Gif by Scratch Garden.

Digital methods recipes by the SMART group, iNOVA Media Lab crew and the SMART Data Sprint collaborators, namely the Density Design Lab and the Public Data Lab. Here you find a step-by-step guide to implementing a variety of analytical techniques with and about online data, web-based applications & research software.

🔛👩🏻‍💻🧑🏽‍💻 Click on the orange title(s) to access the recipes.

📁 #SMARTDataSprint DM recipes

Making sense of online data: from spreadsheets to visualizations

Situating an image dataset 🔗

By Janna Joceli Omena

In this methodological protocol, you will learn how to make sense of a dataset with a focus on images situated context, impact and related actors. The document is divided into two parts (overview and detailed perspectives of the dataset) and it relies on a range of research software for data exploratory analysis. it is an excerpt of the project Computer vision networks.

Links: Research Diary ˚ Project proposal ˚ Video ˚ Lessons learnt   

RAWGraphs: from spreadsheet to visualisation 🔗 

By Elena Aversa, Maria Celeste Casolino, Camilla De Amicis, Federico Meani, Mattia Mertens and Alessandro Quets

This practical lab introduces RAWGraphs and how to use it to create three different visual models. RAWGraphs is an open-source web tool developed by DensityDesign Lab, INMAGIK and Calibro to create custom vector-based visualisations on top of d3.js, the Javascript library developed by Mike Bostock.

📝 Slides: Beginner Advanced  

📺 Video: TBA

Image collection analysis

Visualising collection of images 🔗

By Elena Aversa and Mattia Mertens

This practical lab explores various techniques to perform image analysis with ImageSorter, ImageJ, Pixplot, and PicArrange.

📝 Slides: 

📺 Video: TBA

Image circulation, description & cross-platform analysis w/ Memespector GUI outputs🔗

By Janna Joceli Omena

Memespector-GUI (Chao, 2021) is a tool with a graphical user interface which helps researchers invoke proprietary and open-source computer vision APIs to analyse images with ease. In the following recipes, and using the outputs of Memespector-GUI you will learn different analytical techniques to make sense of image collections.

Short link:

Related practical lab:

📺 Video: TBA

Plotting TikTok video thumbnails per posting time, visual style and colour patterns with ImageJ 🔗

By Elena Pilipets

ImageJ is a free software tool and image processing program that can be used to measure, sort, and visualize collections of images according to their visual similarity, time of publication, and various other features. It was developed by the Software Studies Initiative to enable the exploration of patterns in image metadata through macros such as Image Plot and Image Montage. This practical lab will introduce different plotting and montage techniques for studying TikTok visual vernaculars using a collection of TikTok videos/video thumbnails and platform metadata such as timestamps, music, digg count, hashtags, etc. scraped with TikTok scraper.

📝 Slides: ImageJTikTokVernaculars

📁 Recipe folder here 

📺 Video: TBA