Video lectures about Data Foundry

We have recorded a series of video lectures that show what Data Foundry can do and how you effectively use Data foundry in your design (research) projects. We cannot cover all features–that's a moving target–but you will get a good grasp of the main features.


Chapter 1: Introduction

In the introduction of this series of video lectures, we talk about what Data Foundry actually is -- an all-in-one data collection and storage infrastructure for design research projects. Of course that's just the #start. ;-)

Chapter 2: Creating your first project

The second chapter talks about creating the first project: a simple data collection adventure with Processing and the OOCSI system. Before we go into data collection with an IoT dataset, this chapter also explains how to register in the platform and create a project from scratch. #Processing #OOCSI

Chapter 3: Extending your first project

Chapter 3 is about extending the first project from chapter 2, where we talk about adding more sensors and data collectors: in addition to Processing, we will use the ESP32 platform to implement hardware sensors and connect them to the Data Foundry. #Processing #ESP32

In the second part of this video lecture, we show how to collaborate with others in Data Foundry. And then there is the subscription feature... #collaboration #subscription


Chapter 4: Managing project resources

The fourth chapter shows how to work with project resources: participants, devices and wearables. An important point here are public parameters which allow for segmenting participants and other resources into experimental groups and more. Then we talk about wearables, devices and clusters. This opens a lot of possibilities - recommended watching for the later chapters. #participants #devices #wearables

Chapter 5: Qualitative datasets

In chapter 5 we move to qualitative datasets that allow to collect data as diary entries, forms, images and other media. We introduce several new dataset types that help you collect complementary data to the quantitative data before. #diary #forms #media

Diary entries are more powerful than they seem: they can be used in several places in Data Foundry to let participants comment on other data, but also to send textual data, e.g., from the Data Foundry Telegram bot (see chapter 9).

Forms give you a simple way to send a survey to anonymous respondents. We use Markdown format to create forms, which is actually really easy to do and use.

Media data mostly refers to images, and this dataset type allows to collect images, photos and more from participants.

Chapter 6: Collecting data online

In this chapter 6 we talk about how to collect data online using a project website, running a remote study, and finally using the Entity dataset to collect data in a user profile. #project website #Entity dataset

Chapter 7: Export tool

In this video lecture, we check out the Data Foundry export tool that allows to select and merge different datasets. There is visualization, annotation and more. #visualization #data export


Chapter 8: Scripting

Chapter 8 shows how to use an exciting new feature of Data Foundry: scripting. That is, running code on the Data Foundry server that is always on and can directly respond to new data, analyze data, and trigger actions from OOCSI to Telegram. #scripting #Telegram #OOCSI

Chapter 9: Telegram bot

In the ninth chapter, we talk about using the Data Foundry Telegram bot in your design research projects. This allows to quickly engage participants in a study and to respond new data coming from specific or all participants. #Telegram

Chapter 10: Connecting different datasets

Chapter 10 is all about connecting different datasets in a single project and study. We use the 'Data-enabled Design' case to illustrate how different types of data can be collected and analyzed in a complementary way. We do this in two steps: the contextual and the informed step. #data-enabled design #more datasets

Chapter 11: Helping yourself out

As a final chapter, we touch on ways to help yourself, how to find information about Data Foundry, and how to get help when you cannot move forward on your own anymore. #support