The role of design in science communication

Lizzie Crouch Science Communication Partner, DesignScience Ellen Dowell Creative ProducerAnne Odling-Smee Design Partner, DesignScience Andrew Friend Interactive Designer

1. What is design?2. Examples of design for science 3. The potential of design for science4. How to collaborate

1. What is design?2. Examples of design for science 3. The potential of design for science4. How to collaborate

DesignScienceWHAT CAN DESIGN DO FOR SCIENCE, AND SCIENCE DO FOR DESIGN?Anne Odling-Smee and Phillip Kent explain how the DesignScience group is working with scientists and engineers to improve understanding of design, and working with designers to improve understanding of science. The goal is better science communication for the benefit of all.

WHY DESIGN?When you think of ‘design’, perhaps you think of cool chairs, designer fashion, or being artistic without practical function? Perhaps you associate design with the worst excesses of branding and advertising, Mad Men, and corporate capitalism? In our work with DesignScience we have different ideas, but we recognise that overcoming stereotypical perceptions is vital and not without its challenges. Those working in the design field also exhibit misperceptions of science that need to be addressed. In our definition, design is concerned with ideas and problem solving on technical, functional, aesthetic, economic and socio-political levels. There is a classic definition (attributed to Neville Shute) of the engineer as a person ‘who can do for ten shillings what any fool can for a pound’. Through intelligent use of tools and resources, a better outcome can be achieved, and for less money.

What engineers achieve in the technical realm, so DesignScience aims to achieve in communication and public engagement for science. Design is perhaps best understood as being like a glue between someone else’s content and an intended recipient. We recognise that scientists do communicate with a variety of audiences all of the time. Those of us who are professionally known as ‘designers’ differ in the degree of expertise that enables us to do this specific job more effectively across the complex variety of communication media now available.

COMMUNICATING SCIENCEThere are many reasons to celebrate the progress that has been achieved in science communication and public engagement with science in recent years – especially here at the Cheltenham Festival. But news stories, such as the entirely predictable and harmful repercussions of the 1990s MMR/autism scandal that have lead to the recent measles epidemic in South Wales, indicate that we have a long way to go.

We see engagement as having two elements: ownership and participation. British society today is at heart the product of science and technology developments going back hundreds of years. It is essential that the majority have a sense of ownership of this heritage as well as for a shared future. Arguably the popular sense of ownership has become stronger in recent years – for example, we see clear public expression of identification with the science celebrities of television and radio. Engagement by participation is a far greater challenge. Both scientists and the public have reasons to be wary of it. We have seen a certain amount of ‘citizen science’, including in the mainstream media, however the participation is typically through observation and data collection

(many eyes, hands or feet) and not in data analysis, interpretation or theory-building.

You may wonder how a greater degree of participation could be possible given the asymmetry of knowledge and expertise. To be sure, we are talking about shifting the asymmetry to significant degrees, not removing it. Exploring this challenge is a major element of the work that the DesignScience group will develop over the next few years. Computing and computational thinking are important because one of the greatest barriers to popular participation in science is lack of mathematical knowledge. Without mathematical understanding, the theories expressed in mathematical form or the workings of data analysis are inaccessible. Computers extend and restructure the ways in which it is possible to engage with the mathematical expressions involved in scientific ideas. Indeed, science and mathematics educational researchers have been exploring this for many decades, but the results are neither well known nor widely accessible. We currently have an unprecedented technological infrastructure of widespread personal access to computers, and electronic networks for exchange of information and social interaction. We need to build on that by devising educational resources and practices to change public participation with science and mathematics.

RISK: COMMUNICATING UNCERTAINTYParticipation is crucial as a means of communicating uncertainty, and this is one of the key challenges for science communication today. Extreme weather events are on the increase and virulent animal flu viruses threaten the human population worldwide. The threat of earthquakes has been with us for millennia, and the scientific expertise now available is substantial. Yet communication of vital information about risk factors breaks down again and again; witness the recent prosecution of six scientists in Italy as a result of the 2009 l’Aquila earthquake.

How can we address the asymmetries of knowledge and expertise between scientists and the public? A powerful idea that we are working with is the potential of computers to simulate reality, in part using the mathematical models that are integral to the scientific understanding of phenomena. It is all too easy to rationalise unlikely future events out of existence because we cannot live through them directly. In a virtual reality, everyone may participate and achieve new kinds of dialogue through the shared experience.

Scientists cannot be held responsible for all of the problems in science communication. Communication is a complex, two-way

process. People may hear and understand a message yet not be able to act on it.

Scientists get fed up when they do their research, then are told they’ve got to communicate it. This is understandable when they lack sufficient expertise or support. DesignScience is trying to build meaningful relationships with scientists, technologists and engineers to make design and communication an integral part of the process of doing research – not just a part you tack on at the end as ‘impact’. To achieve this we have to first overcome our own challenge – that of communicating to scientists what design is and what it can do for science. We hope this feature goes some way towards achieving this, and to dispelling some of the unhelpful myths surrounding our subject.

We are also acutely aware that designers, journalists and public relations teams are not always sensitive or understanding of what science is, or of the needs and interests of scientists; so we are campaigning for a change of attitudes and the development of new learning opportunities and educational resources in this area. Indeed, we are convinced that the practice of design in general would be improved by incorporating more scientific approaches. We see the totality of what we are doing as establishing a feedback loop between design and science that will build up as a significant force for change in science communication. To find out more visit www.design-science.org.uk

Design industries today worth nearly £30 billion to UK economy Department for Media, Culture and Sport, 2014

Research question

Reviewa) Theoretical b) Practical

Theory Dissemination

Design process

1. What is design?2. Examples of design for science 3. The potential of design for science4. How to collaborate

Direct observation of coherent electron dynamics

Henri J. Suominen and Adam Kirrander∗

School of Chemistry, University of Edinburgh, West Mains Road, Edinburgh EH9 3JJ, United Kingdom

(Dated: October 29, 2013)

Detection of electron motion by elastic scattering of short x-ray pulses from a coherent superposition of

highly excited electronic states in rare gas atoms is investigated. The laser excitation of the electron wave

packet introduces strong anisotropy which facilitates detection, and large differences in the radial distribution of

the excited Rydberg and core electrons allow the dynamics to be detected using both soft and hard x-rays.

PACS numbers: 32.30.-r, 32.80.Ee, 34.80.Qb, 82.53.Hn

Imaging electron motion with spatial and temporal resolu-

tion could provide crucial understanding of many processes,

such as photochemical reactions [1]. New x-ray free elec-

tron laser facilities, including LCLS [2], XFEL [3], SACLA

[4], and FERMI [5], capable of short duration, tunable wave

length x-ray pulses with high photon flux, will provide pow-

erful tools for the imaging of matter, including ultrafast x-

ray diffraction with spatial and temporal resolution [6, 7].

Time-resolved x-ray diffraction capable of imaging atomic

motion has already been demonstrated at third generation syn-

chrotrons [8–10] for comparatively slow processes. Recently,

diffraction from nanocrystals [11] and non-crystalline biolog-

ical samples [12], as well as isolated and strongly aligned gas

phase molecules [13], have been observed using x-ray pulses

at the LCLS. These advances set the stage for direct observa-

tion of electron motion.

One of the challenges to imaging electron motion is that

the rapid dynamics of core and valence electrons, on the or-

der of femtoseconds or less, may cause inelastic scattering to

dominate the experimental signal [14, 15]. However, Rydberg

electron dynamics is slower and occurs on the order of pi-

coseconds. Rydberg states play an important role in many gas

phase chemical processes, and tunable Rydberg wave packets

in atoms have been used widely as custom physical labora-

tories to examine fundamental phenomena; examples include

non-dispersing Bohr wave packets [16], coherent control [17],

and high harmonic generation [18]. In a prescient article, Wil-

son et al. [19] suggested that Rydberg wave packets in hydro-

gen atoms could be imaged using x-ray diffraction, with the

electron wave packet forming a natural diffraction grid for the

x-ray photon. Under very specific conditions, x-ray diffrac-

tion from extremely long-lived excited electronic states has

already been demonstrated [20].

Rydberg electron wave packets in rare gas atoms exhibit

complex dynamics, including the effects of electron correla-

tion and quantum interferences, and have a number of im-

portant advantages that make them particularly suitable model

systems for new diffraction experiments. It is straightforward

to control the characteristic time scale of the dynamics by

changing the excitation energy [21], and technologies exist

to shape the wave packets [22, 23]. The anisotropy induced

by the optical excitation pulse prevents rotational averaging

effects and increases the amount of information. Most impor-

tantly, the dynamics can be recorded with both soft and hard

x

y

z

FIG. 1: Schematic of the experiment. The atoms are excited

by a pump laser (red beam) and probed by an x-ray pulse

(blue beam), with the diffracted x-rays measured at a

spatially resolved detector.

x-rays, measuring the complementary dynamics of the core-

hole and Rydberg electrons. This makes it possible to use the

entire range of x-ray energies available at new light sources,

and effectively doubles the measurable signal.

We propose an experiment, shown schematically in Figure

1, in which a pump laser excites a coherent wave packet in

the atoms. The excited electrons are subsequently probed by

an x-ray pulse with variable time delay between the pump and

probe. For highly excited Rydberg states the dynamics is suf-

ficiently slow that elastic kinematic scattering theory can be

used to calculate the diffraction for x-ray energies away from

atomic absorption edges [24, 25],

dσ(s, t)dΩ

=dσTh

dΩ

∫ I(t′)ωk

∣∣∣ f 0(s, t)∣∣∣2 dt′, (1)

where t is the pump-probe delay time, Ω the solid angle for

scattering, I(t′) the x-ray pulse, ωk the energy of the incident

x-rays, and dσTh/dΩ the Thomson scattering cross section

for a free electron. Atomic units are used throughout. The

momentum transfer vector, s=k0−k, is defined as the differ-

ence between the incident and the scattered wave vectors, with

Transmission space appendix c Project 1: AttrAction And reAction

1. What is design?2. Examples of design for science 3. The potential of design for science4. How to collaborate

Visual metaphors

Visual metaphors

‘The price of metaphor is eternal vigilence’

– Lewontin, R. C. (2001)

complex data is also generated by scientists who work with algorithms

such calculations often involve elements of chance/uncertainty and interactivity

programming can visualise such data,make it accessible and understandable, might enable to reveal patterns

visuals are easier to read than lists of numbers

letter frequency

A .08167B .01492C .02782D .04253E .12702F .02288G .02015H .06094I .06966J .00153K .00772L .04025M .02406

N .06749O .07507P .01929Q .00095R .05987S .06327T .09056U .02758V .00978W .02360X .00150Y .01974Z .00074

Shared languageWhy programming could be a shared language between scientist and designer

scientist designer

DesignScience

programming

[Example 2]

Elements of Deborah's Dilemma

Information

• Intentionally complex information to provide authenticity;

• Intentionally conflicting information: different opinions of doctors and evidence from personal research.

Life-style modeller ('what if I don't have the operation?')

The user has chosen three aspects of Deborah's life, which, as inferred from the scenario information, might affect her lifestyle, were she not to have the operation. The clock depicts time passing whilst the red bar in the top right corner oscillates up and down as her pain varies as a result of these activities. The graph records the time variation of the pain. 'Pain' here is no more than a sequence of random numbers, yet this simple device proved effective for users to invest it with meaning.

Probability simulator

© Phillip Kent, Dave Pratt and Ralph Levinson, Institute of EducationLife-style modeller (‘what if I don’t have the operation?’)

1. What is design?2. Examples of design for science 3. The potential of design for science4. How to collaborate

Language

Science communicationA practical guide for designers

1. Defining the brief

2. Bringing collaborators together

3. Acknowledgementof expertise

4. Trusting the process

5. Playing for both teams

6. Pushing ideas