulting csv is rather sparse. The file contains the following comma-separated values: <hashtag, vader_min, vader_max, vader_sum,vader_avg, afinn_min, afinn_max, afinn_sum, afinn_avg, ol_min, ol_max, ol_sum, ol_avg, ss_min, ss_max, ss_sum, ss_avg >, where we abbreviate all scores gathered over the Opinion Lexicon with the prefix 'ol'. Similarly, 'ss' stands for SentiStrength. </li> </ul> <p>Please also find the training and test-splits for the dataset in this repo. Also, prototypical implementations of a context-aware recommender system based on the dataset can be found at <a href="https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM">https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM</a>.</p> <p>If you make use of this dataset, please cite the following paper where we describe and experiment with the dataset:</p> <p>@inproceedings{smc18,<br> title = {#nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems},<br> author = {Asmita Poddar and Eva Zangerle and Yi-Hsuan Yang},<br> url = {http://mac.citi.sinica.edu.tw/~yang/pub/poddar18smc.pdf},<br> year = {2018},<br> date = {2018-07-04},<br> booktitle = {Proceedings of the 15th Sound & Music Computing Conference},<br> address = {Limassol, Cyprus},<br> note = {code at https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM},<br> tppubtype = {inproceedings}<br> }</p>
Data from: Building on 150 years of knowledge: the freshwater isopod Asellus aquaticus as an integrative eco-evolutionary model system
<p><strong>Introduction</strong></p> <p>This is a literature database with reference information of all papers that use the freshwater isopod <em>Asellus aquaticus</em>; published between the years 1867 and 2020. This database is intended as a starting point for scientists interested in conducting research on and with this organism. The database is currently only available as a single CSV file; future versions may be made available through a more frequently updated SQL database. The database includes specific information about the subject area and content of each paper, as well as bibliographic information. This repository is associated with the paper "Building on 150 years of knowledge: the freshwater isopod<em> Asellus aquaticus</em> as an integrative eco-evolutionary model system", published in Frontiers in Ecology and Evolution.</p> <p><strong>Details on Methods from the electronic supplement:</strong></p> <p>We used the we online search tools of Web of Science (WOS; Clarivate analytics) by searching for the term "asellus aquaticus" in six relevant databases (BIOSIS, CABI, FSTA, Medline, WOS Core Collection and Zoological Records). The database was accessed with a University License (Lund University). We manually downloaded the results and combined them to a single CSV file in Excel (Microsoft). All further processing was done in the statistical programming language R, version 4.0.2 (R Core Team 2020).</p> <p>From the 1238 obtained records we discarded three papers that were published after the year 2020 to work with completed years only. We used the subject areas assigned by WOS to provide an overview of the fields of science in which A. aquaticus has been most studied. Each paper had between one and ten subject areas assigned by WOS (2845 assignments to 1235 papers, meaning 2.3 assignments per paper, on average). To represent these multiple assignments in relation to the actual number of papers per year, we calculated "fractional assignments" by adding up all assignments to a field per year, divided by the total number of assignments in that year, and then multiplied by the number of papers. For example, if there were 12 assignments to "toxicology" in 1993, and 133 assignments in 1993, but only 21 papers published, "toxicology" would get a score of 1.9 papers in 1993 (as calculated by = (12/133)*21). In Figure 1, we represent these "fractional assignments" in the top panel, and the total number of assignments in the lower panel.</p> <p><strong>Caption for figure (1) in publication:</strong></p> <p>FIGURE 1 | Over 150 years of research on and with Asellus aquaticus. The figure summarizes published scientific literature on A. aquaticus. We conducted a quantitative literature survey with the search tools of Web of Science (WOS; Clarivate analytics) by searching for the term "asellus aquaticus" in six databases (i.e., BIOSIS, CABI, FSTA, Medline, WOS Core Collection, and Zoological Records). We found 1235 records, published between 1867 and 2020. (A) The graph shows the number of publications per year within a given subject area, as designated by WOS. (B) The graph shows the total number of publications assigned to a specific subject area. The top 10 fields account for 72.58% of all publications, and are indicated by color coding in A and B (multiple assignments are possible, summing up to 2845 assignments). The inset in B shows a wordcloud with the 100 most used keywords from all A. aquaticus’ publications. Furthermore, we compiled all records with relevant information (e.g., title, keywords, research areas, and abstract) to a single file which is available online. More details can be found in the Supplementary Material.</p>
Outcomes over output: a user-centric approach to building successful systems
<p><strong>Opening Plenary and keynote: Jeff Gothelf: </strong>Outcomes over output: a user-centric approach to building successful systems<br> Chair: <strong>Jessica Lindholm</strong>, Chalmers University of Technology</p> <p> </p>
Carbon emission and NPV data of hydrogen system in transport and building sector
<p>The dataset contains the simulation environment data, including meteorological data, renewable energy system configuration, grid energy structure data, and energy balance data of the hydrogen systems; the comparison on the lifecycle carbon emissions between different vehicles; and results of the building-transportation energy sharing model, including the calculation process and results of net present value and carbon intensity of the hydrogen system.</p>
Data from: Building functional and sustainable pharmacovigilance systems - an analysis of pharmacovigilance development across high-, middle- and low-income countries
<p>Background</p> <p>Pharmacovigilance (PV) is an essential component of health systems. Functional PV systems protect and promote public health by supporting the safe and effective use of medicinal products through the prevention and mitigation of harm. With increased simultaneous introduction of innovative products in high-, middle- and low-income countries, e.g., COVID-19 vaccines, or solely in low- and middle-income countries (LMIC), e.g., malaria vaccines, PV systems in LMIC must be able to detect safety signals and ensure adequate safety surveillance. This research aims to analyse the development of PV systems across high-, middle- and low-income countries and to carve out essential elements for implementing functional and sustainable PV systems in LMIC.</p> <p>Methods</p> <p>A convergent parallel mixed-methods design, consisting of qualitative and quantitative methods was used. Qualitative research consisted of semi-structured interviews. To expand the breadth and range of the study, a quantitative survey was conducted, focusing on the same thematic questions as the semi-structured interviews.</p> <p>Results</p> <p>Twelve key informants from nine countries were interviewed and 52 respondents from 36 countries completed an online questionnaire. Four major themes consisting of 12 categories emerged from the data. Based on these, the following elements essential for building functional and sustainable pharmacovigilance systems in LMIC were identified: understanding the drivers of PV development; adequately resolving core system challenges; implementing an efficient organisational structure and procedures for PV; investing in activities beyond reporting of adverse drug reactions; identifying alternate sources of financing; having a national strategy with a vision and mission for PV; adequately leveraging the health system; and effectively integrating the pharmaceutical sector in the national PV system.</p> <p>Conclusions</p> <p>Findings from this research revealed progress in PV systems in LMIC in the last decade, though significant efforts are still needed to develop these systems to meet global standards. Developing the different areas emerging from this research, which necessitates implementing functional PV structures and processes, adequately leveraging the health system and effectively engaging the pharmaceutical sector, through the mechanisms proposed, would enable a comprehensive progression from basic to stable, functional and thus sustainable PV systems in LMIC.</p>
An IoT System for Smart Building Combining Multiple mmWave FMCW Radars Applied to People Counting
<p>This repository is related with the next paper. Please cite us if this code is useful to you.</p> <p>Barral, V., Dominguez-Bolano, T., Escudero, C. J., & Garcia-Naya, J. A. An IoT System for Smart Building Combining Multiple mmWave FMCW Radars Applied to People Counting.</p> <h2>Python Scripts</h2> <ul> <li><em>count_plot.py</em>: Generates a plot comparing image tracking estimation, radar with DBSCAN, and radar with OPTICS. Use example:</li> </ul> <pre><code>python count_plot.py count_video_full.log count_radar_moving_average_30_optics.log count_radar_moving_average_30_dbscan.log "Video" "Radar with OPTICS" "Radar with DBSCAN" average_count_full_optics_dbscan.pdf </code></pre> <h2>Radar measurements</h2> <ul> <li><em>test_0.bag</em>: FMCW mmWave radar measurements from three IWR6843 devices (ISK and AOP). Is a ROS (Robotic Operative System) log, can be played with <code>rosbag play test_0.bag</code></li> </ul> <h3>Radar people counting logs</h3> <ul> <li> <p><strong>count_radar_moving_average_30_dbscan.log</strong>: radar people counting estimation using a 30 seconds moving average and DBSCAN as clustering algorithm.</p> </li> <li> <p><strong>count_radar_moving_average_30_optics.log</strong>: radar people counting estimation using a 30 seconds moving average and OPTICS as clustering algorithm.</p> </li> </ul> <h2>Image tracking</h2> <h3>Videos</h3> <ul> <li><em>test_0_cam_0_anonymized.mp4</em>: Camera 0 capture.</li> <li><em>test_0_cam_1_anonymized.mp4</em>: Camera 1 capture.</li> </ul> <h3>Image tracking logs</h3> <ul> <li><em>test_0_cam_0_interp.txt</em>: People count in camera 0</li> <li><em>test_0_cam_1_interp.txt</em>: People count in camera 1</li> </ul> <p>The files have the following format:</p> <p>frame_number, track_id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z The coordinates x, y, z are always -1 The bb fields define the bounding box of the detection If multiple people are detected in a frame, there are several lines with that frame_number, but with different track_ids.</p> <h3>Image people counting logs</h3> <ul> <li><strong>count_video_full.log</strong>: image tracking people counting estimation using a 30 seconds moving average.</li> </ul>
An Empirical Study of Textual and Structural Statistical Models for Maven-Based Build Systems
<p>Replication package for the manuscript entitled "An Empirical Study of Textual and Structural Statistical Models for Maven-Based Build Systems". See README.md file for details about how to use the package.</p>
Dataset supporting publication: 'GEOFIT: Ground source heat pump systems for energy efficient building retrofitting'
<p>Dataset supporting publication: Presentation of GEOFIT at the <a href="https://www.hp-summit.de/en">European Heat Pump Summit</a> (2019) </p> <p>Available for download: <a href="https://zenodo.org/record/3901527">GEOFIT Zenodo</a></p> <p>The integration of geothermal systems for heating / cooling solutions in conjunction with heat pump technology is a major challenge, particularly in the case of renovation. In order to find the best solution for the increased flow temperatures compared to a new building for the renovation, various heat pump configurations are evaluated according to energy and economic criteria. A refrigerant with low greenhouse gas potential (GWP) is used as the working medium, e.g. R1234ze (E)) less than 10 used. A favorable refrigeration circuit configuration for high flow temperatures is a twin-circuit system, which essentially consists of two heat pumps with different condensing temperatures and the same evaporation temperatures. An alternative to this is a single-stage configuration with a significantly larger condenser for improved supercooling. Both systems should enable efficient operation when renovating buildings.</p>
Code Review of Build System Specifications: Prevalence, Purposes, Patterns, and Perceptions (Replication Package)
<p>Online appendix for "Code Review of Build System Specifications: Prevalence, Purposes, Patterns, and Perceptions", in the Proceedings of the International Conference on Software Engineering (ICSE), 2023. </p>
A Construction Classification System Database for Understanding Resource Use in Building Construction
<p>Welcome to the Construction Classification System Database for Understanding Resource Use in Buildings.</p> <p>This database provides a novel dataset and a building material data structure to facilitate study of resource use in building design and construction. The ontology developed for this database uses UniFormat (CSI and CSC, 2010) in conjunction with MasterFormat (CSI and CSC, 2016) for organizing and storing the building material data.</p> <p>The dataset was developed by collecting design or construction drawings for the studied buildings and performing material take-offs based on the drawings. The ontology is based on Uniformat and MasterFormat to facilitate interoperability with existing construction management practices, and to suggest a standardized structure for future MI studies. The structure of the database and these guidelines builds on the structure presented by (Heeren & Fishman, 2019).</p> <p>The initial database version is created by the research team supervised by Prof. Shoshanna Saxe at the University of Toronto and published in the journal Scientific Data (Guven et al. 2022) in February 2022 to describe the dataset and the associated methods and details.</p> <p>Thank you for considering contributing to the database. Data contributors must follow the steps detailed below and must ensure that their inputs do not infringe any intellectual property or copyright agreements.</p> <p>References</p> <p>i. CSI and CSC. (2010). UniFormat - A Uniform Classification of Construction Systems and Assemblies. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC).</p> <p><br> ii. CSI and CSC. (2016). MasterFormat Numbers & Titles (pp. 1–186). pp. 1–186. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC).</p> <p><br> iii. Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A. W., and Saxe, S. (2022). “A construction classification system database for understanding resource use in building construction.” Scientific Data, Springer US, 9(1), 42.</p> <p><br> iv. Heeren, N., & Fishman, T. (2019). A database seed for a community-driven material intensity research platform. Scientific Data, 1–10. https://doi.org/10.1038/s41597-019-0021-x</p>
Building and Pilot Testing a Couples-based Smartphone Systems to Address Alcohol Use Disorder
ClinicalTrials.gov study NCT04059549. IPD Sharing: NO. Countries: 1. Publications: 1.
Building functional and sustainable pharmacovigilance systems - an analysis of pharmacovigilance development across high-, middle- and low-income countries
Open the record for dataset details and reuse information.
Data for: How do we measure and increase systems thinking? Comparing self-reported and performative metrics in response to building causal loop models
Open the record for dataset details and reuse information.
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.