In praise of swimlane diagrams
As an Information Architect (IA) I often make diagrams of various kinds – usually user flow diagrams, sitemaps and wireframes. However, I’d never made use of swimlane diagrams until the most recent NoTube project meeting.
Commonly used for diagramming business processes (sometimes in a humourous vein!), I found this visualisation technique to be an extremely useful, simple and versatile tool for helping us to show how all the various components within Notube need to fit together and influence each other to support our scenarios.
The scenarios (descriptive stories about a user’s overall experience) supplied the context and background – the next step was to map these stories to a sequence of discrete ‘activities’ grouped by component to show what happens and when (as others have suggested, a more accurate name for this type of diagram might be a Scenario Description Swimlane). During the script writing activity described by Libby the ‘actors’ and their ‘lines’ were mapped to a swimlane diagram drawn on a flipchart by Chris van Aart from VU helping to clarify various issues along the way.
As the name suggests, the diagram looks like a swimming pool with lanes. Each NoTube component (service, tool or system) was assigned to a lane – we started with a lane for the user interactions implied by the scenario. The activities performed by each component were represented as boxes within the relevant column and connected by arrows to show the interconnections. Our lanes were arranged vertically so that time flowed forward as you moved down the page (but they could also be laid out horizontally). So – really quick and simple to do once you have the right information: the main challenge was not to make the diagram look too messy when drawing arrows across several lanes.
The resulting diagrams provide a set of documents that show everything going on at once – at a glance – helping us to understand:
- the tools and systems involved
- how the user interacts with the various components
- which components are responsible for which activities and the flow between them
An extra bonus for me as IA was that I could use the diagrams to quickly identify the screens that now need wireframing.
As Yvonne Shek says: “The goal or differentiating factor of this diagram is to tell a story from multiple perspective, in a comprehensive and holistic way.” I’m sure I’ll be using this handy technique again in future, in particular to promote common understanding between participants of a large and distributed project such as NoTube.
Writing scripts for teasing out requirements
The Problem
We were looking for ways to bring out the full implications of our ideas for scenarios to check that they were implementable and work out how we would implement them.
This is a very common problem, and we have looked at it using various tools including writing scenarios, storyboarding and so on. We had a rough idea of the technical components we needed and what we wanted to demonstrate. But for me there was a lack of clarity about precisely how the scenarios would play out, and so we started to look at ’swimlane’ diagrams like these, to illustrate where in the architecture the action moves as the scenario plays out.
“Like a rather boring play”
These diagrams are actually pretty hard to write, but useful if you can do them, as you start to understand what components needs to talk to what and what they need to say. Danbri had an idea that we thought might help for writing them – to create a script – like a script for a rather boring play – with the technical components as well as the users as characters, to see if this would engage our storytelling faculties to help bring out the nuances.
“But the set top box just woudn’t do that”
This made for an entertaining meeting where different meeting participants took the roles of different technical components, and I played script editor, making choices where there were disputes. I think there were several benefits of using this process
- better mutual understanding of the scenario itself, including discovering more about what could and ought to happen
- better participation as different project members became champions for different components (‘yes I’m the recommender!’)
- you didn’t need to be technical to join in and the result was something that everyone can understand
- quite a fun (by EU project standards) meeting
however -
- this is a time-consuming thing to do and we didn’t really have enough time set aside
- it needs participants to be interested and care enough to join in
- it needs more careful planning than I did for it (such as a draft script written ahead of time), and a dedicated person to take notes, as Chris van Aart very kindly did in our session
It would be very interesting to talk to people creating real plays to see what we could learn from their processes.
You can read our ‘rather boring plays’ here, and I hope that Vicky will do a post shortly about the swimlanes she has created as a result of this process.
How willing are you to share data about what you watch on TV?
I’m working on NoTube as part of the BBC team, and together with Lora from VU, I’m looking into various potential privacy issues. In particular, as someone with a background in user experience, I’m interested to find out how willing people are to share information online about what they *actually* watch on TV – i.e. the type of attention data that can be counted with a Beancounter.
For example: you’ve spent years carefully cultivating and managing an online persona which reflects you in the best light – and you choose to post and tweet only about TV programmes which reinforce this persona. Given all this effort, do you really want your online contacts/friends to know that you’re also a secret fan of several ‘trashy’ TV shows – or this information that you’d rather keep to yourself?
On the other hand, how curious would you be to find out what your friends are watching (with their permission of course)? How about if you could get programme recommendations based on their tastes and preferences, combined with yours? For example, if you discovered that ten of your friends watched a programme about a subject you’re interested in that you hadn’t, might that influence you to watch it too? Yes? But how might your friends feel about sharing their TV viewing data with you?
Is what you choose to watch on TV in the privacy of your own sitting room at the end of a long day more intimately personal somehow than, say, the music you listen to, the DVDs you rent or the books you buy? And, if so, might this be because we tend to revert to ‘couch potato’ mode when we’re feeling tired and bored and need passive entertainment – when we want to indulge in the guilty pleasures of less highbrow content than we might pursue in other (more public) contexts?
The ability to share information online about programmes you’ve watched is already being made possible by experimental services such as 4iP’s Test Tube Telly and Whomwah’s twitter bot which sends details about what you are listening to and watching to the @radioandtvbot account on Twitter. Similarly Boxee allows you to match up your feed output to a twitter stream.
Do people have reservations about sharing this kind of data? If so, would the trade-off of potentially interesting programme recommendations based on friends’ viewing behaviours be worth any perceived risk of exposure? These are some questions I hope to answer during the course of this project.
I’d be interested to hear your thoughts. Please leave any comments on the blog.
Would you like to know more? [*]
I’m a representative of the BBC as one of the ‘Usecase’ partners in NoTube, and it’s my responsibility to draft a document describing one of the prototypes we want to make, combining components created by all the workpackages. We will demonstrate what we build at our project review next May, so it’s important to get it right, and having such a distributed team, clear communication of ideas inside the project is important too.
Here’s the basic idea, as described by Dan Brickley in our deliverable document draft:
Although there may never be a unified global network for TV content, there can and should be a unified global network of TV meta-content, by which we mean informally the overlay of annotations, ratings, comments, descriptions, related links and tags that can provide new means for users to inform, educate and entertain themselves online.
I’ll let Dan expand on his thoughts about this ‘NoTube Network’ in a later post, but my job is to propose a way we can show these ideas in action. Here is my current thinking, embodied in two simple scenarios:
Scenario 1: Recommendations for me on my TV
Jana wants to see recommendations based on her social activity on her TV when she gets home at night. She talks a lot on twitter and facebook about what she watches in the context of her online social life, and so do her friends, and doesn’t she see why she should have to explicitly tell any system what her preferences are. She wants to see recommendations clearly featured on the user interface of her set top box.
Scenario 2: Would you like to know more?
While watching TV, Frederik would sometimes like more information about a programme. He’d like to be able to ‘bookmark’ a programme to come back to it later and find out more about it. He doesn’t necessarily want to have his laptop open all the time during this and neither does he want to interfere with the playing of the programme too much as he often watches TV with other people in the same room.
The picture below shows the sorts of physical objects a person might want to use to fulfil these usecases, including TV, an open source set top box, a remote and a laptop – not just using their own laptop for everything, but in the context of the way most people still watch TV.
These are scenarios that will only be of immediate relevance to a relatively unusual group of people at the current time: those who commonly watch TV on their media centre, and who watch a lot of on-demand media and who heavily use social networking sites. It’s important to relate what we make to the majority of users as well, especially from my point of view given the inclusive nature of the BBC and the way it is funded.
In Scenario 2, wanting to know something more about a programme and remembering it for later is the key idea, a desire common to many TV watchers, regardless of the technologies they use. In Scenario 1, the filtering interesting programmes and bringing them to the user’s attention is the most important aspect, and one becoming increasingly relevant to all TV watchers as channels proliferate. Using a setup that replicates at least the feeling of watching TV in a living room allows us to address the most common way of watching TV and also to potentially look at face-to-face communal TV watching.
The APIs and data formats – the components that allow us to make the prototype but also specifically allow us to filter an EPG, export activity feeds, control a television and so on – are the pieces that can be reused in other user situations and can form part of the ‘NoTube Network’.
If you want to see more detail about the architecture and the prototype, you can see the requirements and description as a work in progress in the NoTube Deliverables GIT.
[*] “Would you like to know more…” is an interactive TV user interface component from the film “Starship Troopers”
Landscape sketch
When we had our first project kickoff meeting for NoTube, back in the spring, I made this list of quick sketches of TV-related characters and scenarios. They’re not very carefully modelled or the formal basis for specific project work, but they do touch on a variety of issues around the collision of ‘Web’ and ‘Television’, and I thought it worth posting them somewhere in public. Don’t read too much into the detail (eg. most of the names are quite English-y, I was aware of this but offline while writing them and stuck for naming inspiration). The basic idea was to sketch something of the present-day environment in which our project exists, and to think about how to get systems interoperating across a changing and varied landscape.
Example 1
- Alice is a facebook user
- her friend Bob is on her Facebook buddylist
- when she watches a TV show about one of their shared interests, Bob gets a notification
Example 2
- Charlie uses the YouTube site a lot, and often ‘favourites’ funny videos, as well as US politics
- when he visits TV.example.com and fills out a profile that includes his public YouTube profile, he receives recommendations for comedy and US politics content
Example 3
- Dave listens to a lot of music via last.fm
- He would like to know when there are concerts by his favourite artists, either at home or when travelling on business (eg. dopplr)
Example 4
- Eva bookmarks interesting articles every day on delicious.com or magnol.ia
- She would like these auto-classified because adding tags is boring
- and to have work-related video suggestions when in the office, recreation-related suggestions when watching IPTV at home
Example 5
- Fred hates TV. There is never anything on.
- But he is taking a distance learning course, studying History of Art at weekends.
- He would like free (CC-licensed) videos for his video iPodophone and to have relevant wikipedia pages automatically when he visits Paris.
- And he would love to have comments on these from other History of Art students, and to follow their blogs or on Facebook.
Example 6
- Georgina loves TV, but is too busy to watch a lot except during daily 2h commute by train.
- She prefers news and current affairs, and to argue about politics with colleagues, friends and family.
- She spends at least 1/2 hour a day using podcast audio or video content. Most days she re-posts something in her blog, with short (and funny) comments.
Example 7
- Hannah is a nuclear scientist, a graduate of http://rocketscience.example.edu/
- She secretly wishes she could comment on TV stories and news articles about nuclear issues, and have her comments appear at the top because she knows what she’s talking about.
- …but feels this is somehow elitist, so does not mention it.
Example 8
- Ian just wants some background music videos to play while doing the housework.
- He’d be happy if the computer picked the music for him, mixing stuff he likes with stuff he might like.
- But if it accidentally plays any Jazz… Ugh! Game over!
Example 9
- Joyce is a bit uncomfortable with the Internet, of hackers, viruses and chain letters.
- One time she saw an advert that mentioned the small town she lived in, and some of her hobbies.
- She didn’t like this.
Example 10
- Kristian is a family history enthusiast. He built a database of 8 generations of his family, on a popular geneology site.
- He says he’s no good with computers, but has recently built a map that includes free historical video material of life in the cities his great- grandparents grew up in.
- He loves showing this to the kids, to remind them of where they came from. He wonders if the Web site will exist in 10 years.
Example 11
- Luis prefers to sit back and just watch TV “on the TV”, no fancy stuff.
- When he’s tired, he wishes more of his favourite shows had subtitles in Spanish.
- His sister mentioned you can “get those on the Internet” but he has no idea where to begin.
Example 12
- Martina is planning a holiday, is thinking of south-east Asia somewhere, and is looking for TV travel shows online to inspire her to save & plan.
- She does some Web searches for travel videos, but doesn’t find anything much.
- She hasn’t really picked a country and wonders what search terms to use.
- Once she even clicked on an advert.
Example 13
- Nigel is a sports fan. Well, football fan.
- If anything is on TV or radio about his favourite team, he wants to be emailed or IM’d, immediately.
- But if you spoil an unwatched match by telling him the final score, he will be very very upset and angry.
Example 14
- Olivia is travelling to London for the Olympics.
- She knows she can watch videos on her phone, and that is kind of cool, but she’d rather have a schedule for events on her phone, and also reminders about highlights to watch on her friend’s giant flat-screen TV
Example 15
- Pat is convinced that 9/11 was a sinister plot by the illuminati and space-reptiles from Mars.
- Given any opportunity to comment in online fora, he will share these observations with any audience; the bigger the better. After a few beers he is a bit racist too.
- He wonders why nobody seems to read the comments he leaves on Facebook, YouTube, BBC etc. videos. Suspects a plot.
Example 16
- Rachel is a big fan of BlahBlah, a popular sci-fi series.
- She mentions this in her public Hi5 and Orkut.com profiles.
- Sometimes when she visits online TV sites and logs in using her Orkut OpenID, she is pleasantly suprised when it recommends similar TV shows without asking.
Example 17
- Sam loves books, and often writes reviews on Amazon.com; also has a length wishlist.
- After writing a 5-star review of a great book, she wonders why the Internet can’t
- remind her when this writer is about to be on TV. Or even at a book signing nearby.
- She wonders if this might also be a bit creepy, but expects it will happen someday anyhow. Would people who bookmarked her reviews also get notified?
Example 18
- Tom is pretty open-minded, but worried about what his young kids might find in the huge catalogue of his new IPTV service
- He doesn’t want to let “a bunch of religious nutters who set the ratings” decide what his kids watch.
- He thinks out loud “if my friends reckon something is OK for their kids”, it’s probably fine. “…but there are 1000s of shows… Hmm!”
Example 19
- Uncle Jim filmed a major train accident on his phone just now.
- He wants to send it on to news agencies, and dreams he will get rich from syndication profits.
- …but he is happy for it to be re-used non- commercially, and included in Wikipedia. He wants to be emailed if anyone comments on it, or re-publishes it, anywhere.
Example 20
- V. prefers radio to TV, but uses her laptop for both lately. She never reads listing magazines, and vaguely suspects she is missing out on the good stuff that’s on.
- She is open to suggestions from friends, about what to watch or listen to.
- They all use different Web sites for this kind of thing, or only use email. A couple of friends use MySpace obsessively.
Example 21
- Will is a fictional developer at the BBC
- He’s been asked to see if comments on pieces of BBC content around the Web can be re-aggregated to provide a unified view
- But to bear in mind legal and policy issues
Example 22
- Zelda doesn’t have a TV, phone, video, PC, or Blackberry. Her radio is broken too.
- Every week she prints out 7 days TV listings the community at the community centre, and visits a friend when something good is on TV.
- She would like to save paper and print full info only the things that are interesting to her – movies, soaps, news, but not sport or reality shows.
Example 23
- Anna is has obsessive knowledge of the popular soap series called Blahblah.
- She knows 20 years history of the characters, families and plot.
- She notices some inconsistencies in the Web site for the show, but never got a reply to her email about it.
Awareness not paranoia
In her previous post Libby asks whether you might see NoTube’s Beancounter, which lets you “discover you what you watch and listen to – and the overall categories of things that you like”, as an invasion of your privacy.
Photo
During the course of the NoTube project we will be investigating ways of supporting users in understanding and managing privacy issues when data from various sources is merged about them. Many people have become used to being quite open with their data on sites such as Facebook but might not realise the implications of this openness when these “walled gardens” are opened up. Expressing this to people without scaring them is very hard.
With the user’s permission Beancounter collects, stores and analyses attention data from various sources (such as “Libby watched BBC Question Time on BBC1″), enhancing this data by linking it to other data. It then produces a machine-readable profile of your interests and contacts, which can be used to generate personalised content recommendations. The idea is to combine fragmented data around the Web to allow the user to make use of it.
As our BBC colleagues pointed out in their excellent linked data London presentation, Beancounter-like applications act in some ways rather like a Tesco clubcard database – with the significant difference that the data is under the user’s control rather than that of a company. But its use of multiple sources of information, the opportunity for the user to re-broadcast the combination of these sources, and the potential for combining data about other people, means that there are important privacy implications not covered by a straightforward privacy policy.
So far we have identified four key aspects of the Beancounter that pose interesting new research questions relating to privacy.
- Aggregation of users’ previously unconnected data: Can existing privacy policies from the original sources of the attention data (applications such as Twitter for example) be transferred over to new sets of aggregated data? Can new privacy policies be defined based on existing ones in the original applications? Can the privacy policies of the existing applications be preserved and altered to fit the aggregated data?
- Enrichment of users’ data by linking it to other publically available data: How can we best maintain user awareness of the potential privacy risks when creating new links between data? How should we guide the user in defining privacy strategies for such enriched data?
- Statistics: How do we to help users to manage the sharing of their personal data analytics, given that the statistics might reveal things that people might prefer to keep confidential? How do we best present the statistics so that users understand the added value for them with respect to future recommendations?
- Control: How can the user maintain control over the use of their data, restricting how it can be reused, in commercial and non-commercial scenarios?
These questions are not just about NoTube Beancounters but about any application that merges or connects public data – or in the more difficult case, merges private and public data and re-broadcasts it. Data aggregation can impact directly on the user. Consider a calendar-sharing application in which you can see your friends’ private calendars and which then merges the data from them into a composite social calendar for you. If you were to then make your composite calendar public, you would probably be broadcasting your friends’ personal data about their location and activities that they wouldn’t wish to be publically known; and worse, you might by linking the data derive a new, unwelcome and private piece of knowledge. Here’s a jokey but throught-provoking example from twitter a couple of days ago:
“Both @jonronson @AIannucci claiming to be in Oslo at the same time. Hope this extra-marital affair goes well, boys.” link
Or consider the following case directly relevant to TV: someone connects their TV to their private stash of illegally downloaded movies and also to twitter, and then twitter broadcasts the fact that they watched something they could not legally have watched with precise time and device information. There we have a new link created betweeen the person, the movie and the time, which provides evidence that they have done something illegal.
Assessing and managing privacy in everyday life is an intuitive process. As the sociologist Erving Goffman has described, the front you present is not only tailored to the pertinent audience but also to the context (for example, whether you are at work or at home) and it determines the amount of information you are willing to disclose to the audience. Many of our intuitions are not applicable to new cases where our data is combined and re-broadcast, even if we have control over it, and particularly when we do not have a good understanding of the capabilities of software and the potential consequences of using it. If we are to venture into these kinds of areas, we need to help people develop good intuitions about their privacy when using these services. This is difficult:
- People find it very difficult to think about privacy in an abstract way and perceptions of privacy vary across nations and cultures. For example, people in India are much more comfortable about giving out personal details on social networks than people in America. (Source: Synovate 2008, Social Network Users)
- People systematically underestimate privacy risks online: many users never customise their privacy settings at all but just stick with the defaults, as confirmed in a recent UK Office of Communications survey.
- Reassuring people about online privacy tends to make them more, not less, concerned. The results of a series of experiments conducted by Carnegie Mellon University showed that people who were reminded about privacy were less likely to reveal personal information than those who were not.
- Privacy settings could have complex and numerous consequences and it is difficult to predict all of them. MIT’s Gaydar project is recent example of how personal information can be shared inadvertently.
As we test and develop user experience solutions to these challenges during the coming months we‘ll report back on our findings here.
Why beans need counting
What if you knew what you actually liked, as opposed to what you think you like? would this be interesting or welcome – or would you see it is invading your privacy?
Increasing automation means that lots of data is available about what you do, including what you watch, and listen to. This means that you or I – or companies or researchers – can ‘mine’ information about your activities and use them to make predictions about what you might like, and what they might be able to sell you.
NoTube Beancounter will be a way for you to discover you what you watch and listen to – and the overall categories of things that you like. It will put the control about what sources can be mined in your hands – and limit what companies can do with the outputs.
Update: Here’s the presentation (pdf) we gave on beancounter at the first linked data meeting in London.
NoTube second project meeting
After an interesting second meeting in Gargonza, Italy, project partners are currently planning the next three months’ work.
leave a comment