DSpace is an open source repository software package typically used for creating open access repositories for scholarly and/or published digital content. While DSpace shares some feature overlap with content management systems and document management systems, the DSpace repository software serves a specific need as a digital archives system, focused on the long-term storage, access and preservation of digital content. The optional DSpace registry lists more than three thousand repositories all over the world.
via Wikipedia infobox
DSpace is an open source repository software package typically used for creating open access repositories for scholarly and/or published digital content. While DSpace shares some feature overlap with content management systems and document management systems, the DSpace repository software serves a specific need as a digital archives system, focused on the long-term storage, access and preservation of digital content. The optional DSpace registry lists more than three thousand repositories all over the world.
==History== The first public version of DSpace was released in November 2002, as a joint effort between developers from MIT and HP Labs. Following the first user group meeting in March 2004, a group of interested institutions formed the DSpace Federation, which determined the governance of future software development by adopting the Apache Foundation's community development model as well as establishing the DSpace Committer Group. In July 2007 as the DSpace user community grew larger, HP and MIT jointly formed the DSpace Foundation, a not-for-profit organization that provided leadership and support. In May 2009 collaboration on related projects and growing synergies between the DSpace Foundation and the Fedora Commons organization led to the joining of the two organizations to pursue their common mission in a not-for-profit called DuraSpace. DuraSpace and LYRASIS merged in July 2019. Currently the DSpace software and user community receives leadership and guidance from LYRASIS.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).