So Google has unveiled its eBook store, setting itself up to compete with Amazon, Barnes&Noble, and everyone else selling books. Google offers its editions through the browser and on a range of devices such as Android phones and the iPad. The reading experience on the browser on my laptop was OK: not great, but the text was legible enough, and would even switch to a two-page layout in a wide window. On the iPad, Google offers two choices: the browser, and a free app. The browser interface implements a swipe gesture for page turning, although there is no visible indication that it’s possible, nor any visual feedback until the page flips. The iPad app sports an animated page turning transition, but does not have a two-page mode.

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Thanks to Mor Namaan, I came across an interesting blog post by Justin O’Beirne that analyzed the graphic design of several different maps — Google, Bing, and Yahoo — to show why Google maps tend appear easier to read and to use. The gist of the analysis is that legibility is improved through a number of graphical techniques that in combination produce a significant visual effect.

And of course knowing Google, this stuff was tested and tested and tested to get the right margins around text, the right gray scale for the labels, the right label density, etc.

So why did Justin have to reverse-engineer this work to understand it?

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A recent NY Times article exposed the machinations of a sleazy guy who ran an online business that relied on links — positive, negative, whatever — to his web site that caused it to be promoted in Google search results. In fact, he found that by being nasty to his customers, his rankings improved.

The Time article implies that it was his customers’ negative comments that drove up his PageRank score, but Get Satisfaction (least one of the sites on which many of the comments were posted) claims that they mark links with the “rel=nofollow” attribute, which removes that link from PageRank considerations.

So why was he as successful as the article makes it seem?

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One of FXPAL’s papers at the ACM Multimedia conference this year describes FACT, an interactive paper system for fine-grained interaction with documents. The FACT system consists of a small camera-projector unit, a laptop, and ordinary paper documents. The system works as follows: a user makes pen gestures on a paper document in the view a of a camera-projector unit. FACT processes these gestures to select fine-grained content and to apply various digital functions. For example, the user can choose individual words, symbols, figures, and arbitrary regions for keyword search, copy and paste, web search, and remote sharing. FACT thus enables a computer-like user experience on paper. This paper interaction can be integrated with laptop interaction for cross-media manipulations on multiple documents and views. FACT can be used in the application areas such as document manipulation, map navigation and remote collaboration.

Rumor and inference have it that Apple will release the next generation iPad next spring. The new device is expected to have two cameras (front and back), and may be able to work with multiple carriers, rather than just AT&T. These seem like obvious enhancements, which makes me wonder if the press has thought this up, or if Apple is really not worried about the competition.

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I just read an interesting post by David Karger about PIM, end-user programming, data publishing, and lots of other interesting HCI ideas. The premise is that purpose-built applications for PIM impose strict schemas on their users, making it difficult to adapt, repurpose, or integrate the data with other applications. The alternative is something like Evernote, that lumps everything into one bucket, access to which is mediated largely by search. The tradeoff, then, is between a relatively undifferentiated interface backed by search on one hand, and a large number of siloed applications with dedicated interfaces.

David describes several systems (interfaces) his students built that leverage the Haystack framework for storing arbitrary data, and suggests that it’s possible to structure these data management tasks as authoring problems rather than as programming, thereby making flexible, extensible, customized interfaces more widely accessible.

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Those of you who’ve followed this blog and Jeremy Pickens’ blog will recall his many comments about Google’s un-Googly behavior. Recently, Benjamin Edelman actually tested the hypothesis about Google injecting bias into organic results. His post details several kinds of queries that don’t produce organic results. Which ones? Ones that are related to Google properties such as finance, health, and travel. While it’s clear why Google pushes its own properties, it seems that this behavior is inconsistent with the image it tries to project.

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CHI rebuttals are due at the end of the week. What to do? What to write? How do you convince those reviewers (particularly Reviewer #3) that your work has merit, if only they would brush up on their understanding of regression analysis. I am not promising any miracles, but I’ve written and read a few rebuttals over the years. Here’s my take.

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In the past, media capture and access suffered primarily from a lack of storage and bandwidth. Today networked, multimedia devices are ubiquitous, and the core challenge has less to do with how to transmit more information than with how to capture and communicate the right information. Our first application to explore intelligent media capture was NudgeCam, which supports guided capture to better document problems, discoveries, or other situations in the field. Today we introduce another intelligent capture application: mVideoCast. mVideoCast lets people communicate meaningful video content from mobile phones while semi-automatically removing extraneous details. Specifically, the application can detect, segment, and stream content shown on screens or boards, faces, or arbitrary, user-selected regions. This can allow anyone to stream task-specific content without needing to develop hooks into external software (e.g., screen recorder software).

Check out the video demonstration below and read the paper for more details.

Bill van Melle, Thea Turner, and Eleanor Rieffel contributed to this post

FXPAL’s work on the MyUnity Awareness Platform has received considerable attention from the popular press and the Internet blogosphere in recent weeks, following a nice write-up in MIT’s Technology Review. That article, despite its misleading headline, correctly relays the core motivation for the work: to improve communication among workers in an increasingly fragmented workplace. However, some writers who picked up on that article focused instead on the sensational aspects of having technology monitor people’s behaviors and activities while they are working. They incorrectly described some of the platform’s technical details, overstated what the platform does and what it is able to do with the data it collects, and failed to mention the numerous options we offer users to control their privacy. We thought we should clear up some of these misconceptions and clarify the technical details.

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