Archive for the ‘Communication’ Category

Data Storytelling: The Ultimate Collection of Resources

Saturday, April 20th, 2013

Data Storytelling: The Ultimate Collection of Resources by Zach Gemignani.

From the post:

The hot new concept in data visualization is “data storytelling”; some are calling it the next evolution of visualization (I’m one of them). However, we’re early in the discussion and there are more questions than answers:

  • Is data storytelling more than a catchy phrase?
  • Where does data storytelling fit into the broader landscape of data exploration, visualization, and presentation?
  • How can the traditional tools of storytelling improve how we communicate with data?
  • Is it more about story-telling or story-finding?

Many of the bright minds in the data visualization field have started to tackle these questions — and it is something that we’ve been exploring at Juice in our work. Below you’ll find a collection of some of the best blog posts, presentations, research papers, and other resources that take on this topic.

I count ten (10) blog posts, four (4) presentations, five (5) papers and eight (8) tools, examples and other resources.

Get yourself a fresh cup of coffee. You are going to be here a while.

PS: I don’t know that “data storytelling” is new or if the last century or so suffered a real drought in “data storytelling.”

Medieval cathedrals were exercises in storytelling but a modern/literate audience fails to appreciate them as designed.

When Presenting Your Data…

Saturday, March 30th, 2013

When Presenting Your Data, Get to the Point Fast by Nancy Duarte.

From the post:

Projecting your data on slides puts you at an immediate disadvantage: When you’re giving a presentation, people can’t pull the numbers in for a closer look or take as much time to examine them as they can with a report or a white paper. That’s why you need to direct their attention. What do you want people to get from your data? What’s the message you want them to take away?

Data slides aren’t really about the data. They’re about the meaning of the data. And it’s up to you to make that meaning clear before you click away. Otherwise, the audience won’t process — let alone buy — your argument.

Nancy starts off with a fairly detailed table full of numbers, that is less complex than some topic map diagrams I have seen. ;-)

Moves onto the infamous pie chart* and then to a bar chart.

The lesson being to present information in a way it can be immediately comprehended by your audience.

Here’s a non-topic map illustration, explaining time dilation:

Time Dilation

Here’s another explanation of time dilation:

Time Dilation

Both “explain” time dilation but one to c-suite types and the other to techies.

Problem: C-suite types control the purse strings.

Question: What issues do c-suite types see that topic maps can address?


*Leland Wilkinson in The Grammar of Graphics, 2nd ed., writes of pie charts:

A pie chart is perhaps the most ubiquitous of modern graphics. It has been reviled by statisticians (unjustifiably) and adored by managers (unjustifiably).

So far (I am at chapter 3), Wilkinson doesn’t elaborate on his response to criticisms of pie charts by statisticians.

Not important for this discussion but one of those tidbits that livens up a classroom discussion.

I first saw this in a tweet by Gregory Piatetsky.

….Like A Child’s Story Book [Visual Storytelling]

Wednesday, March 27th, 2013

Articulating Your Content Strategy Like A Child’s Story Book by Michael Brito.

From the post:

I used to read “Love You Forever” to both of my girls when they were little. Even thinking about it today, I still get choked up. It’s really a heartfelt story. What I remember the most about it is that it uses imagery to tell a very significant story (as with most children’s books). The story is about a mother’s unconditional love for her son; and then chronicles her son’s life growing to an adult and starting his own family. The sad conclusion shows how he reciprocates his love to his mother who has grown to be an elderly woman. There are just a few sentences on each page but the story and illustration is powerful and you can even follow along without even reading the text.

Michael makes a great case for visual storytelling and includes a Slideshare presentation by Stefanos Karagos to underline his point.

Before you view the slides!

Ask yourself what percent of users have a great experience with your product?

The slides reveal what percent of users share your opinion.

I doubt you have noticed that I am really a “text” sort of person. ;-)

The lesson here isn’t any more foreign to you than it is to me.

But I think the author has a very good point, assuming our goal is to communicate with others.

Can’t communicate with others as we would like for them to be.

At least not successfully.

FORCE 11

Thursday, March 21st, 2013

FORCE 11

Short description:

Force11 (the Future of Research Communications and e-Scholarship) is a virtual community working to transform scholarly communications toward improved knowledge creation and sharing. Currently, we have 315 active members.

A longer description from the “about” page:

Research and scholarship lead to the generation of new knowledge. The dissemination of this knowledge has a fundamental impact on the ways in which society develops and progresses; and at the same time, it feeds back to improve subsequent research and scholarship. Here, as in so many other areas of human activity, the Internet is changing the way things work: it opens up opportunities for new processes that can accelerate the growth of knowledge, including the creation of new means of communicating that knowledge among researchers and within the wider community. Two decades of emergent and increasingly pervasive information technology have demonstrated the potential for far more effective scholarly communication. However, the use of this technology remains limited; research processes and the dissemination of research results have yet to fully assimilate the capabilities of the Web and other digital media. Producers and consumers remain wedded to formats developed in the era of print publication, and the reward systems for researchers remain tied to those delivery mechanisms.

Force11 is a community of scholars, librarians, archivists, publishers and research funders that has arisen organically to help facilitate the change toward improved knowledge creation and sharing. Individually and collectively, we aim to bring about a change in modern scholarly communications through the effective use of information technology. Force11 has grown from a small group of like-minded individuals into an open movement with clearly identified stakeholders associated with emerging technologies, policies, funding mechanisms and business models. While not disputing the expressive power of the written word to communicate complex ideas, our foundational assumption is that scholarly communication by means of semantically enhanced media-rich digital publishing is likely to have a greater impact than communication in traditional print media or electronic facsimiles of printed works. However, to date, online versions of ‘scholarly outputs’ have tended to replicate print forms, rather than exploit the additional functionalities afforded by the digital terrain. We believe that digital publishing of enhanced papers will enable more effective scholarly communication, which will also broaden to include, for example, the publication of software tools, and research communication by means of social media channels. We see Force11 as a starting point for a community that we hope will grow and be augmented by individual and collective efforts by the participants and others. We invite you to join and contribute to this enterprise.

Force11 grew out of the FORC Workshop held in Dagstuhl, Germany in August 2011.

FORCE11 is a movement of people interested in furthering the goals stated in the FORCE11 manifesto. An important part of our work is information gathering and dissemination. We invite anyone with relevant information to provide us links which we may include on our websites. We ask anyone with similar and/or related efforts to include links to FORCE11. We are a neutral information market, and do not endorse or seek to block any relevant work.

The Tools and Resources page is particularly interesting.

Current divisions are:

  • Alternative metrics
  • Author Identification
  • Annotation
  • Authoring tools
  • Citation analysis
  • Computational Linguistics/Text Mining Efforts
  • Data citation
  • Ereaders
  • Hypothesis/claim-based representation of the rhetorical structure of a scientific paper
  • Mapping initiatives between ontologies
  • Metadata standards and ontologies
  • Modular formats for science publishing
  • Open Citations
  • Peer Review: New Models
  • Provenance
  • Publications and reports relevant to scholarly digital publication and data
  • Semantic publishing initiatives and other enriched forms of publication
  • Structured Digital Abstracts – modeling science (especially biology) as triples
  • Structured experimental methods and workflows
  • Text Extraction

Topic maps fit into communication agendas quite easily.

The first step in communication is capturing something to say.

The second step in communication is expressing what has been captured so it can be understood by others (or yourself next week).

Topic maps do both quite nicely.

I first saw this in a tweet by Anita de Waard.

See What I Mean: How to Use Comics to Communicate Ideas

Friday, February 8th, 2013

Win This Book! See What I Mean: How to Use Comics to Communicate Ideas by Josh Tyson.

From the post:

Here, Cheng talks about the parallels between comics and UX, the joys of drawing, and the power of comics in getting your point across. You can enter to win a copy of the book below.

Comics and UX share the common struggle of having had to work extra hard at being taken seriously. Do you hear similar complaints from folks working in both fields?

I do. Obviously, UX design has become much more mainstream in the past five years and doesn’t have the same struggles it used to. The discipline is taken seriously now but perhaps still misunderstood.

Comics have long existed in more serious contexts—in film as storyboards, for instance—but I’m seeing more and more examples of comics being used in other industries, though many of these examples also feel misunderstood. The medium is often treated as a solution for reaching younger audiences or making something more light-hearted, but it doesn’t have to be constrained to that.

Go to the original post for a chance to win a copy of See What I Mean: How to Use Comics to Communicate Ideas.

Topic map comics anyone? ;-)

Should We Focus on User Experience?

Friday, September 14th, 2012

Should We Focus on User Experience? by Koen Claes.

From the post:

In the next seven minutes or so, this article hopes to convince you that our current notion of UX design mistakenly focuses on experience, and that we should go one step further and focus on the memory of an experience instead.

Studies of behavioral economics have changed my entire perspective on UX design, causing me to question basic tenets. This has led to ponderings like: “Is it possible that trying to create ‘great experiences’ is pointless?” Nobel Prize-winning research seems to hint that it is.

Via concrete examples, additional research sources, and some initial how-to tips, I aim to illustrate why and how we should recalibrate our UX design processes.

You will also like the narrative (with addition resources) from Koen’s presentation at IA Summit 2011, On Why We Should NOT Focus on UX.

The more I learn about the myriad aspects of communcation, the more I am amazed that we communicate at all. ;-)

The Curse Of Knowledge

Wednesday, August 29th, 2012

The Curse Of Knowledge by Mark Needham.

From the post:

My colleague Anand Vishwanath recently recommended the book ‘Made To Stick‘ and one thing that has really stood out for me while reading it is the idea of the ‘The Curse Of Knowledge’ which is described like so:

Once we know something, we find it hard to imagine what it was like not to know it. Our knowledge has “cursed” us. And it becomes difficult for us to share out knowledge with others, because can’t readily re-create our listeners’ state of mind.

This is certainly something I imagine that most people have experienced, perhaps for the first time at school when we realised that the best teacher of a subject isn’t necessarily the person who is best at the subject.

I’m currently working on an infrastructure team and each week every team does a mini showcase where they show the other teams some of the things they’ve been working on.

It’s a very mixed audience – some very technical people and some not as technical people – so we’ve found it quite difficult to work out how exactly we can explain what we’re doing in a way that people will be able to understand.

A lot of what we’re doing is quite abstract/not very visible and the first time we presented we assumed that some things were ‘obvious’ and didn’t need an explanation.
….

Sounds like a problem that teachers/educators have been wrestling with for a long time.

Read the rest of Mark’s post, then find a copy of Made to Stick.

And/or, find a really good teacher and simply observe them teaching.

Heavy use of equations impedes communication among biologists

Thursday, June 28th, 2012

Heavy use of equations impedes communication among biologists by Tim W. Fawcett and Andrew D. Higginson. (Proceedings of the National Academy of Sciences, June 25, 2012 DOI: 10.1073/pnas.1205259109)

Abstract:

Most research in biology is empirical, yet empirical studies rely fundamentally on theoretical work for generating testable predictions and interpreting observations. Despite this interdependence, many empirical studies build largely on other empirical studies with little direct reference to relevant theory, suggesting a failure of communication that may hinder scientific progress. To investigate the extent of this problem, we analyzed how the use of mathematical equations affects the scientific impact of studies in ecology and evolution. The density of equations in an article has a significant negative impact on citation rates, with papers receiving 28% fewer citations overall for each additional equation per page in the main text. Long, equation-dense papers tend to be more frequently cited by other theoretical papers, but this increase is outweighed by a sharp drop in citations from nontheoretical papers (35% fewer citations for each additional equation per page in the main text). In contrast, equations presented in an accompanying appendix do not lessen a paper’s impact. Our analysis suggests possible strategies for enhancing the presentation of mathematical models to facilitate progress in disciplines that rely on the tight integration of theoretical and empirical work.

I first saw this in Scientists Struggle With Mathematical Details, Study by Biologists Finds, where Higginson remarks on one intermediate solution:

Scientists need to think more carefully about how they present the mathematical details of their work. The ideal solution is not to hide the maths away, but to add more explanatory text to take the reader carefully through the assumptions and implications of the theory.

An excellent suggestion, considering that scientists don’t speak to each other in notation but in less precise natural language.

From Classical to Quantum Shannon Theory

Friday, June 22nd, 2012

From Classical to Quantum Shannon Theory by Mark M. Wilde

Abstract:

The aim of this book is to develop “from the ground up” many of the major, exciting, pre- and post-millenium developments in the general area of study known as quantum Shannon theory. As such, we spend a significant amount of time on quantum mechanics for quantum information theory (Part II), we give a careful study of the important unit protocols of teleportation, super-dense coding, and entanglement distribution (Part III), and we develop many of the tools necessary for understanding information transmission or compression (Part IV). Parts V and VI are the culmination of this book, where all of the tools developed come into play for understanding many of the important results in quantum Shannon theory.

From Chapter 1:

You may be wondering, what is quantum Shannon theory and why do we name this area of study as such? In short, quantum Shannon theory is the study of the ultimate capability of noisy physical systems, governed by the laws of quantum mechanics, to preserve information and correlations. Quantum information theorists have chosen the name quantum Shannon theory to honor Claude Shannon, who single-handedly founded the fi eld of classical information theory, with a groundbreaking 1948 paper [222]. In particular, the name refers to the asymptotic theory of quantum information, which is the main topic of study in this book. Information theorists since Shannon have dubbed him the “Einstein of the information age.”1 The name quantum Shannon theory is fit to capture this area of study because we use quantum versions of Shannon’s ideas to prove some of the main theorems in quantum Shannon theory.

This is of immediate importance if you are interested in current research in information theory. Of near-term importance if you are interested in practical design of algorithms for quantum information systems.

Scale, Structure, and Semantics

Monday, June 11th, 2012

Scale, Structure, and Semantics by Daniel Turkelang.

From the post:

This morning I had the pleasure to present a keynote address at the Semantic Technology & Business Conference (SemTechBiz). I’ve had a long and warm relationship with the semantic technology community — especially with Marco Neumann and the New York Semantic Web Meetup.

To give you a taste of the slides:

1. Knowledge representation is overrated.

2. Computation is underrated.

3. We have a communication problem.

I find it helpful to think of search/retrieval as asynchronous conversation.

If I can’t continue or find my place in or know what a conversation is about, there is a communication problem.

Stop Labeling Everything as an Impedance Mismatch!

Monday, June 4th, 2012

Stop Labeling Everything as an Impedance Mismatch! by Jos Dirksen (DZone Java Lobby).

Jos writes:

I recently ran across an article that was talking (again) about the Object-Relational mismatch. And just like in many articles this mismatch is called the Object-Relational Impedance mismatch. This “impedance mismatch” label isn’t just added when talking about object and relational databases, but pretty much in any situation where we have two concepts that don’t match nicely:

As someone who has abused “semantic impedance” in the past (and probably will in the future), this caught my eye.

Particularly because Jos goes on to say:

…In the way we use it impedance mismatch sounds like a bad thing. In electrical engineering it is just a property of an electronic circuit. In some circuits you might need to have impedance matching, in others you don’t.

Saying we have an object relation impedance mismatch doesn’t mean anything. Yes we have a problem between the OO world and the relation world, no discussion about that. Same goes for the other examples I gave in the beginning of this article. But labelling it with the “impedance mismatch” doesn’t tell us anything about the kind of problem we have. We have a “concept mismatch”, a “model mismatch”, or a “technology mismatch”.

That impedance, a property of every circuit, doesn’t tell us anything, is the important point.

Just as “semantic impedance” doesn’t tell us anything about the nature of the “impedance.”

Or possible ways to reduce it.

Suggestion: Let’s take “semantic impedance” as a universal given.

Next question: What can we do to lessen it in specific situations? With enough details, that’s a question we may be able to answer, in part.

All Presentation Software is Broken

Thursday, May 17th, 2012

All Presentation Software is Broken by Ilya Grigorik.

From the post:

Whenever the point I’m trying to make lacks clarity, I often find myself trying to dress it up: fade in the points, slide in the chart, make prettier graphics. It is a great tell when you catch yourself doing it. Conversely, I have yet to see a presentation or a slide that could not have been made better by stripping the unnecessary visual dressing. Simple slides require hard work and a higher level of clarity and confidence from the presenter.

All presentation software is broken. Instead of helping you become a better speaker, we are competing on the depth of transition libraries, text effects, and 3D animations. Prezi takes the trophy. As far as I can tell, it is optimized for precisely one thing: generating nausea.

Next Presentation Platform: Browser

If you want your message to travel, then the browser is your (future) presentation platform of choice. No proprietary formats, no conversion nightmares, instant access from billions of devices, easy sharing, and more. Granted, the frameworks and the authoring tools are still lacking, but that is only a matter of time.

Unfortunately, we are off to a false start. Instead of trying to make the presenter more effective, we are too busy trying to replicate the arsenal of useless visual transitions with the HTML5, CSS3 and WebGL stacks. Spinning WebGL cubes and CSS transitions make for a fun technology demo but add zero value – someone, please, stop the insanity. We have web connectivity, ability to build interactive slides, and get realtime feedback and analytics from the audience. There is nothing to prove by imitating the broken features of PowerPoint and Keynote, let’s leverage the strengths of the web platform instead. (emphasis added)

Imagine that. Testing your slides. Sounds like testing software before it is released to paying customers.

Test your slides on a real audience before a conference or meeting with your board or important client. What a novel concept.

By “real audience” I mean someone other than yourself or one of your office mates.

When you are tempted to say, “they just don’t understand….,” substitute, “I didn’t explain …. well.” (Depends on whether you want to feel smart or be an effective communicator. Your call.)

Presentation software isn’t fixable.

Presenters on the other hand, maybe.

But you have to fix yourself, no one can do it for you.

Conceptual colors, negative proportions, mysterious axes, and all that

Saturday, March 10th, 2012

Conceptual colors, negative proportions, mysterious axes, and all that

Junk Charts asks a serious question about the use of color for race representation but also has the oddest graphic I have seen in some time.

In other words, since the last time I looked at Junk Charts. It is a great site.

I report this graphic for your amusement and/or more serious discussion of the use of color for race representation.

Good graphics don’t guarantee communication but bad graphics…, you know that part.

“Big Data” and the Failure to Communicate…

Wednesday, November 16th, 2011

“Big Data” and the Failure to Communicate… by Richard Murnane.

From the post:

All the talk about “Big Data” reminds me of a line or two from an old movie I like, “What we have here is failure to communicate” (Cool Hand Luke, 1967). Why? Well, we’re all talking about a concept which means different things to different people. To make things worse, the press and all the technology vendors are trying to figure this out before the people who need to operationally deal with this “Big Data” every day know what the heck is going on.

The fact is that “Big Data” is in the air and there is no denying that something is up and we all need to grow up and figure this out. The following chart is a Google Trends snapshot comparing “Big Data” to another common (but mature) IT term, “Network Security.” Notice that a year ago “Big Data” was essentially non-existent as something people were searching Google for and now it’s getting about 50% the activity as this much more common term.

You will enjoy the post and it has much to offer but I do have one small niggle. Well, maybe not small, medium? That not right either, let’s just say really, really big and let it go at that:

Richard says “Big Data” “…means different things to different people.”

What he fails to say, is that the data “inside” big data has the same issue of meaning different things to different people.

Processing (outside of a topic map or other semantically nuanced application) requires us to treat data as having one and only meaning. We may actually view or consider some data to have only one meaning. But our viewing or processing data as having only one meaning doesn’t make it so.

Data can have at least as many meanings as there are users to process or view it. (Allowing for users who ascribe multiple meanings to the same data. Post-modernists for the most part.)