End-User Programming of Visualizations
Lead Research Organisation:
University of Cambridge
Department Name: Computer Science and Technology
Abstract
Visualizations have become important means of communicating information. As data
becomes accessible for more people with no background in programming and data
analytics, there is a growing need for more user-centered visualization software. This
research proposal aims to investigate visualization creation from an end user development
perspective, using the Attention Investment model of programming.
Information visualization has become a common activity for many people. Visualizations
range from simple graphs to infographics, are created by journalists publishing their
findings or designers covering an entire topic in an expressive, compelling visualization,
and can target news readers, business people or research audiences. Given the very
different groups of people that are using visualizations as means of communication, the
ways of creating these visualizations are diverse. Victor (2013) classifies these ways in
three paradigms: using, drawing and coding, each embodied in different software
applications. Representative examples would be Microsoft Excel, Adobe Illustrator and
D3.js respectively.
This research project proposes to look at data visualization from the perspective of end
user programming. From the end user perspective, learning a programming language for
creating visualizations, like Processing or Data-Driven Documents (D3.js) (Bostock et al.
2011), is too expensive. As such, end users prefer to use a more direct manipulation of
information, for example spreadsheets (Lieberman et al 2006). However, research on the
topic of information visualization very rarely appears to be done in a user-centric manner,
even if it's directed for end users (Pantazos et al. 2013).
The approach proposed for end user programming of visualizations also draws on the
theory of Attention Investment (Blackwell 2002, Blackwell & Green 1999). The theory has
been successfully applied mostly to various spreadsheet functionalities (Beckwith et al.
2002, Jones et al 2003), but not to data visualizations.
Guided by the Attention Investment model, the aim is to study the cognitive aspects of
information visualization creation, how existing systems support the users and create
prototypes for data visualization that accounts for the perceived costs, risks and benefits of
the end users.
becomes accessible for more people with no background in programming and data
analytics, there is a growing need for more user-centered visualization software. This
research proposal aims to investigate visualization creation from an end user development
perspective, using the Attention Investment model of programming.
Information visualization has become a common activity for many people. Visualizations
range from simple graphs to infographics, are created by journalists publishing their
findings or designers covering an entire topic in an expressive, compelling visualization,
and can target news readers, business people or research audiences. Given the very
different groups of people that are using visualizations as means of communication, the
ways of creating these visualizations are diverse. Victor (2013) classifies these ways in
three paradigms: using, drawing and coding, each embodied in different software
applications. Representative examples would be Microsoft Excel, Adobe Illustrator and
D3.js respectively.
This research project proposes to look at data visualization from the perspective of end
user programming. From the end user perspective, learning a programming language for
creating visualizations, like Processing or Data-Driven Documents (D3.js) (Bostock et al.
2011), is too expensive. As such, end users prefer to use a more direct manipulation of
information, for example spreadsheets (Lieberman et al 2006). However, research on the
topic of information visualization very rarely appears to be done in a user-centric manner,
even if it's directed for end users (Pantazos et al. 2013).
The approach proposed for end user programming of visualizations also draws on the
theory of Attention Investment (Blackwell 2002, Blackwell & Green 1999). The theory has
been successfully applied mostly to various spreadsheet functionalities (Beckwith et al.
2002, Jones et al 2003), but not to data visualizations.
Guided by the Attention Investment model, the aim is to study the cognitive aspects of
information visualization creation, how existing systems support the users and create
prototypes for data visualization that accounts for the perceived costs, risks and benefits of
the end users.
People |
ORCID iD |
| Alan Blackwell (Primary Supervisor) | |
| Mariana Marasoiu (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509103/1 | 01/10/2015 | 31/03/2022 | |||
| 1649585 | Studentship | EP/N509103/1 | 01/10/2015 | 30/03/2019 | Mariana Marasoiu |
| Description | This work resulted in the design and development of a novel system for creating data visualisations which allows end-user programmers such as business analysts and data journalists to construct new and creative visualisations of their data. This research has resulted in several publications detailing the technical design of the system, as well as the qualitative work that informed the system. |
| Exploitation Route | The outcomes of this funding could support future research into visualisation authoring tools specifically, but also end-user programming more broadly. The approach to bi-directional interaction explored in this work could be applied to other types of interactive systems, such as graphic design and scientific visualisation. |
| Sectors | Digital/Communication/Information Technologies (including Software) |