In August last year (2020), we started the Contributor Of The Month (COTM) program. Every month a member of the KNIME community is selected to be highlighted as Contributor Of The Month.
COTM candidates are KNIME users who have contributed to increasing the KNIME presence on social media, enabling a better learning experience as educators, providing technical help for other fellow users on the KNIME Forum, sharing their experience via articles, blogs, and YouTube videos, and finally, widening the landscape of the official KNIME nodes through newly developed nodes and components. Now that twelve months have passed, the time has come for a retrospective.
But first, even though one year has only 12 months, we do have 13 COTMs. And second, COTMs are chosen according to the five categories listed above: academic ambassadors, support KNinjas, bloggers & YouTubers, social media influencers, and component wizards.
Now, it is time to introduce you to the Hall of Fame, Class 20/21!
We all know the difference a passionate teacher can make in school or continuing education. Academic ambassadors have been conveying their passion for data science to learners with visual workflows and KNIME in various contexts. In 20/21 three academic ambassadors were named Contributors Of The Month.
Keith McCormick. Keith is an independent instructor, at both the University of California at Irvine (UCI) and on LinkedIn Learning. There, you can find his KNIME based courses Introduction to Machine Learning with KNIME, and Data Science Foundations - Data Assessment for Predictive Modeling. Keith not only works as a teacher, he is a teacher at heart. He enjoys preparing his students for the professional world, provoking that effect of surprise when revealing insights from data, and grading his students. Yes, grading, since this is the moment where he can interact with the work of the students, not only to criticize, but also to explain and praise (see Keith’s interview in DCE Magazine).
Giuseppe Di Fatta. Giuseppe Di Fatta is Head of the Department of Computer Science at the University of Reading, where he also teaches data science courses using KNIME Analytics Platform: Data Science Algorithms & Tools, and Data Analytics and Mining. Among the many tools for data science, he also has introduced KNIME Analytics Platform, because he sees the benefit of an open source, low code data science tool in a student’s portfolio for their future career. Giuseppe also collaborated with KNIME to develop the current KNIME Certification Program and designed many of the examination questions. So, if you took the exam and found the questions too hard to answer … well, now you know what it takes to become a KNIME Contributor Of The Month
Alzbeta Tuerkova. Alzbeta Tuerkova is a postdoctoral researcher at Uppsala University. Alzbeta obtained a PhD in biology, with a thesis on hepatic organic anion transporting polypeptides belonging to the SLCO family, from the University of Vienna. Together with Barbara Zdrazil, Alzbeta published a notable research paper about an efficient and reproducible, fully KNIME based, drug-repurposing application to identify new drug candidates for rare diseases and COVID-19 . The workflow, tutorials, and information gained on COVID-19 data have been made freely available to the scientific community for follow-up studies and learning (see “Automated Drug Repurposing Pipeline in KNIME".).
 Tuerkova, A., Zdrazil, B. A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19. J Cheminform 12, 71 (2020). https://doi.org/10.1186/s13321-020-00474-z
These are the people you need when you are stuck with your work. You can find them everywhere, but especially in places like the KNIME Forum. Here their names (or usernames) show up frequently. For 20/21 we highlighted Markus Lauber and Philipp Kowalski in particular, for their fast and knowledgeable help.
Markus Lauber. I am sure you have seen his answers on the KNIME Forum, where he goes by the name of mlauber71. To date, he has created 2.0k posts, received 2.8k hearts, created 8 topics, and provided 130 solutions. All in all, he has been a highly active and trusted member of the KNIME Forum for many years already. He is also very active in content creation, both on the KNIME Forum as well as on the KNIME Hub. We'd like to especially point out his School of Duplicates article! You can find it linked from the Knowledge Sharing category on the KNIME Forum.
Phil Kowalski. Phil is another active and helpful member of the KNIME Forum, where he goes by the name of kowisoft. He is not as prolific as others in providing solutions to questions, but he is very prolific in challenging the community by pushing the KNIME software to the limit. In his forum post “Are you crazy? Show your weirdest use cases – here it is mine!”, Phil shares how he has used KNIME to spark his personal creativity - specifically for his hobby of role-playing games. Dive into the world of wizards, dwarves, elves, and humans working on heroic quests. Maybe you’ll be inspired to accept his challenge and share your own crazy KNIME projects!
Bloggers & YouTubers
What would we do without bloggers and YouTubers? Without those precious little pills of knowledge dispensed on us in between lunch and catching up with emails? KNIME bloggers and YouTubers provide us with new success stories, ideas, practical and theoretical tutorials, tips and tricks, and other similar pre-digested pieces of information.
Angus Veitch. Angus is an active member of the Australian community and has written numerous blog articles about KNIME. His interest lies on the analysis of social media data, especially Twitter data. In his TweetKollidR workflow article, he describes his KNIME workflow for creating text-rich visualizations of Twitter data around a given hashtag. He is also a member of the current editorial board of the newly created KNIME publication on Medium “Low Code for Advanced Data Science”, a journal with the aim of publishing articles by the KNIME community.
Dennis Ganzaroli. Dennis has been on fire these past 12 months. He has been successfully predicting everything, like Nostradamus and the octopus Paul, but using data science models and KNIME Analytics Platform. First, he predicted the curve for the COVID spread worldwide; then he broke it down to predict the COVID spread country by country; and lastly he even predicted the outcome of this July’s European soccer championship, UEFA Euro 2020, with the help of a curious character: Yodime. The beauty of it is that he explained it all in detail, how the models were created and trained to perform such predictions, without disdaining a mix of tools, like KNIME, Jupyter, and Tableau, when needed.
@Makkynm. Unfortunately, I do not speak Japanese, but my colleagues, who do, have ensured me that the blog run and maintained by @Makkynm is a precious resource to grow your knowledge of KNIME Analytics Platform, be it for beginner, intermediate, or advanced KNIME users. The blog is written in Japanese, and it is aimed at the Japanese data science community. Notice that we do not know who @Makkynm is since he sent his Twitter avatar to represent him in the Hall of Fame of COTM 20/21.
Social Media Influencers
We all have our role models, our influencers. Some people follow the Kardashians. We follow Vijaykrishna Venkataram (@vijayv2k) on Twitter & LInkedIn, and Evan Bristow and Miguel InfMad on Facebook. Why? Because from their posts, comments, and tweets we can always learn something new to add to our KNIME and data science knowledge. Kardashians who?
Vijaykrishna Venkataraman. Vijaykrishna Venkataraman was our first KNIME Community Contributor! The whole idea of the COTM program came from his mind map. Indeed, in August 2020 he posted a very original mind map to describe the features of KNIME Analytics Platform on one side and of KNIME Server on the other side. The mind map was both so detailed and so general that we thought that valuable contributions like this should be rewarded. In the figure on the side, you can see his mind map of KNIME features. If it is too small to distinguish anything, you can read his LinkedIn post on this same topic. In his words, "these are just my picks and don’t cover the entire list."
Evan Bristow and Miguel InfMad. Evan Bristow and Miguel InfMad are the founders and admins of the KNIME Analytics Community group on Facebook. The group has been around since 2019 and counts more than 1000 members: from newbies to KNIME experts. It is a lively, competent, and very helpful group regarding your data science problems and KNIME questions. Their work of support does not end on Facebook. You can also find their contributions on the KNIME Forum and on the KNIME Hub, where they go by the name of EvanB and Miguel_infmad. By the way, you must have noticed by now that here, in this double pack, lies the solution to the mystery of 13 COTMs in a classic year of 12 months!
Wouldn’t it be nice if KNIME had a node for that specific task you need? Like a node for translation? Or for all-in-one text processing? That is where our Component Wizards come to play. You know that in KNIME Analytics Platform you can build components i.e., develop new nodes made from existing nodes. You can share them and even get them verified by the KNIME component group. Here are the top component contributors for the year 20/21.
Armin Ghassemi Rudd. Armin Ghassemi Rudd's Translator and Get Request Plus components can be found on the KNIME Hub and are also featured on our Verified Components webpage. The Translator component uses Google Translate to translate any input text from/to supported languages. The Get Request Plus component adds the “Retry” option to the GET Request node. Besides creating awesome components, Armin has been a long term and very active contributor to the KNIME Forum, where he goes by the name of armingrudd.
SJ Porter. SJ Porter’s GUID Generator and Text Preprocessing components were the community contributions in October 2020, which at that time had the most number of downloads on the KNIME Hub. The first component was, finally, a Globally Unique Identifier (GUID) generator for KNIME. This component is useful for creating a unique key that is not based on Row ID. The Text Preprocessing component uses extremely fast regex-based text processing functions to remove specific types of characters from a String column and normalize the data as much as possible without over-processing. This component eliminates the need to convert text to a Document type in order to preprocess it.
See you in 21/22 …
We thank all Contributors Of The Month in the year 20/21 for their incredible support, and we welcome candidacies for the next Contributors Of The Month in the year 21/22! Send your suggestions to email@example.com