Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

November 2, 2015

Do one thing…

Filed under: Interface Research/Design,Linux OS,UX — Patrick Durusau @ 8:30 am

Do one thing… I don’t want barely distinguishable tools that are mediocre at everything; I want tools that do one thing and do it well. by Mike Loukides.

From the post:

I’ve been lamenting the demise of the Unix philosophy: tools should do one thing, and do it well. The ability to connect many small tools is better than having a single tool that does everything poorly.

That philosophy was great, but hasn’t survived into the Web age. Unfortunately, nothing better has come along to replace it. Instead, we have “convergence”: a lot of tools converging on doing all the same things poorly.

The poster child for this blight is Evernote. I started using Evernote because it did an excellent job of solving one problem. I’d take notes at a conference or a meeting, or add someone to my phone list, and have to distribute those files by hand from my laptop to my desktop, to my tablets, to my phone, and to any and all other machines that I might use.
…

Mike takes a stick to Evernote, Gmail, Google Maps, Skype, Twitter, Flickr, Dropbox (insert your list of non-single purpose tools here), etc.

Then he offers a critical insight about web applications:

…There’s no good way to connect one Web application to another. Therefore, everything tends to be monolithic; and in a world of monolithic apps, everyone wants to build their own garden, inevitably with all the features that are in all the other gardens.

Mike mentions IFTTT, which connects web services but wants something a bit more generic.

I think of IFTTT as walkways between a designated set of walled gardens. Useful for traveling between walled gardens but not anything else.

Mike concludes:

I don’t want anyone’s walled garden. I’ve seen what’s inside the walls, and it isn’t a palace; it’s a tenement. I don’t want barely distinguishable tools that are mediocre at everything. I want tools that do one thing, and do it well. And that can be connected to each other to build powerful tools.

What single purpose tool are you developing?

How will it interact with other single purpose tools?

Interactive visual machine learning in spreadsheets

Filed under: Interface Research/Design,Machine Learning,Spreadsheets,Visualization — Patrick Durusau @ 7:59 am

Interactive visual machine learning in spreadsheets by Advait Sarkar, Mateja Jamnik, Alan F. Blackwell, Martin Spott.

Abstract:

BrainCel is an interactive visual system for performing general-purpose machine learning in spreadsheets, building on end-user programming and interactive machine learning. BrainCel features multiple coordinated views of the model being built, explaining its current confidence in predictions as well as its coverage of the input domain, thus helping the user to evolve the model and select training examples. Through a study investigating users’ learning barriers while building models using BrainCel, we found that our approach successfully complements the Teach and Try system [1] to facilitate more complex modelling activities.

To assist users in building machine learning models in spreadsheets:

The user should be able to critically evaluate the quality, capabilities, and outputs of the model. We present “BrainCel,” an interface designed to facilitate this. BrainCel enables the end-user to understand:

  1. How their actions modify the model, through visualisations of the model’s evolution.
  2. How to identify good training examples, through a colour-based interface which “nudges” the user to attend to data where the model has low confidence.
  3. Why and how the model makes certain predictions, through a network visualisation of the k-nearest neighbours algorithm; a simple, consistent way of displaying decisions in an arbitrarily high-dimensional space.

A great example of going where users are spending their time, spreadsheets, as opposed to originating new approaches to data they already possess.

To get a deeper understanding of the Sarkar’s approach to users via spreadsheets as an interface, see also:

Spreadsheet interfaces for usable machine learning by Advait Sarkar.

Abstract:

In the 21st century, it is common for people of many professions to have interesting datasets to which machine learning models may be usefully applied. However, they are often unable to do so due to the lack of usable tools for statistical non-experts. We present a line of research into using the spreadsheet — already familiar to end-users as a paradigm for data manipulation — as a usable interface which lowers the statistical and computing knowledge barriers to building and using these models.

Teach and Try: A simple interaction technique for exploratory data modelling by end users by Advait Sarkar, Alan F Blackwell, Mateja Jamnik, Martin Spott.

Abstract:

The modern economy increasingly relies on exploratory data analysis. Much of this is dependent on data scientists – expert statisticians who process data using statistical tools and programming languages. Our goal is to offer some of this analytical power to end-users who have no statistical training through simple interaction techniques and metaphors. We describe a spreadsheet-based interaction technique that can be used to build and apply sophisticated statistical models such as neural networks, decision trees, support vector machines and linear regression. We present the results of an experiment demonstrating that our prototype can be understood and successfully applied by users having no professional training in statistics or computing, and that the experience of interacting with the system leads them to acquire some understanding of the concepts underlying exploratory statistical modelling.

Sarkar doesn’t mention it but while non-expert users lack skills with machine learning tools, they do have expertise with their own data and domain. Data/domain expertise that is more difficult to communicate to an expert user than machine learning techniques to the non-expert.

Comparison of machine learning expert vs. domain data expert analysis lies in the not too distant and interesting future.

I first saw this in a tweet by Felienne Hermans.

Announcing Gephi 0.9 release date

Filed under: Gephi,Graphs,Visualization — Patrick Durusau @ 7:02 am

Announcing Gephi 0.9 release date by Mathieu Bastian.

From the post:

Gephi has an amazing community of passionate users and developers. In the past few years, they have been very dedicated creating tutorials, developing new plugins or helping out on GitHub. They also have been patiently waiting for a new Gephi release! Today we’re happy to share with you that the wait will come to an end December 20th with the release of Gephi 0.9 for Windows, MacOS X and Linux.

We’re very excited about this upcoming release and developers are hard at work to deliver its roadmap before the end of 2015. This release will resolve a serie of compatibility issues as well as improve features and performance.

Our vision for Gephi remains focused on a few fundamentals, which were already outlined in our Manifesto back in 2009. Gephi should be a software for everyone, powerful yet easy to learn. In many ways, we still have the impression that we’ve only scratched the surface and want to continue to focus on making each module of Gephi better. As part of this release, we’ve undertaken one of the most difficult project we’ve worked on and completely rewrote the core of Gephi. Although not very visible for the end-user, this brings new capabilities, better performance and a level of code quality we can be proud of. This ensure a very solid foundation for the future of this software and paves the way for a future 1.0 version.

Below is an overview of the new features and improvements the 0.9 version will bring.

The list of highlights includes:

  • Java and MacOS compatibility
  • New redeveloped core
  • New Appearance module
  • Timestamp support
  • GEXF 1.3 support
  • Multiple files import
  • Multi-graph support (visualization n a future release)
  • New workspace selection UI
  • Giphi Toolkit release (soon after 0.9)

Enough new features to keep you busy over the long holiday season!

Enjoy!

November 1, 2015

Locked doors, headaches, and intellectual need (teaching monads)

Filed under: Education,Functional Programming,Teaching,Topic Maps — Patrick Durusau @ 8:34 pm

Locked doors, headaches, and intellectual need by Max Kreminski.

From the post:

…
I was first introduced to the idea of problem-solution ordering issues by Richard Lemarchand, one of my game design professors. The idea stuck with me, mostly because it provided a satisfying explanation for a certain confusing pattern of player behavior that I’d witnessed many times in the past.

Here’s the pattern. A new player jumps into your game and starts bouncing around your carefully crafted tutorial level. The level funnels them to the key, which they collect, and then on to the corresponding locked door, which they successfully open. Then, somewhere down the road, they encounter a second locked door… and are completely stumped. They’ve solved this problem once before – why are they having such a hard time solving it again?

What we have here is a problem-solution ordering issue. Because the player got the key in the first level before encountering the locked door, they never really formed an understanding of the causal link between “get key” and “open door”. They got the key, and then some other stuff happened, and then they reached the door, and were able to open it; but “acquiring the key” and “opening the door” were stored as two separate, disconnected events in the player’s mind.

If the player had encountered the locked door first, tried to open it, been unable to, and then found the key and used it to open the door, the causal link would be unmistakable. You use the key to open the locked door, because you can’t open the locked door without the key.

This problem becomes a lot more obvious when you don’t call the key a key, or when the door doesn’t look like a locked door. The “key/door” metaphor is widely understood and frequently used in video games, so many players will assume that you use a key to open a locked door even if your own game doesn’t do a great job of teaching them this fact. But if the “key” is really a thermal detonator and the “door” is really a power generator, a lot of players are going to wind up trying to destroy the second generator they encounter by whacking it ineffectually with a sword.
…

Max goes on to apply problem-solution ordering to teaching both math and monads.

I don’t recall seeing or writing any topic map materials that started with concrete problems that would be of interest to the average user.

Make no mistake, there were always lots of references to where semantic confusion was problematic but that isn’t the same as starting with problems a user is likely to encounter.

The examples and literature Max points to makes me interested in started with concrete problems topic maps are good at solving and then introducing topic map concepts as necessary.

Suggestions?

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