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Found 8 result(s)

Emage

e-Mouse Atlas of Gene Expression

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EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.

GO-GEO

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>>>This repository is no longer available<<< Go-Geo is an online resource discovery tool which allows for the identification and retrieval of records describing the content, quality, condition and other characteristics of geospatial data that exist with UK tertiary education and beyond. The portal supports geospatial searching by interactive map, grid co-ordinates and place name, as well as the more traditional topic or keyword forms of searching. The portal is a key component of the UK academic Spatial Data Infrastructure.

UK Data Service

UKDS

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The UK Data Service is a national data service funded by the ESRC to provide research access to the UK’s largest collection of social, economic and population data including UK government-sponsored surveys, cross-national surveys, longitudinal studies, UK census data, international aggregate, business data, and qualitative data. Designed to meet the data needs of researchers, students and teachers from all sectors, including academia, central and local government, charities and foundations, independent research centres, think tanks, business consultants and analysts, communities and the commercial sector, the UK Data Service provides access to high-quality social and economic data; support for policy-relevant research; guidance and training for the development of skills in data use, and the development of best practice in digital preservation and sharing. Data users can browse collections online and register to analyse and download them. Open Data collections are available for anyone to use. Key partners include JISC, the University of Manchester, University of Southampton, University of Leeds, University of Edinburgh and University College London (UCL). The lead partner is the UK Data Archive (https://service.re3data.org/repository/r3d100010215) based at the University of Essex, a Trusted Digital Repository (TDR) certified against the CoreTrustSeal (https://www.coretrustseal.org/) and certified against ISO27001 for Information Security (https://www.iso.org/standard/27001). The UK Data Service replaces the earlier ESRC investments of the Economic and Social Data Service (ESDS), the Secure Data Service (SDS), the Survey Question Bank and elements of the ESRC Census Programme.

Publicdata.eu

Europe's Public Data

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>>>!!!<<< 2018-08-17: The repository is no longer available >>>!!!<<< >>>!!!<<< publicdata.eu portal is superseded by European data portal https://www.re3data.org/repository/r3d100012199 >>>!!!<<<

Worldpop

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High spatial resolution, contemporary data on human population distributions are a prerequisite for the accurate measurement of the impacts of population growth, for monitoring changes and for planning interventions. The WorldPop project aims to meet these needs through the provision of detailed and open access population distribution datasets built using transparent approaches. The WorldPop project was initiated in October 2013 to combine the AfriPop, AsiaPop and AmeriPop population mapping projects. It aims to provide an open access archive of spatial demographic datasets for Central and South America, Africa and Asia to support development, disaster response and health applications. The methods used are designed with full open access and operational application in mind, using transparent, fully documented and peer-reviewed methods to produce easily updatable maps with accompanying metadata and measures of uncertainty.

History of Marine Animal Populations

HMAP Data Pages

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<<<!!!<<< The data are no longer accessible. >>>!!!>>>

Virgo Millenium Database

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When published in 2005, the Millennium Run was the largest ever simulation of the formation of structure within the ΛCDM cosmology. It uses 10(10) particles to follow the dark matter distribution in a cubic region 500h(−1)Mpc on a side, and has a spatial resolution of 5h−1kpc. Application of simplified modelling techniques to the stored output of this calculation allows the formation and evolution of the ~10(7) galaxies more luminous than the Small Magellanic Cloud to be simulated for a variety of assumptions about the detailed physics involved. As part of the activities of the German Astrophysical Virtual Observatory we have created relational databases to store the detailed assembly histories both of all the haloes and subhaloes resolved by the simulation, and of all the galaxies that form within these structures for two independent models of the galaxy formation physics. We have implemented a Structured Query Language (SQL) server on these databases. This allows easy access to many properties of the galaxies and halos, as well as to the spatial and temporal relations between them. Information is output in table format compatible with standard Virtual Observatory tools. With this announcement (from 1/8/2006) we are making these structures fully accessible to all users. Interested scientists can learn SQL and test queries on a small, openly accessible version of the Millennium Run (with volume 1/512 that of the full simulation). They can then request accounts to run similar queries on the databases for the full simulations. In 2008 and 2012 the simulations were repeated.

Malaria Atlas Project

MAP

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The Malaria Atlas Project (MAP) brings together researchers based around the world with expertise in a wide range of disciplines from public health to mathematics, geography and epidemiology. We work together to generate new and innovative methods of mapping malaria risk. Ultimately our goal is to produce a comprehensive range of maps and estimates that will support effective planning of malaria control at national and international scales.