Institut Pasteur & INRIA Futurs

Participatory programming and the Scope of Mutual Responsibility:

Balancing scientific, design and software commitment

Catherine LetondalWendy E. Mackay

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Research setting

Institut Pasteur, France

World leader in biological research

Created by Louis Pasteur in Paris in 1850’s

Diverse research environment

Diverse computer environment

Over seven years:

multiple long and short-term participatory design projects

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Computing in biology

Biologists rely on a variety of software tools:

Algorithms, databases, editors, websites with on-line tools

Two main types:

• large scale projects (genomic centers, .gov or .europ, etc.)

• local developments (often not distributed)

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Computing in Biology

Needs:

• simple data manipulation and editing

• database search, retrieval and browsing

• tools for running standard data analyses

• tools for constructing scientific hypotheses

• information management tools

Evolution

• dynamic software activity

• developed by domain experts for specific purposes

• small, single-purpose tools

• recycling program chunks vs. reuse of designed modules

• designed modules evolve quickly

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Users as participants

Education: Biology:

Computer Science:

Goals:Biology research:

Tools for biologists:CS research:

Results:Local software:

Distributed software:Biology articles:

CS articles:

Computer scientists

Bioinfor-maticians

Biologists

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Pasteur user survey

Five user categories:

lo-hi use level

lo-hi comfort level

Learners (15%) Occasional

Users (36%)

Non-UNIX (15%)

Young

Scientists (15%)

Gurus (6%)

Discomfort, help needed

Comfort, autonomy

Extensive computing

Little computing

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Informatics in Biology Course

Teach practicing and junior biologists basic programming skill

• Programming autonomy

• Improved communication with computer scientists

Course: 11 sessions, 16 per year, 130 total students

20 Professors: 40% biologists, 50% computer scientists, 10% other

60% Pasteur, 40% exterior

Subjects: Programming, databases, web programming,

Participatory design

Activities: Lectures, workshops, seminars & projects (+50%)

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Software R&D projects

biok Data analysis & visualisation environment for biologists.

1. Analyze biological data, e.g. DNA, sequences 2. Support tailorability and end-user programming

A-book Augmented laboratory notebook,

integrates on-line data with paper lab notebook.

Mobyle Environment for searching, discovering, running &

combining bioinformatics analysis tools.

i3DMo Tk widget for 3D structure visualization

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Participatory design activities

Timeline of participatory design activities (1996 - 2004)

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Reflecting on Participatory Programming

Activities:

Interviews

Group meetings

Questionnaire

Feedback:

Workshops

Course projects

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Boundary objects

Concrete:

Software tools

Abstract:

Program concepts

--------

Installed software

Small local software artifacts, spreadsheets and scripts

(one purpose only)

Projects (from the course) - exercises

Biology problems:

Biologist: the problem

CS: instance of a problem

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Reflection: 3 poles

Most research labs move between 2 poles:

Computational medium and Scientific Hypotheses

Responsibilities:

Software act as Boundary objects

But we do not see boundary roles

Skills: often overlap

Biologists who program, CS who know about biology

Responsibilities: rarely overlap

« Me, I’m not a biologist » or « Me, I’m not a computer scientist »

Image of 2 poles:

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Reflection: 3 poles

If we add a 3rd pole, participatory design,

we open opportunities for better communication and better tools

Participatory design as a ‘boundary activity’

Weak coupling

Image with third pole

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‘

Reflection: 3 poles

Computationalmedium

Participatorydesign

Scientifichypotheses

Localdevelopments

Activetheories

Problemsolving

Scientificscenarios

Informalscientific discussions

Softwaredesign

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Reflection: 3 poles

Most research labs move between:

Computational medium

Scientific Hypotheses

If we add

Participatory Design

We open opportunities for better communication and better tools

(weak coupling)

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Participatory

Participatory Design

Participatory Science

Participatory Problem Solving

Participatory Teaching

Participatory Programming

*

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Participatory Design

Prototyping

Observation

Evaluation Brainstorming

Mackay et al. (2000)

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Participatory Problem-Solving

Designing scientific algorithms:

Who has responsibility for the quality of a scientific hypothesis?

Problem: major misunderstanding

Biologists assume software will help identify scientific questions

Computer scientists assume biologists know the questions

Biologists work with a ‘problem’

Computer scientists consider this to be an ‘instance’ of a problem

Example: biologist is looking yyy gene in a xxx

CS wants to write an algorithm to find this gene in any animal

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Participatory Problem-Solving

Scientific modeling workshops allow participatory problem defining

Participatory prototyping of scientific algorithms

to express scientific problems and sketch potential solutions

Illusion of software ‘magic’ - somehow the software will find the right research question. (Not poor biologists - it’s the tool that creates the illusion)

Example 1: 2 workshops to help define the scientific question:

Data: Families of genes vs. Interactions :

What can we do with this data?

Workshop 1: Brainstorming:

Help identify that the biologists didn’t already have a clear idea of the question - Posed all kinds of different questions (create ‘question’ space)

Workshop 2: Prototyping:

Highly-prepared in advance based on questions that emerged from brainstorming, with lots of data examples

Data examples projected on whiteboard, + paper proto stuf

Refined and validated the question.

What happened - continued to define the question - but this time, seriously evaluating and developing ideas.

Result:

Moving beyond interactive software design to algorithm design

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Course projects

Put in images

Participatory Teaching

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End-user Programming today

Spreadsheets

Scripts

Small databases

Specialised software

Web applications

Distributed software

Algorithms

spreadsheets

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Programming by the user

Biologists program but do not want to be programmers

Need flexibile environment to allow non-anticipated usage

Tool : Biok

MAP = Meta-Application Protocol

Manipulation at multiple levels:

Data (DNA sequences, etc.)

Meta-data (alignment, gap…)

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Participatory Programming

Participatory design for end-user programming

vs.

End-user programming to help the design

Goal : either: end-user programmable software

Or using end-user programming to help in the design

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Participatory Science

Workshops

Serve as a point of discussion for scientific ideas

1 example of PD to explore and specify a scientific design

Why teach participatory design to biologists?

Knowing that it exists, they can demand more and create a better mode of communication with programmers

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Teaching Participatory Design to Biologists

Wendy’s course …

Approach:

A bit strange, but we actively TEACH biologists to do pd.

(they have both roles of being biologists primarily

but also learning to program - and learning PD as

a part of programming, either to communicate with

other programmers or to help them do their own designs…)

Examples from project

Really linked to the issue that who does what..

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Conclusion

- summary view of the 3 poles (as in the paper):

Diagram of three poles

PD -> CM <- science : collaboratively building a CM

CM -> PD <- science : Providing input to the participatory

activities

CM -> science <- PD : Mediating scientific hypotheses

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Boundary objects

Boundary objects are scientific objects which both inhabit several intersecting social worlds and satisfy the informational requirements of each of them. Boundary objects are objects that are both plastic enough to adapt to local needs and the constraints of the several parties employing them, yet robust enough to maintain a common identity across sites. They are weakly structured in common use and become strongly structured in individual site use. These objects may be abstract or concrete. … The creation and management of boundary objects is a key process in developing and maintaining coherence across intersecting social worlds.

(Star & Griesemer, 1989)

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Human-Computer Interaction - 3 themes

New design methods:

participatory designco-adaptive systems

New interaction techniques:

paradigms & interaction models

empirical studies

New software tools:

engineering interactive systems

toolbox

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Utilisateur

Situated Interaction

ComputersUsers

Environment

Artefacts

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Research Strategy

The concept of ‘scientific’ has evolved

Chaotic phenomena: small changes lead to large efffects

Co-evolution : human-system interaction

Triangulation : necessary for ‘real’ problems

Inspiration from other disciplines

Interactive systems are not ‘natural phenomena’

Requires a mix of scientific,engineering and ‘design’ strategies together

Example : architecture

combines science, engineering et design

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Multi-disciplinary approach

design

psychology

sociology

anthropology

industrial design

typography

graphic design

social sciences

Interactive systems

engineering

architecturecomputer science

electronics

mechanicalengineering

optics

physiology

Novel design methods

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Strategies for understanding users

Scientific perspectiveCollect dataAnalyze dataInform designers

Engineering perspective technical trade-offs

ensure that it works “in situ”

Design perspectiveGet design inspirationReflect on daily activitiesRedefine the design problem

[interaction paradigms and models]

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Mixed reality and tangible interfaces

How do we manage physical and on-line documents?

Why is it so hard to eliminate paper?

Mixed realityLinks between physical artifacts and on-line information

Tangible interfacesPhysical objects represent data and software tools

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Mixed reality : A-book

Physical object augmented with software:

Paper notebook

‘Magic lens’

Capture hand-written data

Links and search for data

on-line

Patent: INRIA

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A-book

[novel software tools]

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Compromise between power and simplicity

simplicity

Power of expression

How can we move the curve?

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For more information

Websitehttp://insitu.lri.fr/

Mediated ommunicationhttp://www.lri.fr/~roussel/projects/

Participatory design and mixed realityhttp://www.lri.fr/~mackay/research.html

Information visualisationhttp://www.lri.fr/~fekete/InfovisToolkithttp://www.cs.umd.edu/hcil/millionvis/

Instrumental interaction and the CPN2000 projecthttp://www.lri.fr/~mbl/INSTR/http://www.daimi.au.dk/CPnets/CPN2000/

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Conclusion

Next generation of interactive environments

new design methods

new interaction techniques

new software tools