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Tag Archive: policy research

Oakland’s Public Participation Route to Open Data Legislation


Steve Spiker and Eddie Tejeda (open data policy organizers) sharing OpenOakland’s work at East Bay Mini Maker Faire. Oakland passed an open data law earlier this month (October 15, 2013) that was generated by the people and for the people. Open Oakland captain Steve Spiker (Spike) gathered the Open Oakland and broader open government community to draft and chat the best open data policy for Oakland. Spike and Open Oakland, in addition to garnering support for the open data policy, cultivated the policy from start to finish through drafting, public comments, a call to experts, and [teleconferenced] public meetings. Open Oakland serves as an excellent example of the community's role in generating open data policy, and their public input process is an exemplar route to  incorporating public perspectives into policy. The Sunlight Foundation's Guideline to incorporating public perspective into policy implementation reads as follows:

Implementing the details of an open data policy will benefit from public participation. Open data policies not only have effects government-wide, which will require consideration, but also have consequences for a variety of stakeholder groups outside of the government. Allowing these groups to participate in the decision-making process (and make real contributions) can have great benefits for policy creation and execution. Stakeholders and experts can bring to the table valuable new perspectives that highlight challenges or opportunities that might not otherwise be obvious. Formal mechanisms for collaboration can include hearings, draft proposals open for public comment and contribution, and online resources like wikis and email lists.
Below we have outlined Oakland's public input process and how it is part of a growing trend to openly include community perspective, desires, and concerns into open data policy.

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Your Guidelines to Open Data Guidelines Pt. 2: Stages of Development


In revisiting Sunlight’s Open Data Policy Guidelines for our Version 2.0 release, we took a closer look at other sources for open data guidance that have been released over the years. To see a comprehensive round up of open data guidance (complete with a timeline!) see Part 1 of Your Guideline to Open Data Guidelines: The History.

Although it’s only been eight years since the first resource of this kind was created with the Open Knowledge Foundation's Open Knowledge Definition, exploring open data guidance in its totality not only shows how much these recommendations build on each other, but how the movement has matured. Moreover, many of these resources occupy separate-–but overlapping-–arenas of expertise, though an outside perspective may not immediately catch their nuances. Below, we’ll explore in more detail the three major themes of open data guidance: How to Define Open Data, How to Implement Open Data, and How to Open an Open Data Discussion.

The sequence, prevalence, and layering of these themes showcase the developmental stages of the open data movement thus far. Over the years we have seen open data advocacy emerge from its nascent expert-driven defining period to becoming (quite self-referentially) a public discussion. We’ve seen different missions of the major players in the open data movement inform nuanced definitions and implementation recommendations, and we have seen an increase in best practice assessments, academic critique, and diverging schools of thought.

To understand this larger story, let us look at each piece.

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Your Guideline to Open Data Guidelines Pt. 1: The History


Last summer, Sunlight released a series of Open Data Guidelines in reaction to a surge of municipal open data policy making. In anticipation of revamping these policies this summer (to add fresh context, ideas, and exemplary language) and in reaction to a recent surge in open data policy collaboration as evidenced by the interactive Project Open Data and the newly public (beta) Open Data Stack Exchange (or maybe more accurately in reaction to the Meta Open Data Stack Exchange...), we wanted to provide a roadmap to the world open data resources and recommendations that are available to put these resources in context of their evolution over time–a guideline to Open Data Guidelines, if you will. The first step in navigating the open data guidelines out there is to examine the chronology of how they surfaced.

The timeline below provides a landscape of current open data policy guidelines, guidance, and principles that exist and showcases the chronology in which they have manifested, each guideline often directly building off of (or crafted in reaction to) its predecessor. Looking at these guidelines in context exposes the pragmatic and technical evolutions in thought that have occurred under the banner of open data pursuit: from the foundational drive to define what information is legally available (through FOIA and other public records laws) to the trailblazing concept of proactive disclosure (where "public" access means "online" access) to establishing the qualities that make data more accessible and usable (emphasizing structured, bulk data, unique IDs, and APIs). The dialogue for discussing open data policy guidelines has itself evolved from the gathering of smaller open government groups of: Open House Project, Open Government Working Group, the Open Government Initiative, and early collaborative efforts such as the Open Gov Handbook, to the editable Project Open Data and the Q&A Open Data Stack Exchange.

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The Landscape of Municipal Zoning Data


Zoning impacts the most physical elements of communities and impacts people's daily lives. When it comes to being transparent about the zoning process and its outcomes, many local governments are posting information -- one way or another -- on their websites. It's a varied landscape, but it is worth assessing to see where there might be room for improvement.


It's not surprising, in a way, that so many local governments choose to proactively release various kinds of information related to zoning. Zoning regulations can impact everything from what can be built and where it can be built to how it can be built and more. How a lot is zoned doesn't just determine whether that land can be used for commercial or residential purposes (or something else entirely) -- it can also determine the very structure of buildings down to details like height and square footage. Zoning and planning ordinances can even impact how close certain kinds of buildings may be to one another -- schools and liquor stores are one example of a spatial relationship that is sometimes regulated. Zoning has an impact on many of the most concrete aspects of a municipality, and this makes it an issue that's of interest to residents, business owners, developers, and many other groups. This means zoning can also be a prime target for people who want to game the system to obtain influence over this important aspect of cities.

Madison-street-viewThe zoning process generally consists of elected or appointed officials making decisions about how land can be used and the specifications of structures. It has a direct impact on the shape communities take. The zoning process, and what it controls, however, varies from place to place. That means it's important for each municipality to be clear about what its process is so policymakers, residents, and businesses alike can all understand this powerful issue. For this look into the landscape of zoning data, we're including information most directly related to the process and its outcomes. We're not including other data that might be tied to land parcels, like data about tax breaks or special tax zones. Not all zoning data is created equal, of course. Some cities simply release a list of the ordinances related to zoning, others release PDF maps of how land parcels are zoned, and some have interactive maps with layers of information. To have open zoning data, a municipality should have structured data available online that makes it easy for people to analyze and reuse -- in addition to information that enables people to understand the zoning process.

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Open Data Policy Evolution: San Francisco



Since the release of Sunlight’s Open Data Policy Guidelines last June, Chicago, Madison, Montgomery County, and Utah have all enacted open data laws, and the states of Hawaii and Ohio are both in the process of enacting open data legislation. However, the recent amendment of San Francisco’s two-and-a-half-year-old open data ordinance (ancient in the open data policy world) demonstrates a new frontier for these policies: Evolution.

San Francisco is unique in having been one of three cities to have an open data policy enacted before the federal Open Government Directive and in being the only city that has revamped their open data policy not once, but twice: first in 2010, expanding their bare bones 2009 executive order into a longer, more robust administrative code, and for a second time in late March 2013, amending the administrative code language.

Sunlight identified in our Open Data Policy Guidelines the importance of future review for potential changes to policy and law, and we were glad to see that San Francisco’s most recent amendment not only incorporated many more of Sunlight’s Guidelines, but also broke ground in the United States municipal open data policy world -- arguably taking the title from New York City. Of significance, San Francisco’s amended ordinance creates new oversight authority to review implementation of their open data policy requirements (Sunlight guideline #27) by creating the position of Chief Data Officer (CDO) and requiring the appointment of Department Data Coordinators (DCs) to assist in the implementation of San Francisco’s open data policy. The CDO is tasked with working with DCs to create an open data plan for each Department including: “a timeline for the publication of the Department’s open data and a summary of open data efforts” (#22) and “a summary description of all data sets under the control of each Department” (#18). The CDO is also responsible for creating an annual citywide implementation plan, while each department is delegated to conduct quarterly reviews of their progress, the combination of which sets up procedural expectations that help ensure data quality (#17). The amended language also calls on the CDO to produce analytics on the use of San Francisco’s data portal, DataSF, (as recommended by guideline #32 and incredibly important in determining usefulness and in cost benefit analysis), but unfortunately does spell out specific requirements of these analytics.

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