Welcoming GSoC 2022 students!

Thank you to everyone who submitted a proposal to MetaBrainz for this year’s Summer of Code!

This year, we have selected seven projects. The chosen students and projects are:

Ansh Goyal – BookBrainz and CritiqueBrainz: CritiqueBrainz reviews for BookBrainz entities

Ashutosh Aswal – MusicBrainz Android App: Adding BrainzPlayer in Android App

Prathamesh Ghatole – ListenBrainz: Clean Up The Music Listening Histories Dataset

Shatabarto – ListenBrainz: Send a track to another user as a personal recommendation

Shubh – BookBrainz: Unified Creation Form

skelly37 – Picard: Make Picard work in single instance mode, then improve existing error handling and crash info.

Yuzie – ListenBrainz: Add Timezone support to ListenBrainz

Welcome aboard and congratulations!
Your contributions to MetaBrainz projects and the community are impressive and admirable. We look forward to work with you over the summer and see your work come to fruition 🙂

Communication is the key to success in a closely knit community as ours. Always feel free to reach out to your mentors and other members of the community if you face any issues (stuck in your code, health or family emergencies, etc.). We, the mentors, are here to support and help you.

For all the students that applied but did not get accepted: we appreciate your applications, and even if you did not make the cut this year, we hope that you will stick around and apply with us again next year when we know you better – and you know us better.

akshaaatt, alastair, lucifer, mayhem, monkey, outsidecontext, zas

MusicBrainz App 2021 Updates

Greetings, Everyone!

2021 has been a great year for the MusicBrainz Android App. The app has received updates regularly throughout the year!

Now that we are very close to 10,000+ users on the Playstore, it is evident that the app caters to the needs of a number of users, which is wonderful!

We have plans to introduce new features, involving those of ListenBrainz and CritiqueBrainz in the app. We are confident that the app serves its purpose of introducing everyone to the MetaBrainz world very soundly.

The app now features both a light and dark mode for the users!

Notable feature updates made this year can be found at https://musicbrainz.wordpress.com/2021/07/30/musicbrainz-app/

During the end of the year, we have made some remarkable technical updates to the codebase by introducing Fastlane to the app. This eases the process for the developers and allows us to make a release with the click of a button. This means now we can have a production release every month, day, or hour.

Although going strong and steady, the MusicBrainz developers would love more contributors to join in and share their knowledge with us, while we dive deep into the world of music.

Play Store: MusicBrainz – Apps on Google Play

F-Droid: MusicBrainz | F-Droid – Free and Open Source Android App Repository

Github: metabrainz/musicbrainz-android

Thank you!

Acoustic similarity in AcousticBrainz

We’re pleased to announce that we have just released acoustic similarity in AcousticBrainz. Acoustic similarity is a technique to automatically identify which recordings sound similar to other recordings, using only the recordings themselves, and not any additional metadata. This feature is available via the AcousticBrainz API and the AcousticBrainz website, from any recording page. General documentation on acoustic similarity is available at https://acousticbrainz.readthedocs.io/similarity.html.

This feature is based on work started by Philip Tovstogan at the Music Technology Group, the research group that provides the essentia feature extractor that powers AcousticBrainz. The work was continued by Aidan Lawford-Wickham during Summer of Code 2019. Thanks Philip and Aidan for your work!

From the recording view on AcousticBrainz, you can choose to see similar recordings and choose which similarity metric you want to use. Then, a list of recordings similar to the initial recording will be shown.

These metrics are based on different musical features that the AcousticBrainz feature extractor identifies in the audio file. Some of these features are related to timbral characteristics (generally, what something sounds like), Rhythmic (related to tempo or perceived pulses), or AcousticBrainz’s high-level features (hybrid features that use our machine learning system to identify features such as genre, mood, or instrumentation).

One thing that we can immediately see in these results is that the same recording appears many times. This is because AcousticBrainz stores multiple different submissions for the same MBID, and will sometimes get submissions for the same recording with different MBIDs if the data in MusicBrainz is like this. This is actually really interesting! It shows us that we are successfully identifying that two different submissions in AcousticBrainz as being the same using only acoustic information and no metadata. Using the API you can ask to remove these duplicated MBIDs from the results, and we have some future plans to use MusicBrainz metadata to filter more of these results when needed.

What’s next?

We haven’t yet performed a thorough evaluation of the quality of these similarity results. We’d like people to use them and give us feedback on what they think. In the future we may look at performing some user studies in order to see if some specific features tend to give results that people consider “more” similar than others. AcousticBrainz has a number of additional features in our database, and we’d like to experiment with these to see if they can be used as similarity metrics as well.

The fact that we can identify the same recording as being similar even when the MusicBrainz ID is different is interesting. It could be useful to use this similarity to identify when two recordings could be merged in MusicBrainz.

The data files used for this similarity are stand-alone, and can be used without additional data from AcousticBrainz or MusicBrainz. We’re looking at ways that we can make these data files downloadable so that developers can use them without having to query the AcousticBrainz API. If you think that you might be interested in this, let us know!

Congratulations GSoC 2021 students!

Congratulations and thank you to everyone who submitted a project with MetaBrainz for this year’s Summer of Code!

This year, the selected projects are:

Ritiek Malhotra
MusicBrainz – Complete Rust binding for the MusicBrainz API

Akash Gupta
BookBrainz – Implement a “Series” entity

Akshat Tiwari
Musicbrainz Android App – Dawn of Showdown

Jason Dao
ListenBrainz –  Pin Tracks & Review Tracks Through CritiqueBrainz

Yang Yang
MusicBrainz – Push the URL relationship editor to the next level

Welcome to the team, and congratulations!
In these troubled times it is all the more impressive that you all mustered the focus and determination to work on proposals, contribute to MetaBrainz projects and integrate with the community.

In our small and tightly knit team and community, communication is key!
If you run into any kind of issue (stuck in your code, starting a part-time job, health or family emergencies, etc.) don’t hesitate to contact your mentor as early as possible to find a solution; we’re here to support you.

We mentors all look forward to working with you before, during and after the summer, guiding you to success and helping you learn and improve your skills!

ruaok, yvanzo, mr_monkey, lucifer and oknozor

Introducing the BookBrainz merging tool

Today we come with a big BookBrainz website update that allows you to merge duplicate entities!

Being able to clean up the database is an essential step towards importing public bibliographic records and catalogs from partner websites. As with MusicBrainz, you can visit an entity page on BookBrainz and click on a button to add an entity to a merge queue. You can merge multiple entities in one go easily.

BookBrainz merge queue

After clicking the merge button you will be presented with a page that lets you review and select the correct information in case of conflicting data. The revision history of merged entities is preserved, and in the near future you’ll be able undo merges.

BookBrainz merge page

Your feedback is very welcome! We also have a short tutorial on how to use the new merge tool for the curious.

This latest website update also adds annotations for any information that does not fit into the existing format, some small design improvements and bug fixes.

We’ve also added the ability to search for users on the search page. This last feature will come in handy soon as we introduce collaborative User Collections; stay tuned!

Thank you for your continued support, Google!

We’ve recently received our annual $30,000 support from Google. The brings the total amount donated by Google’s Open Source Programs Office to us to over $470,000 — hopefully next year we’ll cross the half million dollar threshold!

I can’t quite express my gratitude for this level of support! Without Google’s help, especially early on, MetaBrainz may never have made it to sustainability. Google has helped us in a number of ways, including Google Code-In and Summer of Code — all of these forms of support have shaped our organization quite heavily over the past 15 or so years.

Thank you to Google and everyone at the Google Open Source Programs Office — we truly appreciate your support over the years!

Please nominate us for the Open Publishing Awards!

We’ve recently found out about the Open Publishing Awards::

The goal of the inaugural Open Publishing Awards is to promote and celebrate a wide variety of open projects in Publishing.

All content types emanating from the Publishing sector are eligible including Open Access articles, open monographs, Open Educational Resource Materials, open data, open textbooks etc.

Open data? That’s us! We’ve got a pile of it and if you like the work we do, why not nominate us for an award?

Thanks!

Google donates $10,000 in cloud computing credits. Thank you!

The Google Open Source Programs Office continues to support MetaBrainz in a number of ways and most recently they donated $10,000 in credit toward their cloud services. Thank you Google!

This credit allows us to run some services in the cloud to round out primary hosting setup — this gives us a some redundancy and allows us to not keep all of our critical eggs in one basket. We can also give our open source developers Virtual Machines from time to time, since a lot of our projects are very data heavy. Having access to a fat VM can sometimes turn a really frustrating project that makes your laptop melt into a project that is satisfying to watch chug along.

Thank you again, Google, the Open Source Programs Office and in particular, Cat Allman!

MusicBrainz Schema change upgrade downtime: 17:00 UTC (10am PST, 1pm EST, 19:00CEST)

Hi!

At 17:00 UTC (10am PST, 1pm EST, 19:00CEST) we will start the process of our schema change release. The exact time that we plan to start the change will depend on how long it takes to finish our preparations, but we expect it to be shortly after 17:00UTC.

Once we start the process we will put a banner notification on musicbrainz.org and we will also post updates to the @MusicBrainz twitter account, so follow us there for more details.

After the release is complete, we will post instructions here on how to upgrade your replicated MusicBrainz instances.

MusicBrainz introducing: Genres!

One of the things various people have asked MusicBrainz for time and time again has been genres. However, genres are hard to do right and they’re very much subjective—with MusicBrainz dealing almost exclusively with objective data. It’s been a recurring discussion on almost all of our summits, but a couple years ago (with some help from our friend Alastair Porter and his research colleagues at UPF), we finally came to a path forward—and recently Nicolás Tamargo (reosarevok) finally turned that path forward into code… which has now been released! You can see it in action on e.g., Nine Inch Nails’ Year Zero release group.

How does it work?

For now genres are exactly the same as (folksonomy) tags behind the scenes; some tags simply have become the chosen ones and are listed and presented as genres. The list of which tags are considered as genres is currently hardcoded, and no doubt it is missing a lot of our users’ favourite genres. We plan to expand the genre list based on your requests, so if you find a genre that is missing from it, request it by adding a style ticket with the “Genres” component.

As we mentioned above, genres are very subjective, so just like with folksonomy tags, you can upvote and downvote genres you agree or disagree with on any given entity, and you can also submit genre(s) for the entity that no one has added yet.

What about the API?

A bunch of the people asking for genres in MusicBrainz have been application developers, and this type of people are usually more interested in how to actually extract the genres from our data.

The method to request genres mirrors that of tags: you can use inc=genres to get all the genres everyone has proposed for the entity, or inc=user-genres to get all the genres you have proposed yourself (or both!). For the same release group as before, you’d want https://musicbrainz.org/ws/2/release-group/3bd76d40-7f0e-36b7-9348-91a33afee20e?inc=genres+user-genres for the XML API and https://musicbrainz.org/ws/2/release-group/3bd76d40-7f0e-36b7-9348-91a33afee20e?inc=genres+user-genres&fmt=json for the JSON API.

Since genres are tags, all the genres will continue to be served with inc=tags as before as well. As such, you can always use the tag endpoint if you would rather filter the tags by your own genre list rather than follow the MusicBrainz one, or if you want to also get other non-genre tags (maybe you want moods, or maybe you’re really interested in finding artists who perform hip hop music and were murdered – we won’t stop you!).

I use the database directly, not the API

You can parse the taggenres from entities.json in the root of the “musicbrainz-server” repository which will give you a list of what we currently consider genres. Then you can simply compare any folksonomy tags from the %_tag tables.

Note about licensing

One thing to keep in mind for any data consumers out there is that, as per our data licensing, tags—and thus also genres—are not part of our “core (CC0-licensed) data”, but rather part of our “supplementary data” which is available under a Creative Commons Attribution-ShareAlike-NonCommercial license. Thus, if you wish to use our genre data for something commercial, you should get a commercial use license from the MetaBrainz Foundation. (Of course, if you’re going to provide a commercial product using data from MusicBrainz, you should always sign up as a supporter regardless. :)).

The future?

We are hoping to get a better coverage of genres (especially genres outside of the Western tradition, of which we have a very small amount right now) with your help! That applies both to expanding the genre list and actually applying genres to entities. For the latter, remember that everyone can downvote your genre suggestion if they don’t agree, so don’t think too much about “what genres does the world think apply to this artist/release/whatever”. Just add what you feel is right; if everyone does that we’ll get much better information. 🙂

In the near future we’re hoping to move the genre list from the code to the database (which shouldn’t mean too much for most of you, other than less waiting between a new genre being proposed for the list and it being added, but is much better for future development). Also planned is a way to indicate that several tags are the same genre (so that if you tag something as “hiphop”, “hip hop” or “hip-hop” the system will understand that’s really all the same). Further down the line, who knows! We might eventually make genres into limited entities of a sort, in order to allow linking to, say, the appropriate Wikidata/Wikipedia pages. We might do some fun stuff. Time will tell!