OpenKM is an Enterprise Content Management Software, often referred to as Document Management Systems (DMS), EDRMS, or CMS.
A Document Management Software (DMS) is a computer program used to store, manage, and track electronic documents and images of paper-based information captured using a document scanner or other means.
OpenKM is a management solution that allows businesses to control the production, storage, management, and distribution of electronic documents and control documents' flow
OpenKM is a document management software that integrates all essential document management, collaboration, and advanced search functionality into one easy to use solution. The system also includes administration tools to define various users' roles, access control, user quota, document security level, detailed logs of activity, and automation setup.
With OpenKM enterprise document management, you can:
Control your enterprise content. Collect information from any digital source. Collaborate with colleagues on documents and projects. Empower organizations to capitalize on accumulated knowledge by locating documents, experts, and information sources. Enterprise content management features. Manage digital content or documents.
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Based on our record, Every Noice at Once seems to be more popular. It has been mentiond 422 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / 5 days ago
Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / 21 days ago
The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 4 months ago
This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 4 months ago
Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 5 months ago
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