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23,670 results for “Site”
Coastal Forest Aboveground Biomass Data at six sites in the Chesapeake Bay and Delaware Bay region, 2021
This dataset contains aboveground biomass measurement and vegetation inventory of 17 coastal forest sites collected during June 1-8 of 2021 across Virginia (n = 6 in Goodwin Island and Phillips Creek), Maryland (n = 4, Monie Bay and Moneystump Swamp) and Delaware (n = 7, Milford Neck and Donas landing). The aboveground biomass was computed with allometric equations and all study sites were located within a narrow elevation range of 0-5m above sea level.
A Comprehensive Study of the Microclimate-Induced Conservation Risks in Hypogeal Sites: The Mithraeum of the Baths of Caracalla (Rome)
<p>The peculiar microclimate inside cultural hypogeal sites needs to be carefully investigated. This study presents a methodology that aimed at providing a user-friendly assessment of the frequently occurring hazards in such sites. A Risk Index was specifically defined as the percentage of time for which the hygrothermal values lie in ranges that are considered to be hazardous for conservation. An environmental monitoring campaign that was conducted over the past ten years inside the Mithraeum of the Baths of Caracalla (Rome) allowed for us to study the deterioration before and after a maintenance intervention. The general microclimate assessment and the specific conservation risk assessment were both carried out. The former made it possible to investigate the influence of the outdoor weather conditions on the indoor climate and estimate condensation and evaporation responsible for salts crystallisation/dissolution and bio-colonisation. The latter took hygrothermal conditions that were close to wall surfaces to analyse the data distribution on diagrams with critical curves of deliquescence salts, mould germination, and growth. The intervention mitigated the risk of efflorescence thanks to reduced evaporation, while promoting the risk of bioproliferation due to increased condensation. The Risk Index provided a quantitative measure of the individual risks and their synergism towards a more comprehensive understanding of the microclimate-induced risks.</p>
Sample of HYPERNETS Hyperspectral Surface Reflectance Measurements for Satellite Validation from the Gobabeb Site in Namibia
<p>The HYPERNETS project (www.hypernets.eu; Ruddick et al. 2024) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical satellite products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu; Kuusk et al. 2024) dedicated to land and water surface reflectance validation with instrument pointing capabilities. This instrument has been deployed over various sites covering a range of water and land types and a range of climatic and logistic conditions. Here, we provide the first fully quality-checked data for the Gobabeb HYPERNETS site in Namibia (GHNA). The HYPERNETS data products were processed using the HYPERNETS_processor (De Vis et al. 2024b).</p> <p>The provided NetCDF files are the L2B hypernets products with surface reflectances, their associated uncertainties and error-correlation information. The reflectance in these products is the Hemispherical-conical Reflectance Factor (HCRF) defined as: HCRF = π L / E where L is the conical upwelling radiance (with field of view of 5 degrees) and E is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance). These reflectances have dimensions of wavelength and series, where each series is a set of measurements for a given geometry (combination of viewing zenith and azimuth angle). In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, number of valid scans used, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.</p> <p>The GHNA site has minimal daily variation in surface cover and weather conditions and is an ideal location for sustained, homogeneous measurements. The site is well characterised as it is very close to an instrument already recognised as a radiometric calibration site (GONA) as part of the RadCalNet network (Bialek et al. 2016). The HYPERNETS site itself (23.60153 degrees S, 15.12589 degrees E) is 650 m from the RadCalNet site, and is located on a gravel plain near a dry riverbed which separates it from the neighbouring dune sea. The HYPSTAR®-XR sensor was installed May 2022 at the top of a 9m mast on an extended 1 m horizontal boom to minimise interruption of the field of view. Data are collected every 30 minutes between 9am and 6pm local time (UTC+02) between viewing zenith angles of 0 and 60 degrees. No measurements are taken at 2pm and 2:30pm local time to avoid the hottest part of the day.</p> <p>The HYPSTAR®-XR (eXtended Range) instruments deployed at each land HYPERNETS site consist of a VNIR and a SWIR sensor and autonomously collect data between 380-1700 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm and the SWIR sensor has 220 channels between 1000 and 1700 nm with a FWHM of 10 nm. The hypernets_processor (De Vis et al. 2024b) automatically processes all this data into various products, including the L2A surface reflectance product provided here. All of the products have associated uncertainties (divided into random and systematic uncertainties, including error-correlation information) which were propagated using the CoMet toolkit (www.comet-toolkit.org). For an example using these data for satellite vicarious calibration, see De Vis et al. 2024a).</p> <p>To obtain this dataset, we start from the full GHNA data record and omit data that does not pass the relevant quality checks (QC). Some QC are performed during the near-real time processing done by the hypernets_processor (see https://hypernets-processor.readthedocs.io/en/latest/content/atbd/processing/quality_checks.html) to produce the L2A files. Then, a number of site-specific QC are performed as post-processing to produce the L2B files. These site-specific QC cover things such as removing flags in the L2A data, avoiding periods with bad deployment conditions, removing unsuitable viewing and solar angles, as well as poorly performing wavelength ranges and individual sequences. Any potential misalignment of the sensor is also corrected, affecting L1D irradiances, and L2B reflectances. These corrected data are then used in a more stringent clear sky check, and in a check that verifies the reflectances are within realistic ranges for a given angle and time of year for the given site. </p> <p>There was a rain event in Gobabeb in March 2025, resulting in the growth of grass at the site. We expect the site will be back to its normal surface cover in the near future. Since the rain event, less data passed the site-specific QC. A dedicated QC will be developed for this period, as the data with grass surface cover will still be useful for satellite validation. These updated data will be made available in the future. </p>
Cuneiform Inscriptions Geographical Site Index (CIGS)
<p>The <em>Cuneiform Inscriptions Geographial Site</em> (CIGS) index contains a basic set of primary spatial, toponym, attribute, and external link information on close to 600 archaeological locations where texts written in cuneiform and derived scripts have been found. In use across the wider Middle East from c. 3,400 BCE until 100 CE, cuneiform is one of the earliest and most extensively documented ancient scripts in world history. This resource has been prepared by researchers of the Department of Linguistics and Philology of Uppsala University. The index is intended as a tool for students and researchers in cuneiform studies and related areas and as an aid to cultural heritage managers and educators in communicating and safeguarding this unique body of world written heritage. The index remains under development and is regularly updated. The authors will very much appreciate notices of any omissions, errors, or inaccuracies. For any inquiries, please contact <a href="https://www.katalog.uu.se/profile/?id=N18-1120">Rune Rattenborg</a> (<a href="mailto:rune.rattenborg@lingfil.uu.se">rune.rattenborg@lingfil.uu.se</a>). For further details, see <a href="https://cdli.ucla.edu/pubs/cdlj/2021/cdlj2021_001.html">Rattenborg et al. 2021</a>.</p> <p>The version 1.7 index contains 598 entries with a total twenty-six fields, including one primary ID, one integer field for accuracy, twenty-two string fields with toponyms and links, and two spatial data fields. Coordinates given use the WGS 1984 geographic coordinate reference system (<a href="https://epsg.io/4326">EPSG 4326</a>) and have been truncated to four decimal digits. Site locations have been traced from archaeological gazetteers and web mapping services (e.g. <a href="https://pleiades.stoa.org/">Pleiades</a>, <a href="https://www.geonames.org/">GeoNames</a> and <a href="https://www.openstreetmap.org/">OpenStreetMap</a>) and digitally generated from optical recognition using current and legacy satellite imagery datasets in QGIS 3.x.</p> <p>The version 1.7 data set is updated to correlate with archaeological locations included in the <a href="https://cdli.mpiwg-berlin.mpg.de">Cuneiform Digital Library Initiative</a> table of proveniences (see <a href="https://cdli.mpiwg-berlin.mpg.de/proveniences">https://cdli.mpiwg-berlin.mpg.de/proveniences</a>), migrated July 2023. Please see this resource for later updates to individual records.</p>
Improving the Developer Experience with a Low-Code ProcessModelling Language: Companion site
<p>This companion site contains additional data to complement the paper:</p> <p><em><strong>Henriques, H., Lourenço, H., Amaral, V., and Goulão, M. (2018). Improving the developer experience with a low-code process </strong></em><em><strong>modelling</strong></em><em><strong> language. In ACM/IEEE 21st International Conference on Model Driven Engineering Languages and Systems (MODELS 2018), Copenhagen, Denmark. ACM. https://doi.org/10.1145/3239372.3239387</strong></em></p> <p><strong>Abstract</strong></p> <p><strong>Context</strong><strong>: </strong>The OutSystems Platform is a development environment composed of several DSLs, used to specify, quickly build and validate web and mobile applications. The DSLs allow users to model different perspectives such as interfaces and data models, define custom business logic and construct process models.</p> <p><strong>Problem</strong><strong>: </strong>TheDSL for process modelling (Business Process Technology (BPT)), has a low adoption rate and is perceived as having usability problems hampering its adoption. This is problematic given the language maintenance costs.</p> <p><strong>Method:</strong> We used a combination of interviews, a critical review of BPT using the “Physics of Notation” and empirical evaluations of BPT using the System Usability Scale (SUS)and the NASA Task Load indeX (TLX), to develop a new version ofBPT, taking these inputs and Outsystems’ engineers culture into account.</p> <p><strong>Results: </strong>Evaluations conducted with 25 professional soft-ware engineers showed an increase of the semantic transparency on the new version, from 31% to 69%, an increase in the correctness of responses, from 51% to 89%, an increase in the SUS score, from 42.25 to 64.78, and a decrease of the TLX score, from 36.50 to 20.78. These differences were statistically significant.</p> <p><strong>Conclusions:</strong> These results suggest the new version of BPT significantly improved the developer experience of the previous version. The end users background with OutSystems had a relevant impact on the final concrete syntax choices and achieved usability indicators.</p> <p> </p> <p><strong>Contents</strong></p> <p>This companion site provides a permanent link for additional data to the supported paper.</p> <p>This repository includes:</p> <ul> <li>Surveys and Questionnaires used in the evaluation reported in the paper <ul> <li>Survey on OutSystems BPT notations (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/survey.pdf">survey.pdf</a>)</li> <li>Prototype Symbol Set Questionnaire (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/PrototypeSymbolSetQuestionnaire.pdf">PrototypeSymbolSetQuestionnaire.pdf</a>)</li> <li>Original BPT Evaluation (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/languages.png">languages.png</a>)</li> <li>Usability Evaluation (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/sus.png">sus.png</a>)</li> <li>Cognitive Effort Evaluation (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/tlx.png">tlx.png</a>)</li> <li>Testing environment screenshot (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/Testing%20Environment%20Screenshot.png">Testing Environment Screenshot</a>)</li> </ul> </li> <li>Statistics <ul> <li>SUS and NASA TLX <ul> <li>Descriptive statistics (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/SUSTLXDescriptiveStats.pdf">SUSTLXDescriptiveStats.pdf</a>)</li> <li>Normality tests (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/SUSTLXNormalityTests.pdf">SUSTLXNormality.pdf</a>)</li> <li>Correlation test (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/SUSTLXCorrelation.pdf">SUSTLXCorrelation.pdf</a>)</li> <li>Scatterplot (<a href="https://zenodo.org/api/files/68bdc7fa-684a-496d-ab63-d956271f1f7d/SUSTLXScatterPlot.pdf">SUSTLXScatterplot.pdf</a>)</li> </ul> </li> </ul> </li> </ul> <p> </p>
LTER-Italy site Lake Iseo figure
<p>Geographical representation of the LTER-Italy site Lake Iseo (LTER_EU_IT_102) - DEIMS-ID <a href="https://deims.org/0667dab1-f857-45a1-b01b-4261e6a499bd">https://deims.org/0667dab1-f857-45a1-b01b-4261e6a499bd</a></p>
LTER-Italy site Saldur River Catchment figure
<p>Geographical representation of the LTER-Italy site Saldur River Catchment (LTER_EU_IT_099) - DEIMS-ID <a href="https://deims.org/97ff6180-e5d1-45f2-a559-8a7872eb26b1">https://deims.org/97ff6180-e5d1-45f2-a559-8a7872eb26b1</a></p>
LTER-Italy site Mar Piccolo of Taranto figure
<p>Geographical representation of the LTER-Italy site Mar Piccolo of Taranto (LTER_EU_IT_095) - DEIMS-ID <a href="https://deims.org/ede24c6e-9cf2-4cf8-8bf7-36ba327403b4">https://deims.org/ede24c6e-9cf2-4cf8-8bf7-36ba327403b4</a></p>
LTER-Italy site Lago Braies figure
<p>Geographical representation of the LTER-Italy site Lago Braies (LTER_EU_IT_092) - DEIMS-ID <a href="https://deims.org/c54a2c21-2079-400d-b169-5e2de8dfdf06">https://deims.org/c54a2c21-2079-400d-b169-5e2de8dfdf06</a></p>
LTER-Italy site Lago di Tovel figure
<p>Geographical representation of the LTER-Italy site Lago di Tovel (LTER_EU_IT_090) - DEIMS-ID <a href="https://deims.org/f3146959-ae18-4b4e-a9be-16634b0b530a">https://deims.org/f3146959-ae18-4b4e-a9be-16634b0b530a</a></p>
LTER-Italy site Lago Paione Superiore figure
<p>Geographical representation of the LTER-Italy site Lago Paione Superiore (LTER_EU_IT_089) - DEIMS-ID <a href="https://deims.org/7e5837a9-ee27-4e27-822a-f50e5217c313">https://deims.org/7e5837a9-ee27-4e27-822a-f50e5217c313</a></p>
LTER-Italy site Lago Paione Inferiore figure
<p>Geographical representation of the LTER-Italy site Lago Paione Inferiore (LTER_EU_IT_088) - DEIMS-ID <a href="https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f">https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f</a></p>
LTER-Italy site Valbona figure
<p>Geographical representation of the LTER-Italy site Valbona (LTER_EU_IT_085) - DEIMS-ID <a href="https://deims.org/2b587e26-4550-4841-a032-ab3c93ced8a0">https://deims.org/2b587e26-4550-4841-a032-ab3c93ced8a0</a></p>
LTER-Italy site Monumento Naturale Torre Flavia (Roma) figure
<p>Geographical representation of the LTER-Italy site Monumento Naturale Torre Flavia (Roma) (LTER_EU_IT_083) - DEIMS-ID <a href="https://deims.org/e618c7ca-2b92-46cb-9156-d87336c5a81f">https://deims.org/e618c7ca-2b92-46cb-9156-d87336c5a81f</a></p>
LTER-Italy site Foce Trigno-Marina di Petacciato (Campobasso) figure
<p>Geographical representation of the LTER-Italy site Foce Trigno-Marina di Petacciato (Campobasso) (LTER_EU_IT_081) - DEIMS-ID <a href="https://deims.org/1835cda2-b56d-400a-b413-ab5c74086dc5">https://deims.org/1835cda2-b56d-400a-b413-ab5c74086dc5</a></p>
LTER-Italy site Foce Saccione-Bonifica Ramitelli (Campobasso) figure
<p>Geographical representation of the LTER-Italy site Foce Saccione-Bonifica Ramitelli (Campobasso) (LTER_EU_IT_080) - DEIMS-ID <a href="https://deims.org/088fe3af-c5bb-4cc8-b479-fe1ea6d5be80">https://deims.org/088fe3af-c5bb-4cc8-b479-fe1ea6d5be80</a></p>
LTER-Italy site Saldur river figure
<p>Geographical representation of the LTER-Italy site Saldur river (LTER_EU_IT_100) - DEIMS-ID <a href="https://deims.org/7f479263-8f0b-447e-a33d-e08723c86184">https://deims.org/7f479263-8f0b-447e-a33d-e08723c86184</a></p>
LTER-Italy site Matsch-Mazia proglacial area figure
<p>Geographical representation of the LTER-Italy site Matsch-Mazia proglacial area (LTER_EU_IT_101) - DEIMS-ID <a href="https://deims.org/80c56aed-48bc-4d00-9ac0-033effeab9d2">https://deims.org/80c56aed-48bc-4d00-9ac0-033effeab9d2</a></p>
LTER-Italy site Comune di Torgnon (Tronchaney) figure
<p>Geographical representation of the LTER-Italy site Comune di Torgnon (Tronchaney) (LTER_EU_IT_078) - DEIMS-ID <a href="https://deims.org/4312983f-c36a-4b46-b10a-a9dea2172849">https://deims.org/4312983f-c36a-4b46-b10a-a9dea2172849</a></p>
LTER-Italy site Comune di Torgnon (Tellinod) figure
<p>Geographical representation of the LTER-Italy site Comune di Torgnon (Tellinod) (LTER_EU_IT_077) - DEIMS-ID <a href="https://deims.org/a03ef869-aa6f-49cf-8e86-f791ee482ca9">https://deims.org/a03ef869-aa6f-49cf-8e86-f791ee482ca9</a></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.