COMMUNITY JOURNAL | FIRST BIRTHDAY | KNIME ANALYTICS PLATFORM
Celebrating one year of community data stories 🎉
By the KNIME community for the KNIME community
In the spring of 2021, we felt deeply the need for yet another journal about data science. We envisioned a collaborative space where we could combine the need for more knowledge about machine learning algorithms, data science techniques, best practices, open-source tools, and case studies with the desire to bring together the wider groups of professionals dealing with data science problems within the KNIME community (i.e., new and expert users, developers, researchers and educators) and to stimulate discussions among them.
Based on this premise, on June 1st, 2021, Low Code for Advanced Data Science started publication, and today we celebrate its first birthday!
Since its opening, almost 180 articles have been published; content for beginners, in data science theory, and about successful data stories have been shared; 34 community writers and 24 KNIMErs have been involved; and 18 fortnightly newsletters have been sent [since September 2021]. Last but not least, 6 KNIME community members have been invited to be part of the Editorial Board to remain true to our mission of creating a publication that is truly both for and by the KNIME community.
Our Stories
The content of the journal was set to fall into three main categories, and the community has responded exceptionally well to our call.
Getting Started
To onboard new KNIME users, Ali Raza Anjum explained why it’s necessary to go beyond Microsoft Excel, Angel Molina shared how he learnt KNIME without spending a single penny, and Tosin Adekanye listed her favorite KNIME capabilities. For more advanced wrangling operations, Kerem Kabil provided a friendly introduction to flow variables, Bob Peers showed how to work with loop nodes to dynamically output to multiple files, and John Denham wrote a tutorial on data visualization and interactive dashboard creation. And what about machine learning for beginners? We could not miss having a few jump start tutorials (here and here) by Ashish Kumar, and Kashyap Gohil just to mention a few.
Data Science Theory
To educate readers about hot concepts in data science theory, Emilio Silvestri and Ivan Prigarin illustrated how GANs work and how they can be implemented without code, Aamir Ahmad Ansari provided a clear explanation of the most popular activation functions used in neural networks, and Artem Ryasik took readers by the hand in a great walkthrough into data anonymization techniques. Statistics lovers must have enjoyed Paul Wisneskey’s article about running a Monte Carlo simulation, whereas advanced users in machine learning surely benefitted from Daria Goldmann’s insights on parameter optimization. But that’s not all. The “Theory” category also offers content about deep learning, sampling strategies, active learning, XAI, and much more.
Data Stories
To show successful solutions to data problems with KNIME, Dennis Ganzaroli predicted the winners of the UEFA Euro 2020, Angus Veitch designed a low-code tool for OCR error correction, and Francesco Tuscolano built a Word2Vec component to deal with sparse categorical variables in predictive modeling. Successful data stories were often the result of blending different technologies in one environment, hence you should not miss Craig Cullum’s story of how he triggered a KNIME Server workflow using Apple’s Siri, or Diego Romero’s geo-visualization solution to create a 3D map with routes of the Camino de Santiago using KNIME and Mapbox. Some data stories were dedicated to a specific industry, such as Pedo Medina’s testimony of how codeless AI can help food manufacturers manage supply-chain disruptions, or Stefan Helfrich and Jeany Prinz’s story about automatic retrieval and analysis of lab data in the life sciences. Many more data stories await you in our dedicated category!
Our Community Writers
Being a KNIME community journal, the writers are the backbone of Low Code for Advanced Data Science. We appreciate your work and the passion you bring to the shaping of your stories. Every time you share your articles, the whole KNIME community has the chance to grow and expand its knowledge. We are happy to celebrate the top-5 most prolific contributors, keep it up!
Newsletter & Contribute
A few months after the start of publication, we realized that to keep our community engaged and always on top of the game we needed a newsletter. That’s how The Workflow with the three must-read articles started being delivered every second Friday to the email box of our subscribers. If you haven’t subscribed yet, go do it!
As we already mentioned, our community writers are the heart and soul of Low Code for Advanced Data Science. If you are a data enthusiast who wishes to share interesting data stories with the community, our publication is the perfect place to publish your articles. To this end, we expanded our “Contribute” section to include writing guidelines, submission instructions, a list of data science topics, workflow design guidelines, and an article template. We also set a writer helpline where you can make a date with the Editors and get help to shape your articles!
We love learning new creative solutions using KNIME from the articles that we publish, and we love to share them with you. We are proud of building together a thriving community that supports each other, shares experiences and shapes the future of low code data science.
Happy first year of community data stories! 🎉
