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Found 13 result(s)

Danish National Birth Cohort

DNBC

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Exposures in the period from conception to early childhood - including fetal growth, cell division, and organ functioning - may have long-lasting impact on health and disease susceptibility. To investigate these issues the Danish National Birth Cohort (Better health in generations) was established. A large cohort of pregnant women with long-term follow-up of the offspring was the obvious choice because many of the exposures of interest cannot be reconstructed with suffcient validity back in time. The study needed to be large, and the aim was to recruit 100,000 women early in pregnancy, and to continue follow-up for decades. Exposure information was collected by computer-assisted telephone interviews with the women twice during pregnancy and when their children were six and 18 months old. Participants were also asked to fill in a self-administered food frequency questionnaire in mid-pregnancy. Furthermore, a biological bank has been set up with blood taken from the mother twice during pregnancy and blood from theumbilical cord taken shortly after birth.

CIRAD Dataverse

Données de recherche du CIRAD

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The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.

NYCU Dataverse

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Welcome to the National Yang Ming Chiao Tung University Dataverse research data knowledge management website, where you can learn how to obtain, upload, cite and explore research data in the National Yang Ming Chiao Tung University Dataverse.

M-TROPICS

formerly: Bassins Versants Expérimentaux Tropicaux

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The CZO Multiscale TROPIcal CatchmentS (M-TROPICS) consists in the merging, in 2016, of two previously-existing CZOs: BVET (India and Cameroon) and MSEC (Laos and Vietnam). The CZO Multiscale TROPIcal CatchmentS (M-TROPICS) provides the international scientific community with unique decennial time series of meteorological, hydrological, geochemical, and ecological variables in tropical environments. The CZO M-TROPICS involves academic and governmental partners in tropical countries (Cameroun, India, Lao PDR, and Vietnam) and is included in the Research Infrastructure OZCAR, the French contribution to the international CZO initiative.

Harvard Dataverse

The Dataverse Project

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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.

SISSA Open Data

Scuola Internazionale Superiore di Studi Avanzati Open Data

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SISSA Open Data is the Sissa repository for the research data managment. It is an institutional repository that captures, stores, preserves, and redistributes the data of the SISSA scientific community in digital form. SISSA Open Data is managed by the SISSA Library as a service to the SISSA scientific community.

DR-NTU (Data)

Data repository - Nanyang Technological University

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DR-NTU (Data) is the institutional open access research data repository for Nanyang Technological University (NTU), Singapore. NTU researchers are encouraged to use DR-NTU (Data) to deposit, publish and archive their final research data in order to make their research data discoverable, accessible and reusable.

Collaborative Psychiatric Epidemiology Surveys 2001 - 2003

CPES

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CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).

Queen's University Dataverse

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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.

IIT Dataverse

Italian Institute of Technology Dataverse

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IIT Dataverse is the institutional research data repository of the Istituto Italiano di Tecnologia. IIT Dataverse has been operative since May 2021 and is currently open to IIT-affiliated researchers for research data deposition and sharing.

Repository for Open Data (RepOD)

Repository for Open Data

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RepOD is a general-purpose repository for open research data, offering all members of the academic community in Poland the possibility to deposit their work. It is intended for scientific data from all disciplines of knowledge and in all formats. The purpose of RepOD is to create a place where research data can be safely stored and openly shared with others.

Whitehall II Study

Stress and Health Study

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The Whitehall II study was established to explore the relationship between socio-economic status, stress and cardiovascular disease. A cohort of 10,308 participants aged 35-55, of whom 3,413 were women and 6,895 men, was recruited from the British Civil Service in 1985. Since this first wave of data collection, self-completion questionnaires and clinical data have been collected from the cohort every two to five years with a high level of participation. Data collection is intended to continue until 2030.

International Food Policy Research Institute Dataverse

IFPRI Dataverse

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The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.