Ux and Data Visualisation
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This document discusses using user experience (UX) design and data visualization to better understand complex data. It introduces Paula de Matos and Jason Dykes who are experts in UX and visualization. They provide an example scenario about designing a library visualization to help a local authority research officer determine which libraries are most successful. Participants are tasked with sketching a visualization to help address this scenario. The document also discusses challenges of UX design for complex data environments and provides an example of applying a UX process to develop an enzyme portal for bioinformatics data.
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Ux and Data Visualisation
- 1. Using UX and Visualization to give you an edge? Paula de Matos Jason Dykes
- 2. My name is Paula de Matos I live in Cambridge, UK I am an Independent UX Analyst I am South African and Portuguese. I have a special UX interest in complex data and visualization. Tweet at @Paula_deMatos
- 3. My name is Jason Dykes I live in Leicestershire, UK I am an Professor of Visualization at CITY Uni I am a Geographer and a Computer Scientist. I am interested in using visualization in a broad range of domains - transport, energy, ecology, geography, intelligence analysis.
- 5. Meet Jessica • Age: 35 Occupation: Local authority research officer Goals Jessica’s main goal is to determine which libraries are the most successful and why? Using this information she can hopefully transfer this knowledge to less successful libraries and/or decrease redundant library services.
- 6. Scenario – where and when to keep libraries open? “Stockholm library” CC BY Samanthan Marx
- 7. Your task Sketch a visualization that will help Jessica gain some insight into allocating library resources? “Darts” CC BY Richard Matthews
- 8. Read and discuss the task • Read the persona and task. • Find somebody else with the same coloured dot sticker. • Introduce yourself and discuss the task.
- 9. UX and complex data Paula de Matos
- 10. Flickr: Stefson Peter Morville: UX Honecomb What is User Experience (UX)
- 11. A good UX example: The whole package
- 12. What happens when you don’t consider UX? Flickr: Adam Frame
- 13. A UX design Process Study Design Build Evaluate
- 14. UX in complex data environments
- 15. • highly inter-connected • has depth (big picture and high level of granularity important) • high volume, big scale • unfamiliar since it is a ‘niche’/’expert’ field (niche vocab.) • needing security/ privacy/ authentication • real time-critical Complex data environments have data that is/ may be…
- 16. EMBL-EBI EuroHub for Bioinformatics in Hinxton • Part of the European Molecular Biology Laboratory • International, non-profit research institute • 540 people work at EMBL-EBI, 48 nations represented • Average age: 37 yrs
- 17. • At the heart of modern biology research • Science of storing, retrieving and analysing biological information • An interdisciplinary science involving biologists, biochemists, computer scientists and mathematicians What is bioinformatics?
- 19. The UX design process and complex data
- 20. UX and Bioinformatics: Enzyme Portal I can’t find anything? We have over 10 databases dealing with enzymes Data is loosely linked and mismatched I can’t see anything?
- 21. Enzyme Portal UX process Stakeholder Analysis User Research: Interviews Data Analysis: Canvas Sort Prototype and Design Evaluation: Usability Testing
- 22. • Preferably in their own environment • Observe and understand context • Ask questions, learn and validate Interviewing users and understanding their complex data
- 23. What is important to you? What do you want? What happens if you ask?
- 24. Interviewing with complex data • Learn some of the basics in advance. • Asking participants to remember “critical incidents”. • Ask open ended questions to help participants discover the data? • Don’t make assumptions – data is complex!
- 25. Personas were useful research output
- 26. Modeling user stories/data stories Created using yWorks yEd Graph Editor
- 27. Data Analysis: Establish priorities and Information Architecture
- 29. Canvas Sort Result #1: Relative priorities of data items and actions
- 30. Result #2: Model of the users mental model
- 33. Evaluate – how effective is the Vis
- 34. Task 1: User research Pair up and interview each other for 5 minutes. Goal: try to uncover further success measures in library usage. Use open ended research questions such as • “Can you describe the last time you used a library?” • “Why did you go to the library?”
- 35. “Crosshairs - success” CC BY www.flazingo.com
- 36. Task 2: Sketching a design Sketch a visualization design to help Jessica uncover which are the most successful libraries.
- 37. Task 3: Design evaluation • Groups or about 4 or 5. • Group facilitator needed to control timings. • Each group member spends 1 minute describing their design. • As a group try to find one positive, one limitation and one enhancement for each design in your group.
Editor's Notes
- In order to explore the principles of visualization and the UX process we have designed a task for you based on a fictional persona and scenario. The design scenario – quick taster task.
- Jessica has worked for the local authority (LA) for a number of years. She studied mathematics as an undergraduate in Bristol and later did a Masters degree in sociology at Manchester. She is quite computer savvy and is fairly used to using complex interfaces as part of her job. She is married and has a little girl aged 2. She has recently been promoted to ensure the future viability of the library services in the local authority. As a regular library user she is aware that there is quite a lot of information available that she can use to do this research. She knows that the LA have data on hundreds of thousands of individual library members and their lending patterns at over 30 libraries in the county. These are time stamped and themed – so the LA knows who borrowed what, where, when and for how long. The problem is that the information is densely packed away in databases with no interface for her or the librarians to use to make better decisions. The details of this is in the handouts.
- Local authority is making cuts to the library budget. Jessicas team need to determine which libraries they should keep, which should operate on a reduced timetable or close and which should get more investment.. They have complex data which about borrowers, books and loan times. Jessica wants to gain some insight into the libraries and some sort of visualisation may be helpful.
- Process: Jason will outline some visualisation techniques you could use. While you are listening to his talk you can think about using some of these techniques in your task. 5 minute individual sketching session trying to use the techniques outlined. 15 minutes in your group to discuss the sketches.
- By discussing the task you may uncover more questions and assumptions. The idea is to just give you enough time to digest the design scenario and perhaps also get to know each other.
- ISO 9241-210[1] defines user experience as "a person's perceptions and responses that result from the use or anticipated use of a product, system or service". According to the ISO definition, user experience includes all the users' emotions, beliefs, preferences, perceptions, physical and psychological responses, behaviors and accomplishments that occur before, during and after use. He notes that in order for there to be a meaningful and valuable user experience, information must be:
- The IPOD when it was released was not novel in its idea of a music player. There were many music players around. Why was it enormously successful? Because it delivered the whole user experience package. It wasn’t just a music player but it allowed you to manage and download music. It revolutionalised the music industry and changed the fortunes of a company.
- You get that Kodak feeling…. Kodak was the forerunner of photography for many decades even coining the term “Kodak moment”. It developed a digital camera as early as 1975 but product was dropped for fear of it inflicting damage to photographic sales. Later in the 1990’s when computers were emerging as part of everyday life and users were chomping at the bit for an alternative photography form Kodak did not understand its users and their goals. Their management team thought that they knew best but in the end other companies developed the technology and gave users a way to manage photographs digitally. Instead they clung to the belief that photographic film would be the future and that had to be protected at all costs.
- We all know there is no clear-cut perfect generic UX process. That every project is different. However if we abstract it we can think of the conventional UX iterative design methodology which is study, design, build and evaluate. You are most likely very familiar with this. But what is different in visualisation design? After all you are designing an interactive system?
- Ok lets take a step back. We are here not just to talk about UX but also about data and information visualization. Having worked in complex data environments for many years I have a special interest in information visualisation and understanding how UX and info viz can enhance the users experience. So what do I mean by complex data environments?
- highly inter-connected has depth (big picture and high level of granularity important) high volume, big scale unfamiliar since it is a ‘niche’/’expert’ field needing security/ privacy/ authentication real time-critical
- What the EBI provides is store, archive and provide as a service a complete set of the worlds biological digital data.
- EBI library picture
- New technologies have led to an explosion in biological data Whilst DNA sequencing from genomics covers a large amount of this, other areas of biology have seen large increasing in the capacity to produce data 200 Gigabytes – 40 DVD movies; 238 Terabytes – content of the US Library of Congress in 2011; 16 Petabytes - Large Hadron Collider at CERN in a single year of operation! Biology is rapidly becoming a data heavy science, but is still far behind physics
- The best way to illustrate UCD is by example. At the EBI we had a massive problem with disparate resources around enzymes. We made it so difficult for people to find information on enzymes with a number of resources in different places, disparate and mismatched data and not to mention a different styling for each resource that dealt with enzymes. Furthermore, the data was really quite interlinked and complex with both a high level and low level granularity needed. So a few years ago it was decided to attempt to fix the problem. At around the same time UCD was starting out at the EBI and we decided to follow a UCD approach. That means we placed the user at the forefront of our thinking. This work has been published so you can get the full article if you want more details. As this was a very complex UX problem I thought it would make a good example to illustrate how UX is applied in science.
- We used an agile UX process but managed to get a lot of user research done upfront before development really took off. This is roughly the process we followed with much stakeholder involvement (10 databases upfront), user research, data analysis, design and then evaluation (usability testing). Due to the limited time of this workshop I will only focus on two areas which I think are really relevant to Information Visualization namely, User research and data analysis. Both Jason and myself are interested in exploring how UX methods can be used as an intervention for Info Viz.
- Interviewing users and understanding their complex data can be difficult…. The language and vocab used may be different because its often a niche/expert field. Often participants are not sure what they can get out of their data but sense there might be something there. We tended to interview them in their own environment. This allowed us to observe and understand their context. We asked a lot of questions to learn and also validate our assumptions.
- We quickly realized that our users were specialists and they liked to have everything. So if we asked them then they would just give us everything, hence the complex user stories we modeled.
- It can be really tricky to interview users with complex data. They are experts in their field and getting them to step back and really take a look at their data can be difficult. There are all sorts of challenges and here are some tips which will help you along the way: Learn the basics in advance if you can. Make friends with a domain specialist to help you translate the information you might not completely understand. Often this is data related and vivid in the participants memory providing valuable research data. Remember that participants often don’t know what they need in advance. “Why don’t you like this type of data?”
- So you have done user research what now? We found it important that this user research was articulated to the rest of the team. This would give them a feel for the data and the user. In this project we used personas to create empathy for our end users and also understand their motivations.
- How will the website fit into someone’s day? Key user stories on a single map Spot the ‘hubs’ which will be key pages to design Use the map to validate at testing stage & to design scenarios and tasks Run this by your buddy… see what gaps are missing and questions they would ask?
- We needed a way to enable them to prioritise and establish what is important to them and inadvertently establish a kind of domain information architecture. We wanted to understand how they see the world of enzymes. To do this we designed a game called Canvas Sort for users to “play”. It was designed in a workshop setting with a 4 participants at a table all tackling the same canvas.
- Participants had to prioritse six cards per canvas. Explain how they got to this canvas and what information they would want to see next. They also had to describe what “actions” would be useful for the data.
- This example tally is for data items only can do it for actions/ functionalities Tallying up and comparing what each group chose and did per canvas is interesting. Some times overlap others don’t. Here are two different canvas done for the EP project. The second one has lots of overlaps and the first one doesn’t.
- Building the user mental model in the language they understand.
- Both Jason and myself are still exploring this and learning about these practices. But from our own internal comparisons and based on papers we have read we have determined that there seem to be significant changes in the areas of study and evaluation. The primary difference perhaps is the importance of the data. Data viz people spend a lot of time understanding and studying the data and the user. Whereas the focus in UX is perhaps primarily the user. The data viz people try to bridge the gap between data and the user by offering iterative design solutions.
- Not easy to do evaluation with complexity. For example, I have worked extensively in scientific domains and measuring scientific discovery is is difficult. (vis and scientific UX apps) Similarly in Vis measuring insight can be a difficult too in Vis. Heide Lam et al illustrate this brilliantly. Research 850 papers at major viz conferences and only 361 actually did some form of evaluation of the visualisation. They found that the papers could be classified under 7 scenarios classified as either processes or visualisation. Their goal was to provide a methodology which would allow visualisers to focus on the goal of the visualisation and choose an appropriate method. Most of the methods outlined will be familiar to us Uxers such as observation, usability testing, controlled experiments… No time to go into details but its definatley an interesting read.
- User research task Pair up with your neighbout and interview them for 5 minutes. The goal is to uncover further success measures in library usage. There are obvious success measures that we can think of such as “How many books are taken out of the library” or “How many people visit the library”. But by interviewing your partner can you uncover how they use the library, what they find important to them. You need to use open ended user research questions such as “Can you describe the last time you used a library?” “Why did you go to the library?”
- However the criteria for keeping a library are not just the total amount of books leant. Book loans per person per library with loan and return date Frequency and length of loans Distance travelled to library Other library services used during visits (computers, etc.) Demographic information on their users such as age, gender, place of residence
- On your own, sketch a visualization design to help Jessica uncover which are the most successful libraries. Use the A4 paper, pencils and erasers provided. Try using some of the concepts highlighted in the talks to address some of the success criteria. Remember to use your user research and any additional metrics you uncovered to guide your design. Annotate (post-it notes) to show functionality, interactions and animation. Your sketches should be rough and ready, they are meant just for discussion and idea generation.