This week we close our second season with an open-ended challenge on data apps to visualize the musical production of many artists. I know… we will miss you too…
… But we will come back next year for a new season touching on a variety of data science and analytics topics once again!
Here is the challenge. Let’s use this thread to post our solutions to it, which should be uploaded to your public KNIME Hub spaces with tag JKISeason2-30. If you want to see your name on the leaderboard, make sure to work on the challenges until next Tuesday. We will stop the clock and identify the winners right after that.
Need help with tags? To add tag JKISeason2-30 to your workflow, go to the description panel in KNIME Analytics Platform, click the pencil to edit it, and you will see the option for adding tags right there. Let us know if you have any problems!
it’s a pity I’ve lost most of this second season, but I’m trying to recover
Here is my submission to the challenge. Since it’s the last one, I tried to personalise it a little bit.
Italy is full of dialects. And with “full” I don’t just mean they change from region to region (Sardinian, Sicilian, Lombard, Tuscan, just to mention some) but from city to city, village to village.
In this challenge I included my dialect, called Talamùn (Talamonese in Italian), which is a variant of the Northern Lombard dialect and it’s specific of my village (less than 5.000 inhabitants). If you go to the next village, some words, grammar and expressions change and you might not be fully understand.
In this sense, if you want to add your own language or dialect to this workflow, as long as you fill the Excel file correctly, the flow will add a new language to the available ones.
Wow the last challenge! Thank you @alinebessa, KNIME and my fellow JustKNIMEIT participants… what an interesting 30 weeks we’ve had!
For the final challenge, I used the languages file as a hint to decide what info/charts to create. The user can select their language and then view information about the most prolific artists (most songs) using the Tile View, a bar chart and a pie chart.
I have a bit of an issue displaying the bar chart and pie chart when the language is in German, but I’m not sure why. Maybe the umlaut in the column name. I will keep investigating
I have created a table displaying the top 20 artists, ranked by the number of tracks they released each year. Each artist is represented by a unique color in the table cells. To make it easier for users to locate their favorite artists, only selected artists are highlighted. This solution also supports language selection.
Hello everyone,
Here’s my solution. I’ve created a component displaying a transition in audio features in the provided track data.
I’ve learned a lot and had a great time through JKISeason2. I’m grateful to all the participants and the JKI organizers.
Find herewith my submission for last challenge for the season …this is a Dejavu feel of 66 days of data though. Sample language is arabic while used a translator component by armin for this.
Here is my solution. As I did not have much time I implemented the app that shows the charts based on the highest/lowest parameters of the song of the artist. It is still interactive though. I also decided to check if there are several songs with the same name that come from different artists.
By the way I found some problems in the data too. For example check Norma Jean - you would surprised - just compare song “Memphis will be laid to waste” with other songs from this artist.
So far it was quite a journey and I would like to thank Knime people who organized JK-competition as well regular folks here, I have learnt a lot from you!
Coming here one day after the usual because I was at a KNIME event yesterday.
I’d like to thank you all for participating of JKI this season. It was really fun to organize it, and we learned A LOT from you. It was also very beautiful to see how your solutions kept getting better, and how you were so generous and helpful with one another. This spirit of collaboration is at the core of KNIME, and we are honored to have you as part of our community.
Stay tuned for a few announcements about this season soon, and yes: we will have a season 3 next year!
Our sincerest THANK YOU,
Aline on behalf of the KNIME Team
A little late but I didn’t want to miss the last challenge of JKI S02. This is my take, and I am not presenting very elaborate graphs due to lack of time, but I am happy with the analytical workflow.
I couldn’t follow the challenges regularly due to workload, and some (few of them) were left in draft… In any case, thanks to the KNIME team, and to all the knimer participants from whom we always learn techniques and tricks.
Hi All,
I confess it’s been a while since my last solution… Its good to be back!
I was late getting started and after looking through the work you all have done, I am very impressed with what i see. So now how to do something different…?
I have been working to improve a Venn-Scatter diagram I made so that it will except any data set, not just a chemistry-focused table. What better place to share it than here, with this cool challenge.
The Venn-Scatter hybrid visualized the overlap of three parameters for each artist… Here i selected “energy”, “danceability” and “tempo” for the sets and decided i would want to target artists with high scores for each of these parameters for my play list by setting the filters to have high min values.
In order to visualize which two artists meet my criteria, there is a tooltip that displays the artists name and the values of these metrics:
Ideally, the image would display an album cover, for example, but that was not something i could pull together.