Since it was founded, personal blogging has proliferated and competing websites have appeared in the city. Most notably, after 174 years the city’s daily printed newspaper the Ann Arbor News shut down in June 2009. At its close, newspaper company launched AnnArbor.com, a blog-like website with comments and a small core of full-time writers.

I think there’s a lot to learn from this case. One of the most important lessons is something Lisa Williams (of Placeblogger.com) mentioned to me during a conversation we had last fall. She said longevity alone isn’t necessarily a good measure for success of online citizen journalism projects. Given changes in the internet and broader media landscape in Ann Arbor, it seems right to shut down the site. I trust the community members will work to ensure what it achieved will continue somewhere online: a source for information about local issues and a venue for (mostly) civil discussion.

What is government 2.0? I attempted to define the topic earlier this month, but I’m not hung up on definitions. If you’re interested in applying Internet technologies to the business of government, we hope you’ll attend.

> See Conference Wiki or Registration

Of course, transit watchers know despite record ridership in recent years, two other of the nation’s other large, old transit systems are in equally dire straights — Chicago and New York. Although some of the problems are similar, I wanted to know the causes of the crisis in Boston. A recent report by a gubernatorial-appointed commission laid out the stark facts. The report, completed by a group headed by former finance industry executive David F. D’Alessandro, was published in November. This post relies largely on this recent report, readers with alternative perspectives are welcome to post comments below.

In 1999, the Massachusetts state legislature dedicated 20% of the State’s sales tax collection, excluding meals taxes, to the MBTA. Starting in July 1, 2000 this “forward funding” plan meant the MBTA would have a regular revenue source going forward. The agency adopted a financial plan for a balanced budget for the years 2001 through 2008. In the words of the report, “The Forward Funding Finance Plan proved unrealistic in many of its assumptions and nine years later can be deemed a failure.” The authors conclude the main driver of why the plan failed was “unavoidable cost explosions.”

• Fuel and utilities: cost $256 million more than anticipated due to increasing energy costs for the agency’s vehicles. The agency buys huge amounts of fuel and electricity for buses and trains.
• Payroll and employee benefits: $113 million more than anticipated. Wage increases were comparable to the 3.5% rate of inflation, but health care costs increased by 73%.
• The Ride (a federally mandated door-to-door paratransit service for disabled riders): $95 million more than planned.
• Sales tax revenue: $150 million less than expected. The forward funding plan projected an annual growth of 3%, it has actually only increased at around 1%

The only categories where there was good news was Commuter Rail ($37 million under budget) and nontax revenues were $95 million higher than expected. The report concludes the additional revenue is the result of three fare increases, the report authors observer “the last (2007) fare hike actually exceeded the Plan’s target, in part because ridership grew despite the fare hike.”

The cumulative total across the eight years? A $558 million deficit. The report concludes, “A private sector firm faced with this mountain of red ink would likely fold or seek bankruptcy.” In short, to keep operating the agency balanced their budget by pushing off debt, restructuring $238 million in the last three years alone. They also neglected maintenance. Among 56 maintenance projects with a “10″ — the highest — on an internal safety rating, only 6 were funded last year. The authors conclude the agency tool other steps to control costs:

Contrary to not trying, we found evidence that the MBTA did make some hard expense choices. Across-the-board cuts were routinely made to departmental budgets. Periodic layoffs and hiring freezes restrained the headcount. Individual managers took pride in eliminating inefficiencies and redundancies, while embracing a new organizational ethic of customer service. Yet in the end, they could not pare staff below the number needed to move hundreds of thousands of riders across hundreds of routes each workday. Add the complexity and cost of sustaining the system’s aging infrastructure, and it became evident that the cost inflation and savings assumptions in the Finance Plan were never tested against the daily grind.

Against such a bleak picture, finding a “solution” seems like an insurmountable task. However, if any urban institution is “too important to fail” it’s the MBTA. I haven’t done a financial analysis, but the list below presents some steps that could be taken to improve the agency’s solvency.

1. Higher Fares, Pegged to Inflation
There are two general philosophies related to transit fares. One is to support transit from sales taxes or other general taxes, and keep fares low. (Transit as a public good) The other is to use fares to cover a much higher proportion of the actual cost of running the agency. (Transit as a private good) Massachusetts, like most places, has taken the first approach. However, as we have seen, this introduces problems with general tax revenues increase too slowely, and it restricts the agency’s ability to adjust fares to cover the increasing real costs of the inputs to transit (worker benefits, electricity, etc). I’ve struggled with this issue, and concluded I think fares should be increased, and at the very least pegged to inflation. In order to mitigate the equity effects, special subsidies could be implemented for low-income riders. Although I believe in the principle of transit as a public good, Americans generally don’t support the level of taxation to support high quality transit. Using fares for a larger proportion of revenue also means increasing ridership will increase revenues. (By raising the cost of transportation it can also have interesting land-use effects – something for another post.)

2. Debt Relief
The agency needs a large, one-time injection to pay off its sizable debt, some of which was “given” to the agency as part of the costs of the Big Dig. Paying it off now will save taxpayers money in the long run.

3. Federal Funds for Maintenance and Capital Costs
Lots of interests are already lining up for funding from the federal government’s next transportation bill. It should contain a revenue source for transportation infrastructure maintenance and improvement that can be used by agencies like the MBTA. The MBTA Review report describes how a huge proportion of the agency’s rolling stock of buses and trains will need to be upgraded or replaced in the coming years, with no funds in sight to pay for it.

4. Greater Rider Awareness
As I ride the T daily, I often wonder whether the other riders know about the agency’s shaky finances and massive maintenance backlog. I suspect most take the system for granted. Transit advocates — and perhaps the agency itself — should explain in clear terms why the numbers aren’t adding up. This work is as necessary as the others to create the political will for painful, long term solutions. Doing nothing means the discussion about solution will occur in response to a crisis such as an accident or strike. Crises can produce quick fixes, but rarely the type of long-term solutions that are needed.

How do you think the MBTA’s finances can be improved?

> MBTA Review Report (November 2009)
> U.S. PIRG Report – Derailed by Debt (October 2007)

The term government 2.0 is a deliberate reference to the term “web 2.0,” coined by publisher Tim O’Reilly to refer to interactive, social websites like Wikipedia and Facebook, which have revolutionized how people use the web. Before delving into the meaning of government 2.0, we should consider government 1.0, the government analogue to web 1.0. Although less common now, the term most often used for this initial approach to technology in government is e-government.

The Center for Technology in Government defined e-government as having three components: e-management, e-services, and e-democracy. The first two have been largely realized. Governments have adopted, to varying degrees of sophistication, internal information technology systems such as networks, databases, and intranets. As we will see, government 2.0 practices often rely on these underlying systems. Governments have long provided e-services to constituents through websites, email, or APIs, including tax payments, service requests, and digital applications and paperwork. The last component, e-democracy, has been more elusive. In the web 1.0 world, this has most often meant emailing elected officials or signing petitions on topics. These activities have grown, although in the U.S. context exist mainly outside of government websites or structures.

At a lecture hosted by the Kennedy School Government 2.0 Professional Interest Council this fall, Nicco Mele suggested we adopt Tim O’Reilly’s web 2.0 principles as a starting point for government 2.0. My essay builds on his interesting lecture.

1. Government as Platform

O’Reilly’s first principle is “the web as platform,” adjusted for our purposes to be “government as platform.” The most obvious examples of this are where government agencies provide data or host competitions to encourage creative ideas that serve the public interest. The “apps” competitions in Washington, D.C. and New York and sponsored by the Massachusetts Department of Transportation, are a start to this trend. In these competitions, government provides the data, and an ecosystem of third party developers and tools helps unleash the value for the public, creating new tools, resources, and analyses.

Another example where government acts as platform is the phenomenon of participatory budgeting, pioneered by cities in Brazil and now has spread to a number of cities around the world. This approach puts budgetary decision-making, or some part of it, directly in the hands of citizens, bypassing existing representative models of decision-making. The technical dimensions of this are only now being explored, and in the Brazilian case above deliberation and voting online complemented conventional public meetings.

When it comes to service delivery, it is less clear what “government as platform” means. It may echo a broader political agenda that has sought to re-define the role of government through systematic privatization of formerly government functions, such as education or public services. After all, when governments provide educational or housing vouchers, aren’t they acting as the intermediary, or a platform? The political implications of shifting government from a service provider role to a facilitating role deserves consideration. This issue is connected to a host of issues surrounding contracting and public private partnerships. Governments may want to retain some types of service delivery if the good cannot be contracted for, or the public wants to enforce certain service standards.

2. Harnessing Collective Intelligence

The second principle is “harnessing collective intelligence.” Obama’s Memorandum on Transparency and Open Government identified collaboration as a policy goal for the federal government. In fact, Obama’s Deputy Chief Technology Officer for Open Government Beth Noveck experimented with collaboration tools to create an open government policy last summer. In other areas there are limited successes of citizen-government collaboration. The Peer to Patent program pools expert opinion to speed the patent process. The Next Stop Design project in Salt Lake City, Utah used crowdsourcing to select the design for new bus shelters. One of the people involved in the project, Daren Brabham, is writing a PhD dissertation on the application of crowdsourcing to public problems. In Melbourne, the consulting firm Collabforge ran a wiki as a component of a conventional planning process to generate the new city plan.

Fundamentally, this trend will face several types of powerful resistance.

First, it can run counter to traditional concepts of representative democracy, where elected officials work “down” through an expert bureaucracy to create and implement policy. Archon Fung has proposed “empowered participation” can be deployed as a governance method for specific issues, such as Chicago’s school committees or neighborhood policing committees. However, creating these structures depends on modifying existing forms of governance. Existing projects have avoided this in several ways. The apps competitions aren’t about creating policy, and the government hosts can always disavow responsibility. Idea-generation contests usually reserve final decisions to designated juries. Policy-creation projects retain the final decision-making power with conventional authorities. However, pushing this further into what Beth Noveck calls “wiki government” will require addressing this tension with existing practices.

Second, a host of public problems require technical expertise to analyze or solve. The question of how to integrate technical forms of knowledge with citizens is far from resolved. The cutting edge involves putting modeling tools in the hands of citizens, who use them as “decision support tools,” but this runs counter to existing models of professional practice and the very real need for significant expertise to complete complex analyses.

Lastly classified data and national security, a major governmental function, may never be opened to the public. Interestingly, Department of Defense has been interested in the collaborative potential of internal communication across their vast bureaucracy through wikis, for example launching a wiki to improve the Army Field Manual.

3. Open Data Standards

The third principle is the use of data standards. Expanding access to government data is a major trend, with initiatives underway at the federal, state, and local level to create data portals. The concept of linked data, emerging out of the Wikipedia project, seems poised to move into government datasets. In fact, greater linking and cross-comparison among the expanding amount of available government data will create a positive pressure to ensure cross-compatibility. Within Massachusetts state government, for example, town-level data has become a standard for comparison and analysis. With the federal government in setting metadata and other standards already, this may happen slowly but some signs are already in place. Using this to evaluate government may be misleading: the primary purpose of government isn’t to create data, although it is an important one. The technological viewpoint threatens to be reductionist, viewing the government as primarily engaged in collecting and hosting data. In reality, most money and effort in government is spent on delivering healthcare, education, national defense, grant programs, and regulatory actions, where data can play a supporting role (perhaps as indicators) but is not even always a mandatory input to governance.

In Boston, the author of a recent major report studying the city’s transit agency said in November he wouldn’t ride the busy Red Line due to serious maintenance issues that threaten to cause a train derailment. At roughly the same time, data enthusiasts were demanding real-time data about bus and train arrivals at the MassDOT developers conference. When our transit systems are in real danger of catastrophic failure, shouldn’t we spend all available funds preventing disaster for the existing riders, rather than inventing technology to make use more convenient? How can these important goals be balanced properly?

4. Customer Service

The last principle discussed by Nicco is customer service, based on O’Reilly’s “rich user experience.” An emphasis on customer services is undeniable at all levels of government. Cities have launched successful 311 systems for managing citizen requests, and governments have been subscribing to the “plain language” movement make government information more understandable and usable to citizens. However, just like “government as platform,” this principle too often reduces government to a consumer-producer relationship where the government provides services just like private firms might in the marketplace. Customer service is important, but so is engaging with citizens to generate ideas and implement solutions. In exchange for expecting service, citizens have the responsibility to understand the resource and legal limitations of government.

5. Incremental Policy

O’Reilly has several additional principles: end of the software release cycle, lightweight programming models, and software above the level of the single device. Of these, I think the principle for government is the advent of more iterative forms of policy making. The field of planning has developed theories of incrementalism or “muddling through,” to reflect the real-world pace of change. The web supports both short bursts of activity but also long-term archiving, and professionals are only now learning how to use the tools to develop sustained interest and engagement through ongoing conversations and communications.

Conclusion

What do we learn from this exercise? First, I’m not sure government 2.0 is yet a new type of government, instead a collection of promising trends. The adoption of new social and technical approaches of idea creation and governance don’t resolving age-old questions about what government should be doing, and how it should approach principles of equity and justice. In fact, what could emerge is a new, technically-enabled model of in the tradition of the “developmental state,” the concept that the state itself is engaged in economic and community development. This is perhaps the most important lesson of these trends: existing government processes should be examined and where they are not working be re-invented to take advantage of the ability of technology to expand the activity of governance beyond the institutions of government.

The three measures I chose were the overall percentage of workers using transit, bikes, and walking to work. I limited the analysis to the largest 30 “places” in the U.S. Census and used data from the 2006-2008 American Community Survey. Technically this is sample data, but I did not calculate margins of errors since for large cities they are generally small. Also, there’s an extensive and heated debate about exactly how green transit is. Most studies I’ve seen conclude busy buses or trains emit less pollution (including CO2) per passenger than private vehicles, but I won’t wade into the debate here. Here’s what I found.

Transit
For overall transit ridership to work, New York City (55%) and Washington, D.C. (37%) were winners, with Boston in third at 32% with San Francisco (32%) and Chicago (26%) rounding out the top five. Since this metric is for the center city only, I think Boston’s getting a bit short shrift. The region’s truly expansive commuter rail system (it goes all the way to Rhode Island — see below) carries an average of over 138,000 riders a day, more than all but two other similar systems in the nation — New York and Chicago. (Source: APTA ridership report (PDF))

Biking
What about zero-pollution biking? On this measure, the top five are Portland (4.7%), Seattle (2.5%), San Francisco (2.5%), and D.C. (2%) (which launched a bike-sharing system in 2008) and Denver (1.7%). Boston is only a few slots down at #7 with 1.2%. However, the city only recently saw the light and began pursuing bicycle planning aggressively. In fact, in the past it has been named one of the least bicycle-friendly cities in the U.S., although despite this bad reputation ranks way above dozens of other large cities.

The city’s 2009 State of the Hub report (PDF) reports 15 new miles of bike lanes (up from 0 in 2007), 500 new bike racks, a new bike map, and plans for a new bike sharing system moving forward. I should note plenty of smaller cities have larger shares of bike commuters. If Minneapolis were on the list, it would rank second with 3.5% of its commuters biking to work. If it were included, Boston’s neighbor Cambridge would be 5.8%, easily topping Portland.

Walking
Walking is another green mode available to most travelers, often overlooked for more exciting trains and bike facilities. However, making a city walkable can be tricky, as it depends on a subtle combination of good public facilities, urban design and density, and mixed land uses. On this measure, Boston tops the list at 14%, with Washington, D.C. just behind at 11.7%, and the rest of the top five New York (10.1%), San Francisco (9.52%), and Seattle (8.6%). It turns out some of the factors that make Boston such a bad city to bicycle — congested streets and a dense street grid — make it excellent for walking. Walking is so popular the city boasts an active walking advocacy organization — WalkBoston — and extensive trail networks along the harbor and through parks.

Next, I created a composite score for all three indicators. For each indicators, the cities were ranked with 1 going to the city with the highest (best) value and 30 to the worst. I then added the rankings together, weighing each equally. The lower the resulting score, the better. This score gauges the diversity of the mix, and isn’t an objective measure of pollution output. In this measure, Washington, D.C. ranks first with a score of 8, San Francisco and Boston tie for 2nd at 11, and Seattle fourth with a score of 15. New York, strong on transit and walking, falls to an overall place of seventh due to it’s low biking score (16th with just 0.7% of commuters reporting biking).

What can we conclude from this simple comparison? First, as Chava suspected some very bike friendly places like Portland may not have many transit riders or walkers. Any evaluation that stresses diversity, like this one, will rank them lower than older cities with well-developed transit and street networks. And although it comes as no surprise to me, Washington, D.C.’s high ranking may surprise some. Indeed, it is the result of many factors: excellent “bones” in a good street and sidewalk grid, decisions by city leaders in the 60s and 70s to stop as many highways as possible and invest heavily in transit, lots of government-related jobs concentrated downtown, and a city government aggressively pursuing improvements to bicycle, walking, and transit infrastructure in recent years.

Finally, I think Boston’s high walking score and surprisingly high biking statistics (despite little infrastructure and bad weather) show it is somewhat underrated. But is it the greenest city in America? That’s for you to decide.

The big news at the conference was their announcement of a pilot project to provide real-time bus arrival data for several MBTA bus lines. They also announced the winners of competitions for apps and visualizations that used the published data. In addition to scheduling and spatial data, the data for the visualization competition included two datasets containing the time, method of payment, and location (bus route or subway station) for every rider payment for two days.

The winning applications were two iPhone apps containing schedule data. The winning visualization was this animation showing activity in the transit network. The runner-up, “A Day In the Life of the MBTA,” featured striking visualizations of the data showing activity patterns at different stations throughout the days. I also appreciated another entrant, “A Day of MBTA” who created a website with histograms for riders entering each T station.

During his talk, the NextBus’s Michael Smith observed RFID payment cards such as the CharlieCard can improve the bus riding experience by speeding passenger boarding. Riders of busy bus lines know how much one or two riders paying with cash can slow down the system. Although the visualization contest data included payment data, none of the entrants analyzed it. According to the key the state provided, the various payment types are:

• MBTA Old Tickets – This refers to magnetic tickets that are pre-encoded by a third party vendor and then distributed to T sales offices for sale to the general public. They are also distributed to Cubic, which is the vendor in charge of completing on-line and Corporate Program orders.
• Triplex Roll mag. Stripe (Large and Small) – This is the type of stock used to encode magnetic tickets that are issued from Fare Vending Machines and bus Fareboxes.
• PreCut Triplex w. mag. Stripe – This is the type of stock used to encode magnetic tickets that are issued for bulk production of magnetic tickets and retail sales terminals at 7-Eleven, Stop and Shop, etc.
• Smart Card Mifare 1k – This is the type of media on which Charlie Cards and IDs are issued.
• Regular Charlie Cards are purchased pre-encoded from a third party vendor and then distributed to subway stations, select bus terminals, T sales offices and retail locations for further distribution to the general public. Student Charlie Cards and IDs are issued from back-office devices located at 10 Park Plaza.

Using the data key provided, I created summary statistics for payment methods by bus route:

The result seems to show relatively high usage rates on most bus lines. The busy 1 bus, running from Cambridge to Dudley Square, had 77% riders paying with CharlieCards on September 8. I don’t know enough about the routes to pull out any other findings — but there are some curious patterns. (Why does the 429 have 32% paying with “other,” presumably cash?)

CharlieCard use on the subway is also high, ranging from 58% on the Silver Line to 72% on the Red Line. At the station level, the stations with the highest CharlieCard use rates are Wollaston, Davis Square, and Bowdoin, all at over 80%.

Do any readers see interesting patterns in the CharlieCard data? Did anyone else attend?

Notes and other materials will be posted on the following websites next week:

> MassDOT Developers Page
> MassDOT Developers Conference Website

However, models can have insidious effects. They excel when applied to deterministic systems, where the rules are static and known, but often fail when applied to systems with arbitrary or random characteristics. Even more troubling, models can impede decision-making by hiding their assumptions, introducing bias into the simulation.

In this light, let’s consider a simple model developed by the oil company Chevron. Their “Energyville” game is located the Will You Join Us website, now being promoted through magazine and TV ads that position the company as an energy company interested in finding energy “solutions” and using it “wisely.” Energyville is presented as a neutral challenge: “What energy sources will power your city?” A disclaimer reminds the user that the assumptions are “based on The Economist Intelligence Unit’s assessment of global facts and trends obtained form numerous credible sources.” The warning observes the game makes many simplifications, acknowledging “global forces and technological developments may change current and future assumptions.” The game aesthetics shows a clear influence of the popular SimCity.

Launching the simulation, I begin by placing some wind turbines in the city. After installing three turbines, the limit is reached: “Geographical and other constraints prevent Wind power from providing any more power to Energyville.” Next, I turned to solar panels. After just two placed, I get this error: “Unavailable! Solar panels are still too cost prohibitive and inefficient to provide any more power to Energyville.” The only remaining renewable energy source is a massive conventional-looking hydroelectric dam. After installation on the river, most of my city’s electrical needs are met.

All except for the ever-important petroleum. There’s no Better Place-type electric car networks possible here. “Warning! low on fuels,” a message quickly appears, saying I need petroleum for airplanes, vehicles, and mass transit. Only once I put a huge petroleum platform in the ocean could I proceed to the next level.

Before level 2 begins, the simulation presents a policy choice: should I adopt energy efficiency measures that will improve environmental quality and “security,” while placing a tax on economic output? Round two is similar, with a couple surprises. First, my wind farms are in trouble:

Ironically, my attempt at developing renewable sources was thwarted by the very global warming I am concerned with! Next, my solar program is in trouble:

I’m a bit confused by this one. After all, all energy costs money. Solar panels can only be “too costly” if cheaper alternatives are available. What these options are – continued petroleum, nuclear, or some other source, is not explained. In this round my fossil fuels are unaffected by catastrophe.

Repeated playing revealed other game paths have other possible events. In one case, solar panels become more attractive to homeowners due to net metering policies, and two actually make wind power even more attractive due to vaguely specified improved technology or other benefits. If you invest in nuclear it warns you uranium may increase in price due to global demand. Once, a terrorist attack in the middle east tightens oil supply. But petroleum price and supply rarely plays a role in the problem – despite the historical evidence as recently as the summer as 2008 that it can be subject to major price volatility. (Incidentally, I think the game was created in 2007.)

In the end, is this a fair simulation? Despite the capricious nature of some of the factors, most of the assumptions are probably reasonable. Presumably Chevron is too savvy to deliberately plant obvious biases in some of the assumptions, nevertheless I’m sure a serious energy wonk could find plenty to quibble about. However, like too many models, Energyville doesn’t clearly reveal its underlying assumptions, or allow the user to question or manipulate them. Although the limits placed on the speed alternative fuels can be rolled out are probably derived from mainstream sources, history shows change — whether beneficial or catastrophic — can be surprisingly rapid.

This means Energyville misses a major educational opportunity. (Despite it appearing on an educational blog – the only Technorati link to the site.) The flash interface makes it impossible to copy text and contains no links to external sources, and the “about” page lists dozens of unlinked articles, reports, and websites, and no assumption is presented as contested. Although thousands of players may learn a few facts embedded in the game, or gain a vague sense of the benefits and limitations of various energy sources, it doesn’t support serious examination and debate about energy technology or policy. But maybe that’s the point.

> WillYouJoinUs.com

> Web Tools for Participation and Collaboration in Planning

Within government, data can be a powerful tool for management and service delivery. Baltimore’s CitiStat and its emulators have shown the power of data to focus on the bottom line for easily quantified government services and policies. Applications for e-management within government are many, and today’s New York Times story on IBM’s Smarter Cities initiative describes several.

Outside of government, the case is less clear. Some at the conference questioned whether governments should expend their limited resources on finding, cleaning, and publishing data. I think this debate is largely won. The costs of hosting data has dropped precipitously, most of the datasets have already been purchased by citizen tax money, and the resulting apps really do seem to create new value for city residents. Less clear, however, is whether disclosing data to the public will have any impact on urban policy.

It is this deeper question that lurks in the background of conversations about data: although more and more may be available, does influence urban policy or planning? A conference attendee who works for the mayor of a major east coast city suggested this at one point: in his opinion the city was driven by politics, not data.

On the one hand, data seems very needed in planning. Urban planners analyze data to understand trends, and every city plan contains detailed tables, charts, and data analysis. Outside government, community development corporations and nonprofits are also frequent data users: for grant applications, advocacy, and to explore trends in urban neighborhoods. In fact, hundreds of government planners, nonprofit employees, community activists and citizens came to the conference I helped organize here in Boston last summer titled “Data Day: Using Data to Drive Community Change.”

However, the cynic will retort there are “lies, dammed lies, and statistics.” Certainly, government planners and activists need data, the argument goes, but it’s just to support their particular agenda or policy. Taken to the extreme, this jaded view says you can find statistics to back up any belief.

This wasn’t always the case. In fact, for a brief period in the 1960s there was a great deal of interest about the possibility of establishing “social indicators” analogous to economic indicators. Just as economic indicators, such as unemployment rate, are used to determine economic policy, social indicators would guide social policy. Judith Innes in her 1975 book Social Indicators and Public Policy argued social indicators could be created, but must rely on a consensus understanding of definitions and measurement. The book’s fascinating history of the unemployment rate shows how the measurement has responded to cultural values about who to count. Despite thousands of books and articles on indicators in the late 60s and early 70s, the movement didn’t take off as expected. Defining social indicators was value-laden, collecting social data expensive, and focusing on data seemed irrelevant to a turbulent, problem-filled world. It’s little wonder when the second edition of Innes’ book appeared in 1990 it was re-titled Knowledge and Public Policy.

Although falling short of her definition of an indicator, many government datasets do provide a common framework for discussion and analysis, even perhaps guide policy creation. Although often imperfect, their flaws are well known by all users. In the 1990s, a number of “indicators” projects emerged, organized as the National Neighborhood Indicators Partnership. Generally based in nonprofits or foundations, these projects took advantage of new technology and plentiful government data to track measures of their choosing. (At MAPC, I worked closely with the Boston affiliate – the Boston Indicators Project)

Today, thanks to rapidly evolving technology more urban data is available than ever. Its role is equally ambiguous, simultaneously in demand by diverse users to use for advocacy, government service delivery, and perhaps crafting urban policy. At the conference, federal officials reminded the group the Obama administration is interested in evidence based governance, and President Obama even elevated the former architect of the D.C. data catalog, Vivek Kundra, to the nation’s first Chief Information Officer. In an interesting way, perhaps during times of concern for the public interest we are more likely to view data as a shared resource for deliberation and discussion of new policies and plans. We may be in a new era of data availability, but as always what matters isn’t the numbers themselves, but how we view them.