Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Certificates

Data access

Data access restrictions

Database access

Database access restrictions

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Syndications

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 10 result(s)
>>> the repository is offline <<< The Detection of Archaeological Residues using Remote-sensing Techniques (DART) project was initiated in 2010 in order to investigate the ability of various sensors to detect archaeological features in ‘difficult’ circumstances. Concluding in September 2013, DART had the overall aim of developing analytical methods for identifying and quantifying gradual changes and dynamics in sensor responses associated with surface and near-surface archaeological features under different environmental and land-management conditions.
The BGS is a data-rich organisation with over 400 datasets in its care; including environmental monitoring data, digital databases, physical collections (borehole core, rocks, minerals and fossils), records and archives. Our data is managed by the National Geoscience Data Centre.
Content type(s)
>>>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.
EartH2Observe brings together the findings from European FP projects DEWFORA, GLOWASIS, WATCH, GEOWOW and others. It will integrate available global earth observations (EO), in-situ datasets and models and will construct a global water resources re-analysis dataset of significant length (several decades). The resulting data will allow for improved insights on the full extent of available water and existing pressures on global water resources in all parts of the water cycle. The project will support efficient and globally consistent water management and decision making by providing comprehensive multi-scale (regional, continental and global) water resources observations. It will test new EO data sources, extend existing processing algorithms and combine data from multiple satellite missions in order to improve the overall resolution and reliability of EO data included in the re-analysis dataset. The resulting datasets will be made available through an open Water Cycle Integrator data portal https://wci.earth2observe.eu/ : the European contribution to the GEOSS/WCI approach. The datasets will be downscaled for application in case-studies at regional and local levels, and optimized based on identified European and local needs supporting water management and decision making . Actual data access: https://wci.earth2observe.eu/data/group/earth2observe
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.
The DCS allows you to search a catalogue of metadata (information describing data) to discover and gain access to NERC's data holdings and information products. The metadata are prepared to a common NERC Metadata Standard and are provided to the catalogue by the NERC Data Centres.
The DMC is designed to provide registered users with access to non-confidential petroleum exploration and production data from offshore Nova Scotia, subject to certain conditions. The DMC is housed in the CNSOPB's Geoscience Research Centre located in Dartmouth, Nova Scotia. Initially, the DMC will manage and distribute the following digital petroleum data: well data (i.e. logs and reports), seismic image files (e.g. TIFF, PDF), and production data. In the future the DMC could be expanded to include operational, safety, environmental, fisheries data, etc.
The Met Office is the UK's National Weather Service. We have a long history of weather forecasting and have been working in the area of climate change for more than two decades. As a world leader in providing weather and climate services, we employ more than 1,800 at 60 locations throughout the world. We are recognised as one of the world's most accurate forecasters, using more than 10 million weather observations a day, an advanced atmospheric model and a high performance supercomputer to create 3,000 tailored forecasts and briefings a day. These are delivered to a huge range of customers from the Government, to businesses, the general public, armed forces, and other organisations.
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.
British Antarctic Survey (BAS) has, for over 60 years, undertaken the majority of Britain's scientific research on and around the Antarctic continent. Atmospheric, biosphere, cryosphere, geosphere, hydrosphere, and Sun-Earth interactions metadata and data are available. Geographic information and collections are highlighted as well. Information and mapping services include a Discovery Metadata System, Data Access System, the Antarctic Digital Database (ADD), Geophysics Data Portal (BAS-GDP), ICEMAR, a fossil database, and the Antarctic Plant Database.