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Found 9 result(s)

DataverseNO

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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.

The Polinsky Language Sciences Lab Dataverse

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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.

ICRISAT Dataverse

International Crops Research Institute for the Semi-Arid Tropics Dataverse Network

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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.

1.2 Meter CO Survey Dataverse

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The Radio Telescope Data Center (RTDC) reduces, archives, and makes available on its web site data from SMA and the CfA Millimeter-wave Telescope. The whole-Galaxy CO survey presented in Dame et al. (2001) is a composite of 37 separate surveys. The data from most of these surveys can be accessed. Larger composites of these surveys are available separately.

TROLLing

Tromsø Repository of Language and Linguistics

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The Tromsø Repository of Language and Linguistics (TROLLing) is a FAIR-aligned repository of linguistic data and statistical code. The archive is open access, which means that all information is available to everyone. All data are accompanied by searchable metadata that identify the researchers, the languages and linguistic phenomena involved, the statistical methods applied, and scholarly publications based on the data (where relevant). Linguists worldwide are invited to deposit data and statistical code used in their linguistic research. TROLLing is a special collection within DataverseNO (http://doi.org/10.17616/R3TV17), and C Centre within CLARIN (Common Language Resources and Technology Infrastructure, a networked federation of European data repositories; http://www.clarin.eu/), and harvested by their Virtual Language Observatory (VLO; https://vlo.clarin.eu/).

Washington State University Data Center Dataverse

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The gift of the Stowell Datasets, a digital archive of psychographic data, to the College of Liberal Arts (and continued gift of new datasets) provide a unique opportunity for WSU to facilitate access to a valuable research resource. The datasets include over 350 individual major media market surveys (CATI, Random Digit Dialing telephone surveys) collected over the period 1989-2001 and feature approximately n=1,000+ respondents for each market for each year.

CfA Dataverses

The Astronomy Dataverse Network

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The Astronomy data repository at Harvard is currently open to all scientific data from astronomical institutions worldwide. Incorporating Astroinformatics of galaxies and quasars Dataverse. The Astronomy Dataverse is connected to the indexing services provided by the SAO/NASA Astrophysical Data Service (ADS).

World Agroforestry Centre - ICRAF Dataverse

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The Centre’s vision is a rural transformation in the developing world as smallholder households strategically increase their use of trees in agricultural landscapes to improve their food security, nutrition, income, health, shelter, social cohesion, energy resources and environmental sustainability. The Centre’s mission is to generate science-based knowledge about the diverse roles that trees play in agricultural landscapes, and to use its research to advance policies and practices, and their implementation, that benefit the poor and the environment.

Mindboggle-101

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The Mindboggle-101 data consist of three data sets: (1) individually labeled human brain surfaces and volumes, (2) templates (unlabeled images combining the individual brains, used for registration), and (3) atlases (anatomical labels combining the individual brains, used for labeling).