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ANPERSANA is the digital library of IKER (UMR 5478), a research centre specialized in Basque language and texts. The online library platform receives and disseminates primary sources of data issued from research in Basque language and culture. As of today, two corpora of documents have been published. The first one, is a collection of private letters written in an 18th century variety of Basque, documented in and transcribed to modern standard Basque. The discovery of the collection, named Le Dauphin, has enabled the emerging of new questions about the history and sociology of writing in the domain of minority languages, not only in France, but also among the whole Atlantic Arc. The second of the two corpora is a selection of sound recordings about monodic chant in the Basque Country. The documents were collected as part of a PhD thesis research work that took place between 2003 and 2012. It's a total of 50 hours of interviews with francophone and bascophone cultural representatives carried out at either their workplace of the informers or in public areas. ANPERSANA is bundled with an advanced search engine. The documents have been indexed and geo-localized on an interactive map. The platform is engaged with open access and all the resources can be uploaded freely under the different Creative Commons (CC) licenses.
This website makes data available from the first round of data sharing projects that were supported by the CRCNS funding program. To enable concerted efforts in understanding the brain experimental data and other resources such as stimuli and analysis tools should be widely shared by researchers all over the world. To serve this purpose, this website provides a marketplace and discussion forum for sharing tools and data in neuroscience. To date we host experimental data sets of high quality that will be valuable for testing computational models of the brain and new analysis methods. The data include physiological recordings from sensory and memory systems, as well as eye movement data.
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The GAVO data centre at Zentrum für Astronomie Heidelberg publishes astronomical data of all kinds – e.g., catalogues, images, spectra, time series, simulation results – in accordance with Virtual Observatory standards, making them findable and immediately usable through popular clients like TOPCAT, Aladin, or programatically through the astropy-affiliated package pyVO or the Java library STIL. We pay particular attention to providing thorough metadata to the VO Registry in order to facilitate discovery and reuse. While we have a clear focus on data produced with German contributions, we will usually publish data of other provenance, too. See https://docs.g-vo.org/DaCHS/data_checklist.html for an overview of what resource-level metadata we ask for; contact us for further information on how to publish through the German Astronomical Virtual Observatory.
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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.
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IIASA DARE is the institutional repository for publishing open research data produced by all researchers affiliated with IIASA - International Institute for Applied Systems Analysis. IIASA has been implemented to help scientists fulfill the requirements from funding bodies and to meet the growing impact of publishing research data. The deposited data will receive a persistent, citable link and it will be openly accessible and stored for the long term.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.