OK, so I dropped the spoiler in the title. Mind you, you could argue that this is hardly surprising given the importance of mobile development at this point in time. Still, no less than 3 of the top 10 articles in the developerWorks newsletter for the month of May (where we showcase our latest content on a weekly basis) covers mobile web app development.
Also, we weren’t seeing this level of interest in HTML5 even a year ago. True, there was a lot of interest in mobile: but at that time the larger focus was around mobile platform development (led by iPhone and Android).
There’s a lot of talk these days in the enterprise space around mobile development.
In a series of short interviews, watch the infectiously energetic Jerry Cuomo (WebSphere CTO) explain that for many customers mobile is not an option. They need to have a roadmap to mobile deployment, and they need it now. Drawing parallels to the growth of the web over a decade ago, Jerry talks of the current ‘frenzied excitement’ which he believes will lead to an environment of better choice, architecture and the design moving forward.
And choice is something we’re not short of in the mobile development space. Should you develop web-based mobile apps? Should you develop native apps to cover the whole gamut of platforms (which still includes Blackberry if you’re talking B2B development).
Whilst now developers are faced with a number of mobile architectures on which to develop, the Holy Grail is to leverage existing skills, whether they be around the web, open standards, Java, etc. to write an application once and deploy to many devices.
WebSphere Application Server has taken this approach for its mobile strategy with the launch of the Web 2.0 and Mobile Feature Pack. Built on the popular Dojo Toolkit, the Feature Pack gives developers access to HTML5 mobile themes (to develop web apps that look like native applications), mobile widgets, diagrams and improved gauges and charting.
As IBM’s Chris Mitchell explains in this video, for the clear majority of developers of enterprise applications, the user interface (UI) is simple enough to not require all the full-blown features of a native app. Displaying an XML feed of first-quarter product sales is a substantially different proposition to rendering a realistic 3D racing game. Having said that, mobile frameworks like Dojo are becoming richer and really stretching the paradigm of what can be displayed on the web.
For instance, Eric Durocher over on the Web 2.0 and Mobile Development Blog shows how a complex diagram like an organizational chart can be rendered for a mobile device:
What are the best practices for developing these applications?
Chris Mitchell suggests an architecture that decouples the server from the client. Data from the server side can be exposed using REST or web services. These can be accessed from the client side, whether the client be a web application or a mobile one. In this way you only build one core application with only minimal work on the front-end to cover any web-enabled device.
If you want to take this a step further and offer native apps (say, if there is a requirement for the app to appear in an App store like Apple’s or Android’s), you can create a hybrid application with a tool like PhoneGap. You effectively build a web-based mobile app and let PhoneGap provide a wrapper so from a user perspective it looks and runs like a native app.
According to a recent article in Advertising Age, Google’s social strategy does not involve building social networks to compete with Facebook but rather it is focusing on using social data to build better applications:
“As an example of the current strategy, [Eric] Schmidt talked about getting more information from YouTube users in order to offer more targeted video.”
but from Schmidt’s comments, development around this area of exposing social analytics is where they see real business value. This is backed up by moves such as YouTube’s purchase of movie recommendation site Fflick.
How can analytics be used to derive value?
For instance, predictive analytics solutions (like IBM SPSS) can traverse a large inventory of content and make associations based on a visitor’s past behavior and the behavior of their friends in the network. Match this with sentiment analysis, which can be used to look at the conversation around a video to determine whether it is loved or loathed (or somewhere in-between), and suddenly you have a more immersive viewing experience.
Whilst analytics can offer differentiation in a hotly-contested area, the issue of privacy has to be addressed. The interfaces can get so good at offering recommendations that they border on being plain creepy. Couple this with the growing paranoia around the extent to which our digital lives are tracked, and suddenly these interfaces appear more Big Brother rather than benevolent Jeeves. One way to address this issue is to be as transparent as possible when exposing social analytics.
So if Eric Schmidt’s comment can be taken at face value, I’d suggest it’s in the context of a growing trend in looking to maximize the value in existing networks rather than racing to build new ones. Social analytics, when handled deftly, can unlock this latent value in social data.
As the attention span of the browsing population shrinks below that of your average goldfish, so the need to create razor-sharp, perfectly honed navigation systems increases. There’s a demand on publishers to use whatever information they have to provide a more contextualized browsing experience.
That’s all well and good, but have you ever looked at a recommendation and wondered what on earth was the system thinking when it picked it? You’ve spent months on the site exploring hardcore thrash metal so why on earth are you being offered a book on floral knitting patterns?
I just went onto Youtube and noticed that they have actually got pretty transparent with their recommendation engine:
Notice the ‘because you watched’.
As we use more analytics systems to build interfaces, being explicit about how decisions are made becomes increasingly important:
Show what determined the recommendation: This answers the question of why on earth am I seeing this recommendation? In this instance YouTube bases this on what you have watched previously, but this could just as well relate to what others with similar interests have liked (the Amazon approach).
Allow you to interact with the recommendation: YouTube allows you to remove recommendations from the list that you don’t think are appropriate. One thing it doesn’t do is spell out whether that feedback is factored into future recommendations. Some systems (such as Pandora and Netflix) use a thumbs-up/down or rating system with the implicit understanding that this information will be fed into the calculations of future recommendations. As James Taylor, the Decision Management expert pointed out to me some years ago, recommendation engines have their limit. If I booked a once-in-the-lifetime trip to Bermuda last year, there’s no point in showing me vacations to Antigua six months later. Allowing me to vote this kind of recommendation down can help systems disentangle one-shot whims from longer term patterns of behavior.
The question of privacy: Being transparent about analytics systems and and how exactly visitors are being tracked can go a long way to allay the growing public fears around the growing mountain of data produced by the internet in general and social networking sites in particular. Indeed, here in California there has been considerable press around a bill to increase the privacy of social networks. Justin Brookman, director of the Project on Consumer Privacy at the Center for Democracy and Technology has said, “I think the idea of telling people what is going on and giving them control over their information from the beginning is a good idea for social networks and others places as well”. Privacy advocates are asking publishers to be more open about how data is being used.
As user interfaces become more reliant on analytics tools to offer a more personalized experience, there are significant advantages to displaying upfront exactly why we are being shown the recommendations we see.
At a recent business analytics event, Lennart Frantzell demonstrated how (at least at a practical level) there has been a shift in business computing from Artificial Intelligence (AI) to Business Analytics:
Using a healthcare example, Lennart explained how 20 years ago AI was used to form a diagnostic method for treating snakebites in Australia. The approach was to look at the cognitive process doctors go through when treating snakebites and build a system of complex algorithms to mimic this process. The emphasis was on the algorithm – not the underlying dataset. Any sub-optimal decisions made by doctors (say as a result of bias in their individual experience) would also reflected in the system.
Fast forward 20 years. In order to treat HIV in Ethiopia, business analytics is being used to crawl over 41,000 HIV treatment histories. The EuResist system takes data from a new patient and matches this against patients who have been successfully treated in the past, so determining the most appropriate treatment. The treatment consists of a cocktail of drugs, in which the proportion of each drug in the cocktail can affect how successful the treatment will be. This obviously adds a layer of complexity to determining the ideal solution. What success are they seeing on this project? Over 78% accuracy, outperforming 9 out of 10 human experts.
The key difference here compared to the snakebite project is the focus on data. The EuResist project pulls data from disparate databases into a flexible DB2 platform that can be analyzed using business analytics. The algorithms are simpler than those used in AI, but the results can be impressive because the reliance is on exposing trends in the data.
The separation of the algorithms and the data also makes it easier to create products that can be implemented with minimal customization, compared to large AI systems that need to be custom-built. Eg. the underlying technology and methodology for treating HIV in Ethiopia can be applied to looking at Asthma in Western Europe.
As we continue to produce more data (just take a look at the 389,000 datasets the US government makes publicly available), business analytics can play a significant role in turning this data into insight and solve problems that were previously out of the reach of artificial intelligence systems.
This year, Internet Week New York happens to coincide with the celebration of the IBM Centennial in June. So as part of our celebration of 100 years of innovation, we’ll be hosting an Internet Week event on June 9th from 2pm until 5:30pm at the new IBM briefing center on historic Madison Avenue.
What we will be discussing:
Did you know that IBM is focused on helping Startups succeed? Find out how developing social applications with IBM technology can set you apart in the marketplace and learn about the IBM Smart Camp program going on around the globe including right here in New York.
So do you think you are smarter than IBM Watson? Well, you'll also have an opportunity to get up close with IBM Watson, the artificial intelligence computer system developed by IBM Research capable of answering questions posed in natural language. See how the technologies are now going beyond game show history to tackle some of the world's most challenging business problems.
Is your business a Social Business? The integration of social computing into enterprise design represents an enormous shift in how business is conducted. Organizations that successfully transform into a Social Business can potentially reap great benefits – among them the ability to deepen customer relationships, drive operational effectiveness and optimize the workforce. For today's stand-out companies, integrating social capabilities into enterprise design is a must. That opens new doors for business opportunities to be more engaged, transparent and nimble.
So how can IBM help you? Learn about bringing applications to "the cloud", taking your mobile apps on the go on most major platforms, and get started with the IBM Social Business Framework and Toolkit.
Agenda* (2-5.30pm):
Registration and Welcome
100 years of IBM Innovation and IBM Watson Challenge
All About Social Business Apps and the Social Business Framework, and Toolkit Demonstration
Raising Your Applications to the Cloud
Networking and Cocktails
* subject to change
So register now and come check out the New IBM Briefing Center at:
590 Madison Ave. 3rd fl Auditorium New York, NY 10022
OK, so I dropped the spoiler in the title. Mind you, you could argue that this is hardly surprising given the importance of mobile development at this point in time. Still, no less than 3 of the top 10 articles in the developerWorks newsletter for the month of May (where we showcase our latest content on a weekly basis) covers mobile web app development. 
This year, Internet Week New York happens to coincide with the celebration of the IBM Centennial in June. So as part of our celebration of 100 years of innovation, we’ll be 
