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Found 15 result(s)
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.
It is a platform for supporting Open Data initiative of Government of Odisha, intends to publish datasets collected by them for public use. It also supports widely used file formats that are suitable for machine processing, thus gives avenues for many more innovative uses of Government Data in different perspective. This portal has been created under Software as A Service (SaaS) model of Open Government Data (OGD) Platform India of NIC. The data available in the portal are owned by various Departments/Organization of Government of Odisha. It follows principles on which data sharing and accessibility need to be based include: Openness, Flexibility, Transparency, Quality, Security and Machine-readable.
The Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) is a team of researchers, data specialists and computer system developers who are supporting the development of a data management system to store scientific data generated by Gulf of Mexico researchers. The Master Research Agreement between BP and the Gulf of Mexico Alliance that established the Gulf of Mexico Research Initiative (GoMRI) included provisions that all data collected or generated through the agreement must be made available to the public. The Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) is the vehicle through which GoMRI is fulfilling this requirement. The mission of GRIIDC is to ensure a data and information legacy that promotes continual scientific discovery and public awareness of the Gulf of Mexico Ecosystem.
The Social Science Data Archive is still active and maintained as part of the UCLA Library Data Science Center. SSDA Dataverse is one of the archiving opportunities of SSDA, the others are: Data can be archived by SSDA itself or by ICPSR or by UCLA Library or by California Digital Library. The Social Science Data Archives serves the UCLA campus as an archive of faculty and graduate student survey research. We provide long term storage of data files and documentation. We ensure that the data are useable in the future by migrating files to new operating systems. We follow government standards and archival best practices. The mission of the Social Science Data Archive has been and continues to be to provide a foundation for social science research with faculty support throughout an entire research project involving original data collection or the reuse of publicly available studies. Data Archive staff and researchers work as partners throughout all stages of the research process, beginning when a hypothesis or area of study is being developed, during grant and funding activities, while data collection and/or analysis is ongoing, and finally in long term preservation of research results. Our role is to provide a collaborative environment where the focus is on understanding the nature and scope of research approach and management of research output throughout the entire life cycle of the project. Instructional support, especially support that links research with instruction is also a mainstay of operations.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
The DesignSafe Data Depot Repository (DDR) is the platform for curation and publication of datasets generated in the course of natural hazards research. The DDR is an open access data repository that enables data producers to safely store, share, organize, and describe research data, towards permanent publication, distribution, and impact evaluation. The DDR allows data consumers to discover, search for, access, and reuse published data in an effort to accelerate research discovery. It is a component of the DesignSafe cyberinfrastructure, which represents a comprehensive research environment that provides cloud-based tools to manage, analyze, curate, and publish critical data for research to understand the impacts of natural hazards. DesignSafe is part of the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI), and aligns with its mission to provide the natural hazards research community with open access, shared-use scholarship, education, and community resources aimed at supporting civil and social infrastructure prior to, during, and following natural disasters. It serves a broad national and international audience of natural hazard researchers (both engineers and social scientists), students, practitioners, policy makers, as well as the general public. It has been in operation since 2016, and also provides access to legacy data dating from about 2005. These legacy data were generated as part of the NSF-supported Network for Earthquake Engineering Simulation (NEES), a predecessor to NHERI. Legacy data and metadata belonging to NEES were transferred to the DDR for continuous preservation and access.
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
The African Development Bank Group (AfDB) is committed to supporting statistical development in Africa as a sound basis for designing and managing effective development policies for reducing poverty on the continent. Reliable and timely data is critical to setting goals and targets as well as evaluating project impact. Reliable data constitutes the single most convincing way of getting the people involved in what their leaders and institutions are doing. It also helps them to get involved in the development process, thus giving them a sense of ownership of the entire development process. The AfDB has a large team of researchers who focus on the production of statistical data on economic and social situations. The data produced by the institution’s statistics department constitutes the background information in the Bank’s flagship development publications. Besides its own publication, the AfDB also finances studies in collaboration with its partners. The Statistics Department aims to stand as the primary source of relevant, reliable and timely data on African development processes, starting with the data generated from its current management of the Africa component of the International Comparison Program (ICP-Africa). The Department discharges its responsibilities through two divisions: The Economic and Social Statistics Division (ESTA1); The Statistical Capacity Building Division (ESTA2)
The Cornell Center for Social Sciences (CCSS) houses an extensive collection of research data files in the social sciences with particular emphasis on data that matches the interests of Cornell University researchers. CCSS intentionally uses a broad definition of social sciences in recognition of the interdisciplinary nature of Cornell research. CCSS collects and maintains digital research data files in the social sciences, with a current emphasis on Cornell-based social science research, Results Reproduction packages, and potentially at-risk datasets. Our archive historically has focused on a broad range of social science data, including data on demography, economics and labor, political and social behavior, family life, and health. You can search our holdings or browse studies by subject area.
Data.gov increases the ability of the public to easily find, download, and use datasets that are generated and held by the Federal Government. Data.gov provides descriptions of the Federal datasets (metadata), information about how to access the datasets, and tools that leverage government datasets