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Found 35 result(s)
<<< openresearchdata.ch has been discontinued !!! >>> Openresearchdata.ch (ORD@CH) has been developed as a publication platform for open research data in Switzerland. It currently offers a metadata catalogue of the data available at the participating institutions (ETH Zurich Scientific IT Services, FORS Lausanne, Digital Humanities Lab at the University of Basel). In addition, metadata from other institutions is continuously added, with the goal to develop a comprehensive metadata infrastructure for open research data in Switzerland. The ORD@CH project is part of the program „Scientific information: access, processing and safeguarding“, initiated by the Rectors’ Conference of Swiss Universities (Program SUC 2013-2016 P-2). The portal is currently hosted and developed by ETH Zurich Scientific IT Services.
Climate Data Record (CDR) is a time series of measurements of sufficient length, consistency and continuity to determine climate variability and change. The fundamental CDRs include sensor data, such as calibrated radiances and brightness temperatures, that scientists have improved and quality-controlled along with the data used to calibrate them. The thematic CDRs include geophysical variables derived from the fundamental CDRs, such as sea surface temperature and sea ice concentration, and they are specific to various disciplines.
The Global Hydrology Resource Center (GHRC) provides both historical and current Earth science data, information, and products from satellite, airborne, and surface-based instruments. GHRC acquires basic data streams and produces derived products from many instruments spread across a variety of instrument platforms.
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AUSSDA - The Austrian Social Science Data Archive is a certified, national research infrastructure for the social science community. We offer sustainable and easy-to-use services in the field of digital archiving and preservation. The main beneficiaries are researchers, students, educational institutions and media professionals. We implement international standards to make research data findable, accessible, interoperable and reusable according to the FAIR principles. AUSSDA supports the open science movement to maximize the potential for data reuse. We stand for integrity in archiving and advocate for compliance with data protection and ethical principles in research data management. AUSSDA represents Austria as a national service provider in CESSDA ERIC, has locations at the universities of Vienna, Graz, Linz, Innsbruck, Krems and at the OeAW (Austrian Academy of Sciences) and works within a network of national and international partners.
OLOS is a Swiss-based data management portal tailored for researchers and institutions. Powerful yet easy to use, OLOS works with most tools and formats across all scientific disciplines to help researchers safely manage, publish and preserve their data. The solution was developed as part of a larger project focusing on Data Life Cycle Management (dlcm.ch) that aims to develop various services for research data management. Thanks to its highly modular architecture, OLOS can be adapted both to small institutions that need a "turnkey" solution and to larger ones that can rely on OLOS to complement what they have already implemented. OLOS is compatible with all formats in use in the different scientific disciplines and is based on modern technology that interconnects with researchers' environments (such as Electronic Laboratory Notebooks or Laboratory Information Management Systems).
Specification Patterns is an online repository for information about property specification for finite-state verification. The intent of this repository is to collect patterns that occur commonly in the specification of concurrent and reactive systems.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
The University of Pittsburgh English Language Institute Corpus (PELIC) is a 4.2-million-word learner corpus of written texts. These texts were collected in an English for Academic Purposes (EAP) context over seven years in the University of Pittsburgh’s Intensive English Program, and were produced by over 1100 students with a wide range of linguistic backgrounds and proficiency levels. PELIC is longitudinal, offering greater opportunities for tracking development in a natural classroom setting.
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The Austrian NeuroCloud (ANC) is a FAIR-enabling platform for sustainable research data management in Cognitive Neuroscience. Most of the offered research data is restricted, the publicly available datasets can be seen under https://data.anc.plus.ac.at/explore The ANC offers tools and services to archive, manage, and share neurocognitive data flexibly and according to community standards. Scientists have full control over what they share (e.g., full original datasets or data derivatives), how they share it (by choosing from a selection of licensing models), and with whom (e.g., by using the ANC’s adjustable User Agreement templates). The ANC provides persistent DOIs for data releases and operates in accordance with European GDPR. Moreover, the ANC fully supports the mission of the EOSC and is committed to the EU’s open science policy, legal standards, and best open science practices. Accordingly, the ANC aspires to facilitate FAIR data operations along the entire data lifecycle, actively supporting the ongoing shift in research culture towards increased transparency, data reusability, and result reproducibility.
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DataverseNO is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
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GFZ Data Services is a repository for research data and scientific software across the Earth System Sciences, hosted at GFZ. The curated data are archived, persistently accessible and published with digital object identifier (DOI). They range from large dynamic datasets from global monitoring networks with real-time aquisition, to international services in geodesy and geophysics, to the full suite of small and highly heterogeneous datasets collected by individual researchers or small teams ("long-tail data"). In addition to the DOI registration and data archiving itself, GFZ Data Services team offers comprehensive consultation by domain scientists and IT specialists. Among others, GFZ Data Services is data publisher for the IAG Services ICGEM, IGETS and ISG (IAG = Int. Association for Geodesy; ICGEM = Int. Center for Global Earth Models; IGETS = Int. Geodynamics and Earth Tide Service; ISG = Int. Service for the Geoid), the World Stress Map, INTERMAGNET, GEOFON, the Geophysical Instrument Pool Potsdam GIPP, TERENO, EnMAP Flight Campaigns, the Potsdam Institute for Climate Impact Research PIK, the Specialised Information Service for Solid Earth Geosciences (FID GEO) and hosts the GFZ Catalogue for the International Generic Sample Number IGSN.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
Atmosphere to Electrons (A2e) is a new, multi-year, multi-stakeholder U.S. Department of Energy (DOE) research and development initiative tasked with improving wind plant performance and mitigating risk and uncertainty to achieve substantial reduction in the cost of wind energy production. The A2e strategic vision will enable a new generation of wind plant technology, in which smart wind plants are designed to achieve optimized performance stemming from more complete knowledge of the inflow wind resource and complex flow through the wind plant.
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CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R. R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult the R project homepage for further information.
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RADAR4Culture is a low-threshold and easy-to use service for sustainable publication and preservation of cultural heritage research data. It offers free publication for any data type and format according to the FAIR principles, independent of the researcher´s institutional affiliation. Through persistent identifiers (DOI) and a guaranteed retention period of at least 25 years, the research data remain available, citable and findable long-term. Currently, the offer is aimed exclusively at researchers at publicly funded research institutions and (art) universities as well as non-commercial academies, galleries, libraries, archives and museums in Germany. No contract is required and no data publication fees are charged. The researchers are responsible for the upload, organisation, annotation and curation of research data as well as the peer-review process (as an optional step) and finally their publication.
Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
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The interdisciplinary data platform INPTDAT provides easy access to research data and information from all fields of applied plasma physics and plasma medicine. It aims to support the findability, accessibility, interoperability and re-use of data for the low-temperature plasma physics community.
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<<<!!!<<<This is the original site of the JAE Data Archive, which was hosted by a server belonging to the Economics Department of Queen's University from its origin in 1994 until late 2022. This site has been replaced by a new one, which contains all the data from this site plus data for all papers accepted after late 2022: https://www.re3data.org/repository/r3d100010130 >>>!!!>>> The JAE Data Archive, which is hosted by a server belonging to the Economics Department of Queen's University, contains data for all papers accepted after January, 1994, unless the data are confidential. There are also data for a few papers accepted earlier. Volume 10, No. 1 (1995) is the first issue in which all papers were accepted subject to the proviso that data be provided. For some papers, especially more recent ones, the Data Archive also contains programs and supplementary material, such as technical appendices and additional graphs.
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The SABIO-RK is a web-based application based on the SABIO relational database that contains information about biochemical reactions, their kinetic equations with their parameters, and the experimental conditions under which these parameters were measured. It aims to support modellers in the setting-up of models of biochemical networks, but it is also useful for experimentalists or researchers with interest in biochemical reactions and their kinetics. All the data are manually curated and annotated by biological experts, supported by automated consistency checks.
The main goal of the CLUES-project is to provide constrained simulations of the local universe designed to be used as a numerical laboratory of the current paradigm. The simulations will be used for unprecedented analysis of the complex dark matter and gasdynamical processes which govern the formation of galaxies. The predictions of these experiments can be easily compared with the detailed observations of our galactic neighborhood. Some of the CLUES data is now publicly available via the CosmoSim database (https://www.cosmosim.org/). This includes AHF halo catalogues from the Box 64, WMAP3 resimulations of the Local Group with 40963 particle resolution.