Data Driven Transformation
Here you find all the tools, methods developed & courses and workshops given during the three-year Data Driven Transformation track.
The courses and educational materials presented here are developed for society, of which some in close collaboration with a variety of institutions and experts.
COURSES & WORKSHOPS
(6.1) Introduction to Data Visualisation
Basic principles of data visualisation.
- Semiology of Graphics (Excerpt), Jacques Bertin, excerpt from Bertin’s Semiology of Graphics, containing explanations of visual variables and the dos and don’ts when using them to represent different kinds of data.
- Beautiful Evidence (Excerpt), Edward Tufte, excerpt from Beautiful Evidence, a book by Edward Tufte about seeing and showing, and on how empirical observations can turn into explanations and evidence presentations.
- World Geographic Atlas, Herbert Bayer, a selection of pages from one of the most beautifully crafted atlas of the world, designed by Herbert Bayer.
- Folder with presentation (pdf) and resources.
(6.2) Image Sorter and Clarifai tutorial
Exploration of a collection of images through their visual attributes, learn how to explore it through Image Sorter, an image browsing application.
(6.3) Conversational Objects
Approach to conversational objects and making as research. Collection of resources and case studies to start a makers print with an open mind!
- No materials needed apart from post its and markers for the check in
- Presentation link (pdf)
(6.4) Rawgraph: from research question to data visualisation
In this hands-on tutorial, you will learn how to explore and test research questions with data visualisation techniques. Which types of visual models are useful for different types of questions, and which data goes with them.
(6.5) Data Curation with Google Spreadsheet
This simple tutorial demonstrates the basics of spreadsheet magic, such as how to import data in Google spreadsheet and how to sort and filter data in different ways. No experience needed!
- Sample Dataset, Google Account
- Folder with presentation (pdf) and sample dataset
(6.6) Network Visualisation with Gephi
This presentation discusses when and why it is interesting to visualise networks, and how to do so by exploring the basics of Gephi (https://gephi.org). You will learn how to format a dataset for Gephi, how to use different visual features and layout algorithms to visualise the dataset as a network, and the principles of reading and understanding network visualisations.
- Sample Dataset, Download Gephi
- Folder with presentation, sample datasets and resources
(6.7) Web scraping tool Medley
The presentation includes an Introduction of tools and techniques used to scrape data from the web. Included in this overview are tutorials for tools such as: Google Search Engine, Google Images, Twitter, Instagram, YouTube, and Wikipedia.
(6.8) Adaptable Mindset MOOC
This course will empower you to find your own way in this increasingly complex world
- Laptop and the will to create an adaptable mindset
- Presentation link
(6.9) R and Visualisation for Beginners
This 2-day course is meant for very beginners to learn data visualisation and R. Participants can learn to handle datasets and make neat visualisations with just a few lines of code. After two days, they can inspect datasets, manipulate them, and plot nice graphs to show their results.
(6.10) Set of Lectures on Statistics
This set of lectures provides an introduction to key statistical methods in machine learning and econometrics.
(6.11) Set of Lectures on Machine Learning
This set of lectures provides an introduction to key machine learning methods.
(6.12) Visualisation for Data Scientist
This lecture introduces the basic steps to design visualisations, and to code them with R or D3. Finally, it gives an overview of key visualisation of interest for all sorts of data analysis tasks.
(6.13) Computer Vision for In-Situ Trash Monitoring
This two-week summer school called Map That Trash! was specifically developed for the École supérieure d’informatique, électronique, automatique (ESIEA), which is a French engineering school. During this course the following topics were addressed: how to make visualisations, how to use illustrator to make stylistic choices, specialised visualisations, clean and manipulate data, learn advanced methods to deal with classification errors, basics of artificial intelligence and basics of computer vision. The summer school assignment was about collecting data by taking images of garbage in the city of Amsterdam. The participants did this by biking around in the seven city districts of Amsterdam. While doing so, one’s GPS coordinates will be mapped. At the end of the two weeks, for each city district an overview has been created of where garbage is a challenge to deal with for the city.
The following topics have been addressed:
- Design Method Toolkit + Design Thinking + Sustainable Development Goals;
- Cycling rules;
- Practical of use of AI;
- Introduction to AI;
- Introduction to computer vision and classifiers;
- Network visualisation with Gephi;
- How to make raw visualisation with Raw Graph;
- Visualising Methods for Digital Systems;
- Dealing with Clarifi and Google API’s;
- R for beginners course and manual;
- Giving and Receiving Feedback.
(6.14) Data Decoloniality and Speculative Design
How to decolonise the web and other stories.
TOOLS & METHODS
If you need to tighten a screw, you will most likely not use a hammer. Depending on the challenges you are facing, there are many interesting tools, methods, and approaches that can support you when designing and innovating your service or product.
Tools & Methods
(7.1) Carbon Dating
A speed dating tool to find possible relationships between climate change solutions and different stakeholders.
4.1 Climate change solutions.
(7.2) Right between our ears (website)
To address a certain communication issue, digital methods of research have been used to create a unique and manually curated dataset of common messages. https://rightbetweenourears.com/
4.2 Right between our ears.
The Donometer is a decision-making tool designed to make climate change (in this specific case climate change, but it could be any change) more actionable by visualising the impact of choices which helps users find better solutions. See the links to the folder with code and the video tutorial to learn more about how the Donometer could be used.
4.1 Climate Change Solutions.
The Decarbonator is a real-time stakeholder mapping tool which can be used to discover which sectors of society are actively addressing a topic. In this case, we focus on the sectors of climate change. Here you can find the printed file for the board and the lasercut files to reconstruct the Decarbonator.
4.1 Climate Change Solutions.
(7.5) Interactive Visualisation GGD
This interactive visualisation prompts users to explore new connections between datasets by interjecting datasets from different sources. It serves to fix the rupture between environmental data and public health monitor data, without forcing correlations.
3.2 Participatory Ecosystem for Public Health
(7.6) See you on the street
This tool is developed in the form of a web-platform. It is a platform that celebrates the phenomena off taking to the streets to demand climate justice by combining digital and physical activism. The webspace takes visual content from recent instances of climate protests on Instagram and compiles them into one ‘digital demonstration.’ The platform is based on a dataset that contains images from climate demonstrations between the years 2015 and 2019. Images were extracted from the Instagram official accounts of four main climate movements (Extinction Rebellion, Fridays for Future, Sunrise Movement, and Zero Hour) as well as from individuals who used the official hashtags of the movements within their post. The team collected the data from Instagram in November 2019, using the Instagram Scraper tool from the DMI. The platform can be accessed here.
4.3 See you on the street.
(7.7) Booklet with digital and visual methods used to study climate debate
The booklet consists of six studies on climate change online debate. Each chapter contains an introduction to the study, a designed research protocol, and research findings.
The studies in this report use digital methods to perform online research. These methods include: instructions to build ranked source lists over time by using Google Images results for the query “climate change”; how-to’s on performing single-platform and cross-platform analysis with Twitter, Facebook, Instagram and others, for finding dominant voices and explore different ‘visual vernaculars’ of climate change; procedures that can be used to spot the most engaging content on Instagram and Twitter; and methods used for analysing climate movements imagery with computer vision.
4.5 Making Climate Visible.
(7.8) Climate future protocol
In this project, artificial intelligence (AI) functions as our co-author, who has (machine) learned about climate imaginaries on the basis of training sets which contain examples of climate fiction literature, indigenous climate change stories, climate-themed visual arts, and Hollywood ‘climate disaster’ film trailers.
In this protocol, several queries have been designed, including queries used to prompt the machine to create new climate imaginaries, in text and in visual form. The machine-generated ‘cli-fi’ narratives have been edited and thereafter translated into short stories, podcasts, and artwork.
4.6 Climate Features: (Machine) Learning from Cl-Fi.
Botoploy is a game developed to explore the potential of chatbots and their ethical and technical challenges, to, in the end, foster public engagement. The game runs on a simple concept similar to Monopoly. Players impersonate a chatbot and must navigate the game to have meaningful interactions with online abusers. The first player who collects all the conversational cards wins. However, to collect the cards, players must face multiple ethical and technical challenges, feats, and dilemmas.
3.3 Anti-Harassment Chatbots.
(7.10) Curating Datasets (GGD)
The interactive D3 visualisation uses glyphs to show multiple dataset characteristics (also called metadata), and includes functionalities to filter data, view datasets details, and edit the datasets and their characteristics (i.e. for long-term curation). The visualisation tool is accessible only to GGD employees, but a public tool with fictitious datasets is available here.
3.5 GGD Monitor.
(7.11) VR tool for data collection
A VR installation was created to physicalise publicly monitored health data, and to bring it closer to the public which it serves. Users can interact with a physical installation that shows a map of Amsterdam with a QR code to access the VR content.
3.2 Participatory Ecosystem for Public Health.
(7.12) Tree visualisation TNO
We designed an interactive visualisation that uses the metaphor of a tree to show a user’s health status, good and bad habits, and risks of non-communicable disease (predicted by a Bayesian Network developed by TNO). The visualisation highlights the most influential habits which, if changed, would most increase the health of the user. Users are also provided with recommendations about changing their habits, and more information on what the habit entails. The tool is available here.
3.4 Habit for Health.