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Found 52 result(s)
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
The World Ocean Database (WOD) is a collection of scientifically quality-controlled ocean profile and plankton data that includes measurements of temperature, salinity, oxygen, phosphate, nitrate, silicate, chlorophyll, alkalinity, pH, pCO2, TCO2, Tritium, Δ13Carbon, Δ14Carbon, Δ18Oxygen, Freon, Helium, Δ3Helium, Neon, and plankton. WOD contains all data of "World Data Service Oceanography" (WDS-Oceanography).
<<<!!!<<< This repository is no longer available. >>>!!!>>> The programme "International Oceanographic Data and Information Exchange" (IODE) of the "Intergovernmental Oceanographic Commission" (IOC) of UNESCO was established in 1961. Its purpose is to enhance marine research, exploitation and development, by facilitating the exchange of oceanographic data and information between participating Member States, and by meeting the needs of users for data and information products.
Welcome to the largest bibliographic database dedicated to Economics and available freely on the Internet. This site is part of a large volunteer effort to enhance the free dissemination of research in Economics, RePEc, which includes bibliographic metadata from over 1,800 participating archives, including all the major publishers and research outlets. IDEAS is just one of several services that use RePEc data. Authors are invited to register with RePEc to create an online profile. Then, anyone finding some of your research here can find your latest contact details and a listing of your other research. You will also receive a monthly mailing about the popularity of your works, your ranking and newly found citations. Besides that IDEAS provides software and public accessible data from Federal Reserve Bank.
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
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 UC San Diego Library Digital Collections website gathers two categories of content managed by the Library: library collections (including digitized versions of selected collections covering topics such as art, film, music, history and anthropology) and research data collections (including research data generated by UC San Diego researchers).
The Duke Research Data Repository is a service of the Duke University Libraries that provides curation, access, and preservation of research data produced by the Duke community. Duke's RDR is a discipline agnostic institutional data repository that is intended to preserve and make public data related to the teaching and research mission of Duke University including data linked to a publication, research project, and/or class, as well as supplementary software code and documentation used to provide context for the data.
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.
Strong-motion data of engineering and scientific importance from the United States and other seismically active countries are served through the Center for Engineering Strong Motion Data(CESMD). The CESMD now automatically posts strong-motion data from an increasing number of seismic stations in California within a few minutes following an earthquake as an InternetQuick Report(IQR). As appropriate,IQRs are updated by more comprehensive Internet Data Reports that include reviewed versions of the data and maps showing, for example, the finite fault rupture along with the distribution of recording stations. Automated processing of strong-motion data will be extended to post the strong-motion records of the regional seismic networks of the Advanced National Seismic System (ANSS) outside California.
OEDI is a centralized repository of high-value energy research datasets aggregated from the U.S. Department of Energy’s Programs, Offices, and National Laboratories. Built to enable data discoverability, OEDI facilitates access to a broad network of findings, including the data available in technology-specific catalogs like the Geothermal Data Repository and Marine Hydrokinetic Data Repository.
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 WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
Merritt is a curation repository for the preservation of and access to the digital research data of the ten campus University of California system and external project collaborators. Merritt is supported by the University of California Curation Center (UC3) at the California Digital Library (CDL). While Merritt itself is content agnostic, accepting digital content regardless of domain, format, or structure, it is being used for management of research data, and it forms the basis for a number of domain-specific repositories, such as the ONEShare repository for earth and environmental science and the DataShare repository for life sciences. Merritt provides persistent identifiers, storage replication, fixity audit, complete version history, REST API, a comprehensive metadata catalog for discovery, ATOM-based syndication, and curatorially-defined collections, access control rules, and data use agreements (DUAs). Merritt content upload and download may each be curatorially-designated as public or restricted. Merritt DOIs are provided by UC3's EZID service, which is integrated with DataCite. All DOIs and associated metadata are automatically registered with DataCite and are harvested by Ex Libris PRIMO and Thomson Reuters Data Citation Index (DCI) for high-level discovery. Merritt is also a member node in the DataONE network; curatorially-designated data submitted to Merritt are automatically registered with DataONE for additional replication and federated discovery through the ONEMercury search/browse interface.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.
LibraData is a place for UVA researchers to share data publicly. It is UVA's local instance of Dataverse. LibraData is part of the Libra Scholarly Repository suite of services which includes works of UVA scholarship such as articles, books, theses, and data.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
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.
The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
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.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.