A data-driven approach for understanding Open Design @ Design For Next

A data-driven approach for understanding
Open Design. Mapping social interactions
in collaborative processes on GitHub
Massimo Menichinelli
IAAC | Fab City Research Lab
Aalto University – School of Art, Design and Architecture – Department of Media – Media Lab
Helsinki
SUPSI – Department for Environment Constructions and Design
massimo@fablabbcn.org – massimo.menichinelli@aalto.f

Introduction
1. Trend: development and adoption of digital technologies
in the Design field
2. Context: Open Design + Maker Movement + Digital
Platforms = collaborative design processes for digital
content + manufacturing
3. Target: Designer / researcher as reflective practitioner
4. Scope: A software library and a data-driven approach for
understanding design-related cases, not case-studies

Introduction
5. Research questions:
1. how could the analysis of social interactions over time on
such platforms improve the understanding of design-
related collaborative processes?
6. Goals:
1. advance our understanding of how platforms connects and
influence makers and designers in their collaborative work
on Open Design
2. provide support to the activity of Maker and Design
researcher and reflective practitioners

Overview of the paper
1. the intersections of platforms, makers and designers (section 1-2)
2. existing approaches in understanding social interactions in GitHub and
related tools and platforms (section 2)
3. a proposal of a software library for analysing networks of social
interactions over time on GitHub (section 2)
4. its application to three cases (section 3) of
1. discussing the nature and concepts of Open Design (section 3.2)
2. teaching Open Design to interaction design students (section 3.3)
3. the development of a Maker platform for laboratories and for Open
Design project development (section 3.4)
5. conclusions regarding the results obtained, the limits of the research and
potential future directions for improving it (section 4)

1. Open Design: the Design discipline started adopting the tools
and principles from Open Source and P2P software development
community, opening the design processes, documentations and
outcomes to digitally-enabled communities.
2. Maker movement: a loose global movement of individuals who
focus on making physical projects but with a digital layer and
digital tools, often with collaborative processes and the sharing of
the digital files or documentation. Makers often meet and work in
globally-networked laboratories such as Fab Labs, Makerspaces
and Hackerspaces that provide access to a local and global
community of like-minded actors and to several digital fabrication
technologies able to manufacture easily and locally digital
projects.
Context: Open Design + Maker movement

1. Digital businesses with ecosystems, partnerships and
communities where it is easy for providers and users to
participate
2. Long tails, exchange of goods and services (multisided
platforms)
3. Features, (big) data, ability to scale
4. Influence on society, politics, economy, knowledge
5. A source of data for understanding phenomena (and
their impact on them)
6. Used by makers and designers
Platforms

Git / GitHub
Versions of a project managed by multiple authors.
Source:https://github.com/fablabbcn/fablabs/commits/master

Git / GitHub
Issue assignment and comments for discussing the project.
Source: https://github.com/fablabbcn/fablabs/issues/assigned/ceritium

Analysis of platforms (GitHub)
Previous literature:
1. Analyses of Git (and other version control systems) projects
2. Analyses of projects hosted on several platforms
3. Analyses of projects hosted on GitHub
Mostly social network analysis methods in order to understand
latent organizations, community structure, team dynamics,
participation of developers and project evolution

A software for analysis of platforms (GitHub)
1.Social network analysis of
interactions over time
2.Free / Open Source and easy to use:
pip install platform_analysis
3.Can be used for analysis,
visualization, and inside
platforms
4.Python data science ecosystem
5.Git / GitHub (and other version
control systems) projects
6.Can be expanded to more
platforms = more dimensions of a
project can be analysed
Source: https://pypi.python.org/pypi/platform_analysis/0.20 - https://github.com/openp2pdesign/platform_analysis

Data format
[{
"@node": "Content id",
"date": "Content creation date",
"msg": "Content title or body",
"author": {
"#text": "User name",
"@email": "User e-mail",
"avatar_url": "User avatar URL on GitHub"
}
}]

Type of analyses
1. A graph of interactions among users (a social network analysis):
1. centrality of users (degree, betweenness, closeness,
eigenvector, …)
2. users who produced commits, or just online comments
3. community structure
2.a plot of interactions over time among users (a time series
analysis):
1. all interactions
2. interactions split by type
3. interactions split by user

Example: 3 cases
1. Discussing the nature and concepts of Open Design
2. Teaching Open Design to interaction design students
3. The development of a platform for Maker laboratories
and Open Design projects

Example: #01 Defining Open Design
Source: https://2012.okfestival.org - https://github.com/OpenDesign-WorkingGroup/Open-Design-Definition

Example: #01 Defining Open Design

Example: #02 Teaching Open Design
Source: https://www.maind.supsi.ch - https://github.com/OpenDesign-SUPSI

Example: #02 Teaching Open Design

Example: #03 Maker + Open Design platform
Source: https://www.fablabs.io - https://github.com/fablabbcn/fablabs

Example: #03 Maker + Open Design platform

More analyses / visualizations #01

More analyses / visualizations #02

Conclusions
This approach is useful for understanding:
1. the process of a project
2. the interactions that constitute the process
3. the kind of work done in the process
4. the influence and importance of specific actors on the
process
5. the amount of participation in the process

1.Large scale research = more insights about the impact of platforms on maker
and designer activities
2.Small scale research = insights related to the specific projects
3.Custom interactive visualizations tools for exploring all the available data
4.Refine data extraction and analysis for all the features of Git and GitHub
5.Compare interactions with the overall individual activity that is not
collaborative, in order to understand the balance between autonomous
work and collaborative one.
6.Integrate with more version control systems tools and social media platforms
7.Combine it with qualitative methods like interviews, in order to understand
not just the activity of a project as a whole, but also the experience of each
participant
Limitations / Future research

Thank you.
info@make-it.io
http://make-it.io
https://twitter.com/MAKE_IT_io
https://www.facebook.com/makeitio/
Massimo Menichinelli
IAAC | Fab City Research Lab
Aalto University – School of Art, Design and Architecture – Department of Media – Media Lab Helsinki
SUPSI – Department for Environment Constructions and Design
massimo@fablabbcn.org - massimo.menichinelli@aalto.f

A data-driven approach for understanding Open Design @ Design For Next

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