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Found 5 result(s)

openLandscapes

The Knowledge Collection for Landscape Science

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<<<!!!<<< This repository is no longer available. 2018-10-15: no more access to OpenLandscapes >>>!!!>>>

datastore by Universität Münster

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datastore is the cross-domain research data repository of the University Münster (Germany). In datastore, scientific members of the University Münster can publish their research data following the FAIR principles, including the assignment of a DOI for each dataset as a persistent identifier.

Edmond

The Open Research Data Repository of the Max Planck Society

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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.

Open Research Data

ZALF. Open Research Data

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Attention! Data sets are not updated anymore. Please, visit the BonaRes Repositor​ium​ for new datasets. Open Research Data provides quality assessed data and their metadata such as context information on measurement objectives, equipment, methods, testing and investigation areas. The purpose of the repository is to secure quality, integrity and long-term availability of landscape and ecosystem research data as well as to enhance accessibility of free data from ZALF long-term monitoring campaigns, landscape laboratories (Agro-ScapeLabs), field trials and experiments. The Leibniz Centre for Agricultural Landscape Research (ZALF) explores ecosystems in agricultural landscapes and the development of ecologically and economically viable land use systems. ZALF combines scientific expertise from agricultural science, geosciences, biosciences and socio-economics.

Motion Capture Database HDM05

Mocap database HDM05

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It is the objective of our motion capture database HDM05 to supply free motion capture data for research purposes. HDM05 contains more than three hours of systematically recorded and well-documented motion capture data in the C3D as well as in the ASF/AMC data format. Furthermore, HDM05 contains for more than 70 motion classes in 10 to 50 realizations executed by various actors.