Metadata - problems / ideas (suggestions for database modeling / object recognition)

You distinguish objects in your global and local identity. Each file and link to Qobuz or Tidal has its separate identity. You track these identities with your cloud service and find global object descriptions for further linking. Is this more than a Tidal - copy?

Reports here in the community show that there are still very many cases where further efforts are needed to make it work even more reliably. Reasons are complex. Sometimes the data provider is bad. Even Tidal needs to better maintain stocks and new additions and AllMusic lives primarily from the past still really good. Good personal maintenance of metadata in local libraries is always helpful for object recognition. Also useful is a clear folder structure that allows automatic recognition.

I believe to have perfect metadata in my local library. If the artist with title, album, track and disc number, year of release is well maintained and packed into separate folders, your cloud with other information like genre etc. should actually manage a match of over 90%. For me it was 15 to 25%. If I have files from two different providers, they are put in different folders for me as well. It could hardly be better, unless label, copyright, lyrics, duplicate covers (album and artist) and much more are also considered absolutely necessary mandatory fields and not enriched. Even from that I already embedded a lot and expected from your market appearance that Roon can do it much better.

I have read a lot, tried and am familiar with computer technology. Know many programs and solutions on various operating systems. It is nevertheless identified for a year very little. I have come over test and wait at multiple read in not really to music enjoyment. But I am happy about every customer where it worked.

This circumstance leads to the fact that I can not fully develop my Roon love. I’ll wait to subscribe for another year until I see significant improvements. There are obviously too many combinations (artists, performers, compositions, albums, tracks, labels, periods that you don’t know globally in the cloud, yet I’ve been in the familiar listening area of albums and artists since the 80s that almost every purchase and streaming provider still knows today.

I’m not talking about Bandcamp, Soundcloud or Discogs but these providers here:

What is done here for free should also be possible in 2021 with the Roon database for a fee. All possible links to every artist title and the most important providers. Too bad that Qobuz is not included, because then you would also have direct access. With Roon but no problem, because via Tidal also leads a direct path to Qobuz. Unless both do not have this title:

My guess:

Their cloud is very knowledgeable about metadata from Tidal and Qobuz. Can extend some with AllMusic and also uses MusicBrainz, but not much more.
There may also already be sufficient specialization in iTunes tagging and playlists. It’s certainly not as perfect as Qobuz or Tidal, though. When other legacy providers like Napster or Microsoft or other current market players come into play, it gets much more complicated and your cloud fails 3 times out of 4. Then there are simply no pictures, biographies, reviews, lyrics, just none of the nice things Roon promises. With artist, album and track global object links are sometimes possible manually, but of course way too much effort. The fun factor of manual discovery is gone. No one should do that without good programs.

They wanted to offer and link a database experience from a global point of view independently of the local objects, illustrated with additional texts. Only with this the enormous benefit and the love for Roon unfolds. Creating a good object experience should be your unique selling point. I missed this expertise in my use case.

I need a break and new jump start with fresh ideas. Your full credit list certainly almost always provides an original release date based on artist and title with review, original artist and many more versions. If so at least 9 out of 10 files are illustrated with picture to the artist and album, the experience becomes more enjoyable. Not everyone has to like this and it can be turned on or off with user switch.

Suggestion 1

Instead of complete release identification, always suggest the most original (first release artist - title) and let the customer select it by switch. This way, the library is also better sorted by years. How it goes with the releases then, will be the next exciting journey of discovery and thereby each customer also always finds a local copy without image and text and then prefers to go to the part that comes from Qobuz or Tidal.

Suggestion 2

The purely name identification of genre, label, place, period, country should always be written down twice and switchable and usable in the database. Now we only have switches for one or the other on import. Dynamic switching would be technically more perfect and uses everything local or in the cloud.

Suggestion 3

Your object attributes exclude so much important data. What Roon does not use or derive is not available to Valence. This makes Valence poor in data, experience and boring in performance without detection. Cover artwork, lyrics, artist photos and credits just have to be there to make it the experience promised in the marketing.

Just using everything the web gives would be a smart approach. This is how all music lovers work, using other programs.

Spotify shows how simple data backup and identification can then be. You can hold lists of 5,000 entries in big data dimension via copy & paste, rebuild, filter, sort, backup, temporarily delete, restore…

z. E.g. Here Exportify with setting, what should come.

…and know to each link a search term, which leads in each browser to pictures, texts and soon also to better sounds, if the Lossless customers should be served in the future also. Don’t let this site drain the water from you.

Work also with this freely accessible information.

Example: Up Where We Belong by Joe Cocker and Jennifer Warnes

Track URI spotify:track:3Jm0pbjIOtHgEmvrTlkUCO
Track Name Up Where We Belong
Artist URI(s) spotify:artist:3pFCERyEiP5xeN2EsPXhjI, spotify:artist:1BwHztAQKypBuy5WBEdJnG
Artist Name(s) Joe Cocker, Jennifer Warnes
Album URI spotify:album:5cIXrkl0NX3GMvzLfGl2Tt
Album Name The Best of Joe Cocker
Album Artist URI(s) spotify:artist:3pFCERyEiP5xeN2EsPXhjI
Album Artist Name(s) Joe Cocker
Album Release Date 1992-11-02
Album Image URL
Disc Number 1
Track Number 4
Track Duration (ms) 233240

Track Preview URL
Explicit false
Popularity 65
Added By spotify:user:usernameXYZ
Added At 2021-08-09T06:32:46Z
Artist Genres album rock,blues rock,classic rock,mellow gold,rock,soft rock,folk,lilith
Danceability 573
Energy 429
Key 2
Loudness -8.68
Mode 1
Speechiness 0.0294
Acousticness 597
Instrumentalness 0.0000818
Liveness 0.0839
Valence 361
Tempo 139097
Time Signature 4
Album Genres
Label Parlophone UK
Copyrights C © 1992 Parlophone Records Ltd, a Warner Music Group Company,
P ℗ 1992 Parlophone Records Ltd, a Warner Music Group Company.

What you can do with such information is shown by Playlistmachinery e.g. with this page
or Spotify itself with this:

This won’t happen overnight, but if Spotify expands its datasets in this direction, there will be an offering for every use case (except HiRes niche).

All of this is in the Google cloud and is then already available via a normal browser, even with Deezer.

Joe Cocker, Jennifer Warnes - Up Where We Belong.ogg
Joe Cocker, Jennifer Warnes - Up Where We Belong.opus
Joe Cocker, Jennifer Warnes - Up Where We Belong.flac

Good luck with the further development if you fish in the pool of nearly 400.000.000 customers, it is better profitable if you do not offer the free variant.