This grantee profile features Stephan Max for our series of Frictionless Data Tool Fund posts, written to shine a light on Frictionless Data’s Tool Fund grantees, their work and to let our technical community know how they can get involved.
# Meet Stephan Max
Hi, my name is Stephan Max and I am a computer scientist based in Cologne, Germany. I’ve been in the industry for over 10 years now and worked for all kinds of companies, ranging from own startup (crowd-funded online journalism), over big corporate (IBM), to established African business data startup (Asoko Insight). I am now a filter engineer at eyeo trying to make the web a fair, open, and safe place for everybody.
I love working with kids and teenagers, cooking, and doing music—I just recently started drum lessons!
# How did you first hear about Frictionless Data?
I’ve been following the work of the Open Knowledge Foundation for a while now and contributed to the German branch as a mentor for the teenage hackathon weekends project “Jugend Hackt” (Youth Hacks). I first heard about the Frictionless Data program when the OKF announced funding by the Sloan Foundation in 2018. After watching Serah Njambi Rono’s talk on Youtube (https://www.youtube.com/watch?v=3Ranx9Jz0Ro (opens new window)) and reading about the Reproducible Research Tool Fund on Twitter, I knew I wanted to contribute.
# Why did you apply for a Tool Fund grant?
I first heard about the concepts and challenges around Reproducible Research when taking the MOOC “Data Science” from Johns Hopkins University on Coursera. Since I had my fair share of work inside proprietary data formats and tools, I was happy to see that there are people out there making serious efforts to remedy the loss of attribution and data manipulation steps. After browsing through OKF’s Frictionless Data website, I was even happier that there are actual tools, libraries, and standards already available. Applying for the tool fund and contributing my own humble idea was a no-brainer for me.
# What specific issues are you looking to address with the Tool Fund?
My goal is to add a Data Package import/export add-on to Google Sheets. I understand that a lot of data wrangling is still done in Sheets, Excel, and files being swapped around. A lot of information is lost that way. Where did the data initially come from? How was it manipulated, cleaned, or otherwise altered? How can we feed spreadsheets back into a Reproducible Research pipeline? I think Data Packages is a brilliant format to model and preserve exactly that information. While I do not want to lure people away from the tools they are already familiar with, I think we can bridge the gap between Google Sheets and Frictionless Data by making Data Packages a first-class citizen.
# How can the open data, open source, community engage with the work you are doing around Frictionless Data Google Sheets add-on?
I think open source and data is a unique and wonderful opportunity to get access to the “wisdom of the crowd” and ensure that software and information is and remains accessible to everyone. In the first few weeks I will focus on getting a first prototype and sufficient documentation up, so you can all play with the Data Package import/export add-on as soon as possible. After that, I invite you to take a look at our Github repository (https://github.com/frictionlessdata/googlesheets-datapackage-tools (opens new window)), play around with the tool, and contribute. Raising an issue, opening a pull request, improving the documentation, giving feedback on the user experience—everything counts! I am so stoked to be part of this Frictionless Data journey and can’t wait to see what we will accomplish. Thank you very much in advance!