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Found 79 result(s)
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.
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The edoc-Server, start 1998, is the Institutional Repository of the Humboldt-Universität zu Berlin and offers the posibility of text- and data-publications. Every item is published for Open-Access with an optional embargo period of up to five years. Data publications since 01.01.2018.
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BExIS is the online data repository and information system of the Biodiversity Exploratories Project (BE). The BE is a German network of biodiversity related working groups from areas such as vegetation and soil science, zoology and forestry. Up to three years after data acquisition, the data use is restricted to members of the BE. Thereafter, the data is usually public available (https://www.bexis.uni-jena.de/ddm/publicsearch/index).
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
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With Open Science OVGU the Otto-von-Guericke University provides its scientists with a research data repository. Measurement data, laboratory values, survey data, methodical test procedures, etc. can be archived in Open Science OVGU and made available to the scientific community via Open Access.
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This data repository allows users to publish animal tracking datasets that have been uploaded to Movebank (https://www.movebank.org/ ). Published datasets have gone through a submission and review process, and are typically associated with a written study published in an academic journal. All animal tracking data in this repository are available to the public.
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The IOWDB was designed for the particular requirements of the Leibniz Institute for Baltic Sea Research. It is aimed at the management of historical and recent measurement of the IOW (to some extend of other data, too) and to provide them in a user-friendly way via the research tool ODIN (Oceanographic Database research with Interactive Navigation).
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The BonaRes Repository stores, manage and publishes soil and agricultural research data from research projects, agricultural long-term field experiments and soil profiles which contribute significantly to the analysis of changes of soil and soil functions over the long term. Research data are described by the metadata following the BonaRes Metadata Schema (DOI: 10.20387/bonares-5pgg-8yrp) which combines international recognized standards for the description of geospatial data (INSPIRE Directive) and research data (DataCite 4.0). Metadata includes AGROVOC keywords. Within the BonaRes Repository research data is provided for free reuse under the CC License and can be discovered by advanced text and map search via a number of criteria.
We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.
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The NOMAD Repository and Archive stands for open access of scientific materials data. It enables the confirmatory analysis of materials data, their reuse, and repurposing. All data is available in their raw format as produced by the underlying code (Repository) and in a common, machine-processable, and well-defined data format (Archive).
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The "Flora of Bavaria" initiative with its data portal (14 million occurrence data) and Wiki representation is primarily a citizen science project. Efforts to describe and monitor the flora of Bavaria have been ongoing for 100 years. The goal of these efforts is to record all vascular plants, including newcomers, and to document threatened or former local occurrences. Being geographically largest state of Germany with a broad range of habitats, Bavaria has a special responsibility for documenting and maintaining its plant diversity . About 85% of all German vascular plant species occur in Bavaria, and in addition it has about 50 endemic taxa, only known from Bavaria (most of them occur in the Alps). The Wiki is collaboration of volunteers and local and regional Bavarian botanical societies. Everybody is welcome to contribute, especially with photos or reports of local changes in the flora. The Flora of Bavaria project is providing access to a research data repository for occurrence data powered by the Diversity Workbench database framework.
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The small digitized archive comprises drawings and photos made by Hans J. Nissen, many of which were not included in the book, The Uruk Countryside. Most of the material consists of pottery, but other ceramic artifacts, stone and metal objects as well as inscribed bricks were also documented. All materials were recorded in the field. The goal of this website is to provide online access to this remaining archival documentation of the Uruk-Warka survey.
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The ZBW Journal Data Archive is a service for editors of journals in economics and management. The Journal Data Archive offers the possibility for journal authors of papers that contain empirical work, simulations or experimental work to store the data, programs, and other details of computations, to make these files publicly available and to support confirmability and replicability of their published research papers.
The ESCAPE Open-source Scientific Software and Service Repository (OSSR) is a sustainable open-access repository to share scientific software, services and datasets to the astro-particle-physics-related communities and enable open science. It is built as a curated Zenodo community (https://zenodo.org/communities/escape2020) integrated with several tools to enable a complete software life-cycle. The ESCAPE Zenodo community welcomes entries that support the software and service projects in the OSSR such as user-support documentation, tutorials, presentations and training activities. It also encourages the archival of documents and material that disseminate and support the goals of ESCAPE.
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As a research data hub for social and economic history, Emporion enables the free and standards-compliant publication of time series, historical statistical and panel data, georeferenced vector data, text mining analyses and data papers. Emporion is also open to contributions from the fields of business and environmental history and the history of technology. Emporion's supporting institutions are the DFG Priority Programme 1859 'Experience and Expectations. Historical Foundations of Economic Behavior' and the Gesellschaft für Sozial- und Wirtschaftsgeschichte in conjunction with the Staatsbibliothek zu Berlin – Preußischer Kulturbesitz.
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PTB is the national metrology institute of the Federal Republic of Germany. The Open Access Repository of the Physikalisch-Technische Bundesanstalt grants free access to a number of factual datasets and documents that were elaborated at PTB. This includes publications such as the "PTB-Mitteilungen", the metrological expert journal of PTB, and numerous of documents from the field of legal metrology.
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Discuss Data is an open repository for storing, sharing and discussing research data on Eastern Europe, the South Caucasus and Central Asia. The platform, launched in September 2020, is funded by the German Research Foundation (DFG) and operated by the Research Centre for East European Studies at the University of Bremen (FSO) and the Göttingen State and University Library (SUB). Discuss Data goes beyond ordinary repositories and offers an interactive online platform for the discussion and quality assessment of research data. Our aim is to create a space for academic communication and for the community-specific publication, curation, annotation and discussion of research data.
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The Leibniz Data Manager (LDM) is a scientific repository for research data from the fields of science and technology. The service supports a better re-usability of research data for scientific projects. The LDM fosters the management and access to heterogeneous research data publications and assists researchers in the selection of relevant data sets for their respective disciplines. The LDM currently offers the following functions for the visualization of research data: · Supports data collections and publications with different formats. · Different views on the same data set (2D and 3D support). · Visualization of Auto CAD files. · Jupyter Notes for demonstrating live code. · RDF Description of data collections.
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The German Central Health Study Hub is a platform that serves two different kinds of users. First, it allows scientists and data holding organizations (data producers) to publish their project characteristics, documents and data related to their research endeavour in a FAIR manner. Obviously, patient-level data cannot be shared publicly, however, metadata describing the patient-level data along with information about data access can be shared via the platform (preservation description information). The other kind of user is a scientist or researcher (data consumer) that likes to find information about past and ongoing studies and is interested in reusing existing patient-level data for their project. To summarize, the platforms connect data providers with data consumers in the domain of clinical, public health and epidemiologic health research to foster reuse. The platform aggregates and harmonizes information already entered in various public repositories such as DRKS, clinicaltrials.gov, WHO ICTRP to provide a holistic view of the German research landscape in the aforementioned research areas. In addition, data stewards actively collect available information from (public) resources such as websites that cannot be automatically integrated. The service started during the COVID-19 pandemic.
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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.
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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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OpenAgrar is an open access repository which publishes, stores, archives and distributes publications, publication references and research data. Its resources can be searched and used by everyone. It contains amongst others theses, reports, conference proceedings, journal articles, books, institutional documents, research datasets, videos and interviews.