Everybody can use Excel, but creating a web-based data-driven story requires professional developers, if not a team. I'm working on making data-driven storytelling easier, more open and reproducible.
The Gamma is a research project to build tools that easily integrate with modern data sources (open government data, public online sources) and let users easily create visualizations that are directly linked to the data, making the visualizations more transparent, reproducible, but also easy to adapt to explore other aspects of the data.
- Visualizing Olympic medalists is a demo that shows how such open data-driven articles could look like. It lets explores the history of Olympic medals.
- Computation + Journalism 2015 paper about an earlier prototype describes ideas and motivations of the project in more details. Watch a 15 minute demo or a 45 minute talk from StrangeLoop.
- The Gamma is on GitHub and everything is available under the MIT license. You can learn about the latest news on Twitter at @thegamma_net.
I'm a frequent conference speaker, founding member of the F# Software Foundation author of C# and F# books and author of many definitive F# libraries. I have been Microsoft MVP since 2004 and used F# since early Microsoft Research versions.
Have you seen the F# testimonials and are you thinking how can your company also benefit from the safety, correctness, efficiency and faster time-to-market provided by F#?
- fsharpWorks trainings — At fsharpWorks, we love sharing our knowledge with your team and we offer a wide range of workshops. We created an online course about F# in Finance and Type Providers and we regularly run an in-person course Fast Track to F# in London. We offer all of these and more as on-site trainings too — just drop us an email!
- F# books and articles — I wrote Real World Functional Programming, which explains functional concepts using C# and F#, edited a collection of F# case studies: F# Deep Dives and also wrote a free O'Reilly report: Analyzing and Visualizing Data with F#.
Coeffects and research
I recently submitted my PhD thesis at University of Cambridge and I closely collaborate with the F# team in Microsoft Research Cambridge.
My recent publications cover a range of topics from theory of context-aware programming, F# and type providers to language extensions for concurrent, reactive and asynchronous programming.
- Coeffects playgrouund is an interactive essay that lets you explore my PhD research in an accessible and fun way. You can read more in our ICFP 2014 paper.
- Academic web page has links to other published papers, work-in-progress drafts, research talks and also information about student projects and courses that I supervised.
Philosophy of science
During my (computer science) PhD, I became interested in how programming language research is done and how it should be done. We tend to think that science has infallible methods for discovering the truth, but is that the case? Or is science more 'sloppy' and 'irrational' than its methodological image as Paul Feyerabend says?
- History and philosophy of types is my most recent work in this area. It uses types as an example of a concept that appears simple, but is (and needs to be) more complex. Watch my LambdaDays talk or read the full-length Onward! essay.
- Philosophy posts on my blog — start with philosophy and history books every computer scientist should read and come to some of the events organized by the HaPoC Comission.
Tuesday, 12 September 2017, 5:42 PM
The word "design" is often used when talking about programming languages. In fact, it even made it into the name of one of the most prestigious academic programming conferences, Programming Language Design and Implementation (PLDI). Yet, it is almost impossible to come across a paper about programming languages that uses design methods to study its subject. We intuitively feel that "design" is an important aspect of programming languages, but we never found a way to talk about it and instead treat programming languages as mathematical puzzles or as engineering problems.
This is a shame. Applying design thinking, in the sense used in applied arts, can let us talk about, explore and answer important questions about programming languages that are ignored when we limit ourselves to mathematical or engineering methods. I think the programming language community is, perhaps unconsciously, aware of this - one of the reviews of my recent PLDI paper said "this is a nice, novel design paper, and the community often wants more design papers in our conferences". The problem is that we we do not know how to write and evaluate work that follows design methodology.
To better understand how design works, I recently read The Philosophy of Design by Glenn Parsons. The book perhaps did not answer many of my questions about design, but it did give me a number of ideas about what design is, what questions it can explore and how those could be relevant for the study of programming languages...
Here you'll find what I'm working on — my blog posts tend to be either updates about projects I'm working on, trainings and talks I'm doing, or longer posts that are early versions of my ideas — some of them become papers, some of them have been cited in other papers, some will be soon forgotten.
Wednesday, 14 June 2017, 1:27 PM
Create open visualizations in four steps. The Gamma aims to make it easier to create transparent data visualizations that let the reader explore data further. Until today, getting started with The Gamma was tricky, because you had to provide data via a REST service. The new Gallery makes it easy to upload your own CSV file or paste data from Excel and it also guides you through the process and lets you easily embed the results into your blog. If you were curious about The Gamma, now you can start using it!
Wednesday, 12 April 2017, 2:05 PM
It is very easy to see academic papers as containing eternal and unquestionable truths, rather than as something that the reader should actively interact with. I recently remarked about this saying that just reading papers is too passive. In this blog post, I try to uncover some of the caveats when reading papers - how we misread history and ignore historical context in which paper was written. I discuss different ways of reading papers and suggest a more active way of reading.
Tuesday, 7 March 2017, 3:31 PM
What can computer science learn from the fantastically wrong theories of 16th century science? What is amazing about the old stories is that the conclusions that now seem funny often had very solid reasoning behind them. In the same way, it is likely that some of our current beliefs about computer science and programming will appear fantastically wrong to a computer scientist of 24th century.
Thursday, 2 March 2017, 11:53 AM
Can open and engaging data visualizations help to fight post-fact world, fake news and the decreasing interest and trust in statistics? I recently gave a talk about my work on programming tools for open, transparent data-driven storytelling at the Alan Turing Institute in London. You can watch the talk on YouTube, but if you prefer text, this blog post is a short summary of the key ideas.
Wednesday, 25 January 2017, 12:31 PM
There were a lot of rumors recently about the death of facts and statistics. I believe the core of the problem is that working with facts is quite tedious and the results are often not particularly exciting. This is the problem that I'm trying to address with The Gamma project - and today, I'm happy to share the first reusable component based on the work that you can use in your data visualization projects.
I published papers about programming languages including type providers, theory of coeffects, concurrent and reactive programming, but also philosophy and history of programming. My academic page has a complete list, including teaching and other activities.
Tomas Petricek. Unpublished draft.
Computer science provides an in-depth understanding of technical and mathematical aspects of programming concepts, but if we want to understand how programming concepts evolve, how programmers think about them and how they are used in practice, we need to consider a broader perspective. In this paper, we develop such broader understanding of monads.
Tomas Petricek. Unpublished draft.
Data science can be done by directly manipulating data using spreadsheets, or by writing data manipulation scripts using a programming language. The former is error-prone and does not scale, while the latter requires expert skills. Live coding has the potential to bridge this gap and make writing of transparent, reproducible scripts more accessible.
Tomas Petricek. Proceedings of European Data and Computational Journalism Conference, 2017
The rise of open data initiatives means that there is an increasing amount of raw data available. At the same time, the general public increasingly distrusts statistics and post-truth has been chosen as the word of 2016. The Gamma project aims to help reverse this development.