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Found 10 result(s)

SPT Galaxy Cluster Followup Dataverse

South Pole Telescope Galaxy Cluster Followup Dataverse

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Dataverse to host followup observations of galaxy clusters identified in South Pole Telescope SZ Surveys. This includes: 1) GMOS spectroscopy of low to moderate redshift galaxy clusters taken as a part of NOAO Large Survey Program 11A-0034 (PI: Christopher Stubbs).

CSISA Data Repository

Cereal Systems Initiative for South Asia (CSISA) Research Data

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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.

Society of American Archivists Dataverse

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The Society of American Archivists (SAA) Dataverse is an SAA data service that was established to support the needs and interests of SAA’s members and the broader archives community. The SAA Dataverse supports the reuse of datasets for purposes of fostering knowledge, insights, and a deeper understanding of archival organizations, the status of archivists, and the impact of archives and archival work on the broader society. Deposited datasets should be “actionable” in that they should support direct analysis and interpretation. The SAA Dataverse welcomes deposits of collections of quantitative or qualitative data and associated documentation. SAA membership is not required to deposit or use data in the SAA Dataverse.

eSHODHMANTHAN

eSHODHMANTHAN-RDR

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A Research Data Repository (RDR) for researchers in India. Any registered researchers of Indian Universities can manage their research data on eSHODHMANTHAN-RDR free of cost. This research data repository is configured to provide free of cost research data management services to existing and forthcoming researchers throughout their research life. eSHODHMANTHAN-RDR is powered by Dataverse project of Harvard University

George Mason University Dataverse

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The George Mason University Dataverse is available for George Mason faculty, staff, and students to publish, share, and preserve their research data of enduring value. It is a companion to the Mason Archival Repository Service (https://mars.gmu.edu).

UCLA Social Science Data Archive

SSDA Dataverse

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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.

York University Dataverse

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York University Libraries makes available Borealis for despositing data . Borealis is a an instance of Dataverse hosted by The Ontario Council of University Libraries, of which York University Libraries is a member.

UNB Libraries Dataverse Research Data Repository

University of New Brunswick Libraries Dataverse Research Data Repository

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UNB Dataverse is repository for research data collected by researchers and organizations primarily affiliated with the University of New Brunswick. The repository allows researchers to deposit, share, analyze, cite, and explore data. Dataverse is an open source application developed by the Institute for Quantitative Social Science (IQSS) at Harvard University.

The Abdul Latif Jameel Poverty Action Lab

J-PAL Dataverse

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Data from selected studies from the Abdul Latif Jameel Poverty Action Lab (J-PAL), povertyactionlab.org. A number of other studies from J-PAL have data posted on the MacArthur Dataverse: http://dvn.iq.harvard.edu/dvn/dv/macarthur.

Dados Abertos De Pesquisas

Repositório de Dados de Pesquisas do Instituto Federal Goiano – Campus Urutaí

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Research Data Repository of the Instituto Federal Goiano - Campus Urutaí, a Brazilian public institution of the Ministry of Education. The project is an initiative of the Directorate of Post-Graduate Studies, Research and Innovation of the Federal Institute of Goiás - Campus Urutaí, which follows the philosophy of Open Science, for expansion and valuation of scientific research, aiming to provide data from technical-scientific observations and experimentation, ensuring that its authors, researchers and students receive all the credit they deserve as agents generating data. At the same time, the appropriate reuse of data is envisaged, whether in didactic-pedagogical activities or in new research.