For the past year or so I’ve been tracking trends in analytics, sensing systems, community feedback services, and visualization & modeling tools as they might be applied to intentional civic design. IBM’s Smarter Planet initiative is both a fine example and a major signal of the move towards a deeper understanding of natural & human systems and the technologies that enable us to model and reprogram our world. What this means for my local community is that we’re increasingly able to collate run-time data about our city that can be scraped, sorted, analyzed, visualized, and used to inform behavior, policy, planning, and optimizations. Services like EveryBlock and San Francisco CrimeSpotting, as well as the data visualization work carried out by Stamen Design, MIT’s CitySENSE, and many others illustrate some of the ways local data can be harvested, parsed, & visualized to derive valuable behavioral patterns about a city.

Such services have mostly been cobbled together using Google Maps and limited access to data feeds released by civic bodies but there is a growing trend for city governments to mandate standardization of their metrics into structured data streams (XML, RDF) and to aggregate & publish these feeds to the public. Gavin Newsom, the mayor of San Francisco, announced today the DataSF project which aims to create a “clearinghouse of structured, raw & machine-readable gov data”. This commitment by such a major & influential city is a huge step in legitimizing the value of open data and engaging developers & innovators to build better services for optimizing civic functioning. It is this intersection of government openness & data standardization that underlies the Gov 2.0 movement and reinforces the emerging metaphor of City as Platform.

In reviewing the General Plan 2030 [PDF] of my own city, Santa Cruz, Ca., I see the standard (and important!) list of local resources, community planning & preservation concerns, issues regarding land use & economic development, etc… but what’s missing is any reference to the increasingly large and important data shadow cast by our civic, ecological, financial, and social structures. I think this is typical of most cities that consider both event-driven data and cloud-mediated activities as tangentially arising off of primary traditional institutions. Business has sales metrics, the Department of Works has road repair updates, and farmer’s have crop reports. But in order for a city to become a platform, and for civic planning to truly step into the Information Age, the importance of it’s data shadow must be addressed as a fundamentally critical component of it’s overall functionality. Just as water resources, agriculture, and emergency services are important vertical columns in the map of city planning, so too is the dynamic body of information produced and mediated by local activities. Civic planning must consider how this data can be leveraged to better understand and optimize the vibrancy and resilience of the community.

There are many open source tools to enable creation of local mash-ups and visualizations but the fundamental roadblock impeding such progress is the missing mandate for civic bodies to convert their data into open & structured standards like XML, KML, and RDF. Just as companies invest increasingly in business intelligence platforms, executive dashboards, and analytic platforms in order to better understand their operations and model future implementations, so too must city planners underwrite their IT departments with the funds necessary to standardize & open their data so the behaviors & patterns of the city may better reveal themselves to analysis. It is a meager investment that will pay off immeasurably within just a few years. Implementing such a strategy will bring a tremendous amount of transparency into civic operational processes and stimulate a rich ecology of innovation, while engaging the community directly in the enterprise of building more efficient local systems.

Below this post are a few articles I wrote at http://urbeingrecorded.com/news and have been meaning to cross-post here.

I attended the Friday session of Metaverse University 2009 at Stanford last week. Here are some of my observations:

Themes: interoperability, open source, simulations, visualizations, breaking down the walls, and being stuck with Second Life. Little emphasis on chat and social networking, per se. Much more emphasis on architectures & component solutions.

Trends from Virtual Worlds Roadmap: simulation & training, health care, augmented tourism, mixed-reality museums, live sporting events in VW’s, virtual meetings.

Overview:
While the hype over virtual worlds has faded, many serious researchers continue to do fascinating work in the territory. Monetization of a good VW strategy is still needed but this goal seems to have receded into the future for many of the speakers, as well as many of the enterprise-scale companies investigating these spaces who seem less interested in making money (either through direct development and monetization or by riding the public hypetrain) and more interested in gaining efficiencies and trimming overhead (teleconferencing, remote collaboration).

Google (O3D), Intel (Cable Beach), Sun Microsystems (Project Wonderland), Samsung (Virtual Worlds Roadmap), and Nokia (supporting REalXtend) were all present, as well as many Stanford researchers, including the folks building Sirikata. Many are working to extend the OpenSim fork of the Second Life platform. None of them seem to be working towards direct productization (though Google wants O3D to be the in-browser standard for 3D content) but each were working to advance the platform and explore future possibilities.

With monetization off the table and money drying up, researchers are moving to embrace open source solutions (OpenSim, ScienceSim, Ogre3D) and pushing for open standards (OpenId, OAuth, XMPP) and flexible API’s. Almost everyone mentioned a desire to move away from the proprietary walled-garden approach towards an integrative one that looks to the success of social network strategies. While celebrating open source development of Second Life forks, almost everyone bemoaned being stuck on the platform, often underscoring the feeling with a groan that “there’s nothing else”.

Authoring was rarely addressed with content instead being re-purposed from upstream solutions, eg using 3DSMax & Maya content to build world content. Collada was uniformly mentioned as the exchange format. Most developers still want to shoehorn other modalities (eg PowerPoint, web browsing, document collab, etc) into the VW space. Some examples inadvertantly showed the clunkiness of current solutions. I asked why a technology like PowerPoint is any better in 3D than in 2D, eliciting a long pause from the presenter. There’s still a lot of ambition on the part of developers but not always a ton of common sense.

However, IBM’s manager of service design and service systems research, Susan Stucky, gave me the most reasonable answer I’ve heard yet about why it’s important to move 2D modalities into 3D. She said that for collaborative telepresence it was very helpful to have access to everything you would normally have access to in a meeting. Speaking with her at the break, she told me how IBM has found that the greatest use of their Second Life investment has come from the ability to bring employees and clients from around the world together into a collaborative space. They’ve held conferences, run meetings, and explored simulations of project management strategies. For her, the ROI was gained by telepresence & simulations.

And for me, I had a breakthrough speaking with Susan. One of the most compelling yet least-obvious values of collaboration in virtual worlds is the sense of embodiment conveyed by the presence of the avatar. Identity, social cohesion, team building, and friendship arise more naturally when those engaged are perceived as physically present. Self-awareness and the projection of self onto others is still quite bound to our physical bodies. Perhaps combining the embodiment of avatars with in-world access to knowledge & productivity tools represents a more effective modality for non-local collaboration. I’m not sure how this compares to video teleconferencing but I feel there’s a lot of depth to be explored in how virtual embodiment reinforces social cohesion & collaboration (attn: PhD candidates).

Other notables: Henry Lowood (Stanford Curator of History of Science, Media, & Genetics) speaking on The Ultimate Archive: building virtual museums of virtual world platforms inside virtual worlds (eg a virtual museum with a room that lets you play the first Doom level as it was originally). He noted both “perfect capture” (all the data can be archived) and “perfect loss” (experiences, emotions, and deleted content cannot be captured) in VW archiving. Sheldon Brown (Center for Research in Computing in the Arts, UCSD) showed his mind-bending work Scalable City and called for procedurally deriving world assets and behaviorally deriving world experiences.

Analysis:
Virtual Worlds have lost funding and are presently in the Valley of Hype. Effective monetization strategies have yet to reveal themselves. However, there is value to the enterprise in leveraging virtual worlds for telepresence and collaboration, simulation & training. The VW community is moving the R&D towards openness: open source components, open standards, interoperability, and engaging with the platforms and principles of social networks to enhance connectivity and move away from the Walled Garden. The most interesting work with virtual worlds continues to be in the deeper realms of behavior, psychology, telepresence, and simulations. Graphically, everyone is apparently stuck in Second Life. A smart, well-funded private investor would build a platform with the competitive graphics capabilities (surface mesh, brep, kinematics, HLSL, etc), a powerful and scalable object model that can push to XML/RDF/RSS, a powerful simulation engine with an expressive visualization/analytics front-end, a REST/JSON API capable of talking to agents, tools, and other VW’s (as well as Twitter, Facebook, LinkedIn, SMS, Playstation Network, XBox Network, etc), integrate ActiveX embedding of 2D tools (Office apps, browsers, etc), enable a content marketplace built around highly expressive and personalizable avatars and fetish objects, and cultivate a 3rd part service ecosystem supporting all of the above.

Is this so hard?

In a time of monumental change it’s important to look at how the big player’s are adapting. Their moves are typically the most heavily researched and financed attempts at divining the underlying currents and capitalizing on the shifting technological marketplace. It’s especially interesting when conservative tech stalwarts like IBM & SAP suddenly start looking cool.

Both IBM & SAP are moving quickly into 3 of the most powerful trends in computing, each of which are driven by the enormous amounts of data being captured across all domains: business intelligence & modeling, stream computing, and sustainable systems analysis.

IBM’s new initiative A Smarter Planet states succinctly, “the planet will be instrumented, interconnected, intelligent.” This is a powerful statement from one of the largest and most technologically advanced companies in the world. They’re not just talking about business. IBM CEO Sam Palmisano speaks to the really large-scale planetary challenges in creating smart infrastructures for energy, water, transport, and data.

A key component is the recently-announced System S project for supporting so-called Stream Computing.

System S is designed to perform real-time analytics using high-throughput data streams… to host applications that turn heterogeneous data streams into actionable intelligence… System S applications are able to take unstructured raw data and process it in real time.

“This is about what’s going to happen,” explains [director of high performance stream computing at IBM] Nagui Halim. “The thesis is that there are many signals that foreshadow what will occur if we have a system that is smart enough to pick them up and understand them. We tend to think it’s impossible to predict what’s going to happen; and in many cases it is. But in other cases there is a lot of antecedent information in the environment that strongly indicates what’s likely to be occurring in the future.”

With enough data you can start to create connections and patterns. With patterns you can derive meaning and ultimately be better enabled to make more accurate predictions. Since humans aren’t very well-adapted to processing large data sets, we build tools to handle the heavy lifting. Whether Wall Street indexes, ERP scenarios, government accounting, energy grid analysis, or dynamic climate models, serious hardware & software is required to process operational data into meaningful determinations and prescriptions.

SAP has introduced the Clear New World initiative built on their Business Objects service architecture. Again, the notion is that businesses, enterprises, and even governments can run more efficiently when there is a free-flow of data and a suite of integrated services to crunch and render the info into meaningful contexts.

It’s time to build greater visibility, transparency, and accountability into the way your organization works. Because being clear allows timely and relevant information to be available when and where it is needed. Clarity demonstrates that your company is willing and able to stay accountable to key stakeholders. Clarity helps call out inefficiencies, reveal your best customers, create credible sustainability, and give your business the flexibility needed to anticipate and respond to a complex, ever-changing, global environment.

[See James Governor's recent post for more on how SAP & IBM are tackling enterprise sustainability.]

Note the statements about accountability to stakeholders & creating credible sustainability. Clear data & clear reporting. Now consider the latest announcement about SAP for Public Sector “to support the management and reporting of economic stimulus funds”. As a plugin to their Business Objects suite, this utility drafts on the trends towards open accountability and government transparency, often termed Gov 2.0, to provide support for determining just how stimulus money is being spent.

Both IBM and SAP have the power to execute effectively on these strategies, though it remains to be seen how enterprise spending will move to implement these services or if the companies will offer flexible licensing to LLC’s working on the really challenging non-profit global issues. Likewise, SAP has suffered usability problems for years and their core object architecture is old and slow. They will need more than just branding and plugins to make a more transparent world.

Finally, it’s worth noting the branding for these projects. “A Smarter Planet” is a global posture indicating agency and identity on a planetary scale. This hints at the real deep trend across the human species towards a global sense of purpose and strategy. “Clear New World” acknowledges both the occlusions under which human endeavor has marched thus far and the great clarity of visibility we’re now gaining across all domains & enterprises, while admitting that indeed everything is changing and we are moving into a New World. The technology is stepping forward to help us more effectively manage the present and navigate into the unknown future. But of course like all foresight, it remains to be seen whether individuals will choose to act appropriately with the knowledge they come to possess…

A core human competency is the capacity to model outcomes. This predictive ability has contributed to our successful growth as a species and provided the stage from which we extrude our technologies. We observe our world, log our experiences, and use this information to envision & plan our future possibilities. In the rush into tomorrow we’ve deputized machines to assist in our scenario modeling as our plans grow ever greater in scope.

Today we have tremendous amounts of data available about any system we wish to model. Drive platters are bulging into the terabytes just to store all of the information gathered by sensors, services, and empowered humans. Whether we study business networks, financial models, or natural systems, our awareness of their complexity has grown exponentially. Things are far wider and more interconnected than we could have imagined even 20 years ago.

All systems are sets of nodes with properties & variables that govern their behavior, coupled together by relational rules governing their interaction. The more complex a system, the more unique nodes and the more interconnections between nodes. Given the human constraint of being able to hold only 6 or 7 unique objects in mind at any given time it’s clear that we’re overwhelmed by even the relatively simple tasks of understanding, for example, a mid-size business structure enough to predict its future, especially when you consider the business system itself as a single node embedded in a much larger global socio-economic system. Imagine the difficulties climate modelers face trying to document global circulatory systems…

One emerging strategy for modeling complex systems looks to software and the floating-point wonders enabled by Moore’s Law. Computers are phenomenally capable of managing the inconceivable amounts of operations necessary to begin modeling dynamic systems. Yet, until very recently one needed to book time on a supercomputer cluster to run weather models or robust behavioral analysis. Even today’s bleeding hardware strains under the weight of such complexity. Research institutions have pursued natural systems modeling for some time and the business world has been paying attention. SAP now offers modeling capabilities with its business intelligence ERP solutions, enabling executives to run scenarios and envision possible outcomes of strategic decisions. Oracle recently acquired Hyperion, adding “performance management” to their suite of BI tools. You can bet these technologies will work their way into government & geopolitical protocols, as well as social & personal behavioral engineering as we increasingly track & model our lives.

Effectively, this pattern emulates the deeper shift from individual enterprise to collective collaborations. You can only model a complex system with another sufficiently complex system. However, even the most interesting algorithms are encumbered by the impositions of their logic: they can only be as creative as they were written. A second emerging strategy for modeling complex systems looks to deputize humans as processing nodes, crowdsourcing future possibilities across infinitely creative sets of minds. The Institute for the Future has taken this approach with its Signtific Lab and the Superstruct platform, leveraging the principles of gameplay to engage massive participation in envisioning scenarios.

The Superstruct games have drawn in thousands of players offering their thoughts & dreams of the future. Players become processing nodes for the chosen subject (eg. “when augmented reality is everywhere”, or “when personal satellites are as easy to deploy as websites”) iterating across large sets of potential outcomes. From these inputs, patterns emerge showing trends with greater frequency & momentum among the collective. Perhaps even more interesting – and where the Superstruct method is more flexible than computational modeling – are the outliers that emerge from players. Many of the most compelling signals of the future are those that completely break from current patterns. Indeed, one of the most fundamental prevailing shifts in the global paradigm is that change is accelerating in ways we cannot even imagine.

These two approaches both consider complex systems & scenario modeling from architectures that themselves are complex, object-oriented systems. The programmatic approach brings heavy-weight numeric bit-crunching to dynamic data streams, while the Superstructing approach offers wide-reaching creativity and human sensing. Augmenting one approach with the other will mark the next phase of predictive analysis necessary to safely navigate civilization through the future. Envisioning these scenarios and building compelling narratives around them will inevitably draw them into becoming.

Our lives are more & more complex and our enterprises & collaborations are commonly reaching global scales. The need to effectively model & predict is a fundamental human trait, reinforced in the face of escalating complexity in a hyper-connected, Read-Write world.