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The TextGrid Repository is a digital preservation archive for human sciences research data. It offers an extensive searchable and adaptable corpus of XML/TEI encoded texts, pictures and databases. Amongst the continuously growing corpus is the Digital Library of TextGrid, which consists of works of more than 600 authors of fiction (prose verse and drama) as well as nonfiction from the beginning of the printing press to the early 20th century written in or translated into German. The files are saved in different output formats (XML, ePub, PDF), published and made searchable. Different tools e.g. viewing or quantitative text-analysis tools can be used for visualization or to further research the text. The TextGrid Repository is part of the virtual research environment TextGrid, which besides offering digital preservation also offers open-source software for collaborative creations and publications of e.g. digital editions that are based on XML/TEI.
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This site provides access to over 210,000 digitized or born-digital images in the Koç University collections featuring prints, photographs, slides, maps, newspapers, posters, postcards, manuscripts, streaming video, and more. The collections consist of the materials of the Koç University Libraries and Archives (AKMED, ANAMED, SKL, and VEKAM), Koç University Faculty and Departments, and projects carried out in partnership with the Koç University Libraries. It includes the Koç University Institutional Repository (KU-IR).
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).
The OpenNeuro project (formerly known as the OpenfMRI project) was established in 2010 to provide a resource for researchers interested in making their neuroimaging data openly available to the research community. It is managed by Russ Poldrack and Chris Gorgolewski of the Center for Reproducible Neuroscience at Stanford University. The project has been developed with funding from the National Science Foundation, National Institute of Drug Abuse, and the Laura and John Arnold Foundation.
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The Maya Image Archive is intended to host research materials provided by various scholars, such as Karl Herbert Mayer, Berthold Riese, Stephan Merk and the members of the project among others. Comprising image collections with photographs, drawings, notes and manuscripts, the Maya Image Archive allows the user to browse through the results of several decades of research trips through the entire Maya region.
It is a platform for supporting Open Data initiative of Government of Odisha, intends to publish datasets collected by them for public use. It also supports widely used file formats that are suitable for machine processing, thus gives avenues for many more innovative uses of Government Data in different perspective. This portal has been created under Software as A Service (SaaS) model of Open Government Data (OGD) Platform India of NIC. The data available in the portal are owned by various Departments/Organization of Government of Odisha. It follows principles on which data sharing and accessibility need to be based include: Openness, Flexibility, Transparency, Quality, Security and Machine-readable.
Data.gov increases the ability of the public to easily find, download, and use datasets that are generated and held by the Federal Government. Data.gov provides descriptions of the Federal datasets (metadata), information about how to access the datasets, and tools that leverage government datasets