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Found 39 result(s)
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DUnAs is the institutional research data repository of the University of Aveiro. This repository is intended to share, archive, preserve, cite, access, and explore research data produced in the university scientific research activities.
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.
Data deposit is supported for University of Ottawa faculty, students, and affiliated researchers. The repository is multidisciplinary and hosted on Canadian servers. It includes features such as permanent links (DOIs) which encourage citation of your dataset and help you set terms for access and reuse of your data. uOttawa Dataverse is currently optimal for small to medium datasets.
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Created and managed by the Library, DataSpace@HKUST is the data repository and workspace service for HKUST research community. Faculty members and research postgraduate students can use the platform to store, share, organize, preserve and publish research data. It is built on Dataverse, an open source web application developed at Harvard’s Institute for Quantitative Social Science. Using Dataverse architecture, the repository hosts multiple "dataverses". Each dataverse contains datasets; while each dataset may contain multiple data files and the corresponding descriptive metadata.
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DataverseNO (https://dataverse.no) 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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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.
UCLA Library is adopting Dataverse, the open source web application designed for sharing, preserving and using research data. UCLA Dataverse will allow data, text, software, scripts, data visualizations, etc., created from research projects at UCLA to be made publicly available, widely discoverable, linkable, and ultimately, reusable
University of Alberta Dataverse is a service provided by the University of Albert Library to help researchers publish, analyze, distribute, and preserve data and datasets. Open for University of Alberta-affiliated researchers to deposit data.
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University of Warsaw Research Data Repository aims to collect, archive, preserve and make available all types of research data. Storing and making data available is possible for users affiliated with the University of Warsaw, Poland, or those involved in projects carried out in partnership with the University of Warsaw. Browsing and downloading publicly available research data is open to all interested.
The Polinsky Language Sciences Lab at Harvard University is a linguistics lab that examines questions of language structure and its effect on the ways in which people use and process language in real time. We engage in linguistic and interdisciplinary research projects ourselves; offer linguistic research capabilities for undergraduate and graduate students, faculty, and visitors; and build relationships with the linguistic communities in which we do our research. We are interested in a broad range of issues pertaining to syntax, interfaces, and cross-linguistic variation. We place a particular emphasis on novel experimental evidence that facilitates the construction of linguistic theory. We have a strong cross-linguistic focus, drawing upon English, Russian, Chinese, Korean, Mayan languages, Basque, Austronesian languages, languages of the Caucasus, and others. We believe that challenging existing theories with data from as broad a range of languages as possible is a crucial component of the successful development of linguistic theory. We investigate both fluent speakers and heritage speakers—those who grew up hearing or speaking a particular language but who are now more fluent in a different, societally dominant language. Heritage languages, a novel field of linguistic inquiry, are important because they provide new insights into processes of linguistic development and attrition in general, thus increasing our understanding of the human capacity to maintain and acquire language. Understanding language use and processing in real time and how children acquire language helps us improve language study and pedagogy, which in turn improves communication across the globe. Although our lab does not specialize in language acquisition, we have conducted some studies of acquisition of lesser-studied languages and heritage languages, with the purpose of comparing heritage speakers to adults.
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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
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Borealis, the Canadian Dataverse Repository, is a bilingual, multidisciplinary, secure, Canadian research data repository, supported by academic libraries and research institutions across Canada. Borealis supports open discovery, management, sharing, and preservation of Canadian research data. Borealis is available to researchers who are affiliated with a participating Canadian university or research organization and their collaborators. Borealis is a shared service provided in partnership with Canadian regional academic library consortia, institutions, research organizations, and the Digital Research Alliance of Canada, with technical infrastructure hosted by Scholars Portal and the University of Toronto Libraries.
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DaRUS, the data repository of the University of Stuttgart, offers a secure location for research data and codes, be it for the administration of own data, for exchange within a research group, for sharing with selected partners or for publishing.
TiU Dataverse is the central online repository for research data at Tilburg University. The TiU Dataverse is managed by the Research Data Office (RDO) at Library and IT Services (LIS). TiU Dataverse takes part of the DataverseNL network. DataverseNL is a shared data service of several Dutch universities and institutions. The data management is in the hands of the member organizations, while the national organization Data Archiving and Networked Services (DANS) manages the network
PSI is a global health organization dedicated to improving the health of people in the developing world by focusing on serious challenges like a lack of family planning, HIV and AIDS, barriers to maternal health, and the greatest threats to children under five, including malaria, diarrhea, pneumonia and malnutrition. A hallmark of PSI is a commitment to the principle that health services and products are most effective when they are accompanied by robust communications and distribution efforts that help ensure wide acceptance and proper use. PSI works in partnership with local governments, ministries of health and local organizations to create health solutions that are built to last. We use original data to monitor and evaluate our programs, generate consumer insight, estimate the impact of our solutions, and evaluate the health of the markets we work to strengthen.
A data repository for researchers affiliated with Toronto Metropolitan University. This resource is part of Borealis which is a service provided by the Ontario Council of University Libraries.
Queen's University Dataverse is the institutional open access research data repository for Queen's University, featuring Queen's University Biological Station (QUBS) which includes research related to ecology, evolution, resource management and conservation, GIS, climate data, and environmental science.
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The purpose of the Social Data Repository (RDS) is to make available in the Internet social data, consisting of data sets and accompanying technical or methodological documentation. The use of Repository is open for everyone. The repository is operated by the University of Warsaw (Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw). Individual collections in the Social Data Repository are subject to editorial review by University of Warsaw or collection administrators, under separate rules for a given collection. In particular, the supervising editor for the collection “Archive of Quantitative Social Data” is the Team of the Archive of Quantitative Social Data.
The Texas Data Repository is a platform for publishing and archiving datasets (and other data products) created by faculty, staff, and students at Texas higher education institutions. The repository is built in an open-source application called Dataverse, developed and used by Harvard University. The repository is hosted by the Texas Digital Library, a consortium of academic libraries in Texas with a proven history of providing shared technology services that support secure, reliable access to digital collections of research and scholarship. For a list of TDL participating institutions, please visit: https://www.tdl.org/members/.
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RODBUK Cracow Open Research Data Repository is co-created by six Cracow universities: AGH University of Science and Technology, University of Physical Education in Krakow, Cracow University of Technology, Krakow University of Economics, Jagiellonian University in Kraków, Pedagogical University of Krakow. The purpose of RODBUK is to collect, develop, archive and make available in open access all types of research data created by researchers, PhD candidates and students in the course of scientific activity. RODBUK aims to implement the Open Science policy by creating a publicly available platform for depositing research datasets enabling: getting acquainted with the research conducted in Cracow's scientific centers, storage of various types of research data obtaining a permanent Digital Object Identifier (DOI) for each dataset, standardized data citation, choosing a data usage license agreement (Creative Commons or other. RODBUK allows to collect and share open research data from various disciplines and in all file formats. RODBUK applies the FAIR Principles, which means the data is findable, accessible, interoperable, reusable.