ADDING ASSETS TO NEEDS: CREATING A COMMUNITY DATA LANDSCAPE
Margaret M. Roudebush, MNO, is the Director of the Center for Research and Scholarship,
School of Nursing at Case Western Reserve University.
Robert L. Fischer, Ph.D. is a Research Associate Professor and Co-Director of the Center on
Urban Poverty & Community Development at the Mandel School of Applied Social Sciences at
Case Western Reserve University.
Jeffrey L. Brudney, Ph.D. is the Betty and Dan Cameron Family Distinguished Professor of
Innovation in the Nonprofit Sector in the Department of Public and International Affairs at the
University of North Carolina Wilmington.
The nonprofit sector is increasingly focused on using data to inform practice. Social and economic
indicators describing the needs of communities are readily available, but data on community assets are
often hard to find. This article critically reviews the movement underway to bring together both
community indicators of need as well as data on community assets in a common data portal. These portals
have emerged largely outside the purview of academic researchers, nonprofit practitioners, philanthropic
funders, government and community leaders and service users. Although the initiatives provide powerful
frameworks for the collection, display, and analysis of community data, they do not meet all the needs of
these highly disparate audiences. This article reviews these new community geographic data systems,
discusses the advantages and challenges of launching and sustaining them, and presents suggestions
regarding next steps for development in this field.
INTRODUCTION
A movement is underway in the nonprofit sector that will make geographically-based social
and economic indicators along with community asset data more widely usable and available.
With such titles as National Neighborhood Indicators Partnership (NNIP), Open Indicators
Consortium, and Community Platform, these systems have the potential to support and change
decision-making in communities in general and in nonprofits in particular. Yet, the identity and
characteristics of these systems are largely unknown to nonprofit scholars, practitioners, leaders,
funders, and clients. Moreover, although these systems have captured the attention of some
nonprofits, governments, and funders, the challenges and opportunities they confront have not
been sufficiently discussed in the scholarly literature. In this article we examine the development
of community geographic data systems across the United States, illustrate their potential by
reviewing applications operating in various locations, describe the challenges confronting these
systems, and make recommendations for further use and expansion.
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A WEALTH OF DATA
The rapid advance of geographic information systems and other information technology; the
increasing availability of tax and other records pertaining to nonprofit and public organizations
and the broader community; and the development of integrative tools to interlink these rich
resources spatially have given practitioners, scholars, and leaders unparalleled access to a wide
variety of data organized by geographic location. Many local community data system initiatives
are underway working to provide a visual snapshot of the needs of the community through
demographic and socioeconomic data together with community asset data provided via nonprofit
organization, Internal Revenue Service (IRS), and service provider data. These community
geographic mapping systems provide decision-makers with an array of information tied to
location that could not have been imagined even a few years ago.
In the early 2010s, the technology exists to provide in a single geographic database a large
volume of useful information, such as finance and tax, program spending and outputs, emergency
services and shared resources, and community needs and resources, all of which can be viewed
spatially (Urban Institute, 2011). Tailored to meet the needs and preferences of individual
communities, these systems can integrate some or all of these features or modules. The data
systems can also be designed to focus on specific “industries” in the community in which
nonprofits are actively involved, such as early childhood education, prenatal services, or low
income housing. Another advantage of these systems is that they offer the convenience and
simplification of providing disparate community data and indicators in a single portal.
Consequently, these systems would appear to have great appeal—and use—for a range of
community stakeholders. Since the databases may over time incorporate information, community
planners can utilize them to depict, understand, and anticipate complex community needs, trends,
and growth and decline patterns, as well as experiment with “what-if” scenarios, both
geographically and longitudinally. These systems bring together diverse data that can facilitate
comprehensive analysis and planning. For researchers, these systems can yield data useful for
basic research as well as applied projects that respond directly to immediate circumstances and
needs in the community.
For government decision-makers, the geographic data systems offer potential for discovering
previously hidden community assets that might be brought to bear on public problems, as well as
revealing unfortunate shortfalls and voids that ought to be addressed. Examples of hidden assets
include such resources as a local food pantry or an after-school program that may be unknown to
government (or other) decision makers due to the lack of public funding, but which may be
revealed through a GIS (geographic information system) community portal populated by local
community data. The systems attempt to compile local investment of nonprofit, public and
private organizations, and persistent service needs, in particular service domains, such as
unemployment and health care. The availability of better, more comprehensive information can
possibly turn discussion, debate, and deliberation from a focus on “government budgeting” for a
particular service to a refined emphasis on “community budgeting.”
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For individual citizens and groups interested in making a difference in their communities, the
geographic data systems identify areas where they can be more involved, for example, through
donating and volunteering. Conversely, for families and individuals requiring assistance in such
areas as nutrition, childcare, job training, and housing these systems can show where and how it
might be obtained in the community. For diligent funders, too, these geographic data systems can
help to provide guidance in identifying and quantifying community needs, deploying scarce
philanthropic resources to meet them, demonstrating the impact of these benefactions thereby
“moving the needle” on community conditions.
To this listing of stakeholders, we would add nonprofit organizations -- whose financial, tax,
and program data typically constitute the backbone of these systems. For nonprofits, which are
frequently exhorted to consider the advantages of merger, consolidation, collaboration, shared
facilities and “back office” operations with other agencies (Fischer, Coulton, & Vadapalli, 2012),
having ready access to information on potential partners is crucial. These systems can provide the
impetus to forming collaborations, partnerships, and broader associations among nonprofits (as
well as with government agencies and private firms) that may share information, resources,
referrals, and the like to rationalize service delivery. Alternatively, for nonprofits committed to
making a go of it on their own -- much like their counterparts in business and government -- these
systems are equally valuable in understanding the marketplace for particular services and
appreciating the dynamics of location and catchment area (Paarlberg & Varda, 2009).
These mapping tool platforms also provide a mechanism to collect data on the many
nonprofit organizations that fall “under the radar” of IRS reporting requirements by using local
nonprofit data such as United Way 2-1-1 information and allowing organizations to register with
the community data system and update their information. As Brent Never observes, “By
providing a map, we provide legitimacy not only to the entire sector, but especially to those
organizations that slip through the formal taxonomies of those who belong in the ‘official’
sector” (2011, p. 187). In this manner, the data systems enable a larger voice for the smaller
nonprofit. Smaller nonprofits and faith-based organizations are often at the heart of a local
community, providing tailored assistance where needed most. Yet, these nonprofits are usually
not required to register with the IRS and may go undetected through the usual data tracking
mechanisms. In the local data system, though, faith-based and smaller nonprofits may enter the
arena of community service provision. Their activities can then be recognized and made more
visible to the larger community, including donors, volunteers and clients. They have an incentive
to participate in the local GIS portal to gain partners, allies, funders, and other supporters. Sandi
Scannelli, President and Chief Executive Officer of the Community Foundation of Brevard,
Florida, reports, the Brevard County Community Platform (“Connect Brevard”) “brought small
nonprofits to the table, where they typically don’t have a table” (Urban Institute, 2012).
TAKING STOCK OF THE MOVEMENT
Over the past 20 years, several initiatives have aimed at increasing access to community-level
data. As technological advances have occurred in storing, hosting, and presenting data and
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information electronically, these initiatives have rapidly increased clustering around several
goals. Many community data efforts develop organically in response to specific regional needs
for data. Several initiatives have emerged to coordinate and support the development of
community data by providing an organizational host or forms of self-governance. Table 1
summarizes basic information on major multi-site initiatives. Dating to 1995, these efforts
include the National Neighborhood Indicators Partnership, the Open Indicators Consortium,
United Way’s 2-1-1, the Urban Institute’s Community Platform, and the Foundation Center’s
Philanthropy In/Sight.
TABLE 1: EFFORTS TO EXPAND COMMUNITY-LEVEL DATA ON NEEDS ASSETS
Member
Statement of
Initiative
Host
Launch
Sites
Objective
National
Urban Institute
1995
36
To further the
Neighborhood
development and use of
Indicators
neighborhood-level
Partnership
information systems in
community-building
www.neighborhoo
and policymaking.
dindicators.org
2-1-1
United Way
1997
In all 50 2-1-1 provides an easy
Worldwide/
states
way for everyone to
http://211us.org/
Alliance of
access comprehensive
Information &
and specialized
Referral
information and referral
Systems
services to their
(AIRS)
community.
Open Indicators
Consortium/WEA
VE
 Local/regional
United Ways and
partners
University of
Massachusetts
Lowell
2008
15
To transfer publicly
available data into
visually compelling and
actionable indicators to
inform public policy
and community-based
decision makers.
 Members of the
OIC
 The John S. and
James L. Knight
Foundation
 The Barr
Foundation
Urban Institute
2010
9
To support
transformative
community change by
enabling publicspirited citizens and
nonprofit organizations
to work together in new
and more effective
ways.
 The Boston
Foundation
 The Charles
Stewart Mott
Foundation
 The Kresge
Foundation
www.openindicato
rs.org
The Community
Platform
Initial/ Ongoing
Funders
 The Annie E.
Casey Foundation
 The John D. and
Catherine T.
MacArthur
Foundation
www.urban.org/ce
nter/cnp/projects/
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Figure 1 shows the location of the sites involved in these initiatives (with the exception of 21-1 and Philanthropy In/Sight, both of which exist much more broadly across the United States).
All of these community mapping platforms claim to provide an important tool to bridge the
information gap between the needs of the community and the areas served by nonprofits. We
examine them more closely below.
FIGURE 1: LOCATION OF COMMUNITY DATA SITES
Tracking Community Conditions
A primary goal of these tools has been to create publicly-available (usually web-based)
portals housing data on community needs and conditions. These efforts have as a central feature
developing indicators of community conditions and making them available at varying levels of
spatial geography. The National Neighborhood Indicators Partnership (NNIP) is one of these
efforts; it focuses on building local capacity to maintain regional data repositories to further the
development and use of neighborhood information systems (Urban Institute, 2012a). NNIP works
to make available a range of social, economic, and environmental indicators based on local needs
and the organizational capacity and mission of each NNIP partner site.
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Hosted by the Urban Institute, the National Neighborhood Indicators Partnership includes
partner sites in 37 cities. The sites develop indicators related to such topics as births, deaths,
crime, health, educational performance, public assistance, and property conditions. Because a key
goal of NNIP is democratizing information, a central tenet involves “facilitating the direct
practical use of data by city and community leaders, rather than preparing independent research
reports.” These sites have adopted as a primary purpose “using information to build the capacities
of institutions and residents in distressed urban neighborhoods” (Urban Institute, 2012b). The
NNIP has drawn on the network’s collective capacity to expand knowledge in such areas as
public health, early childhood and school readiness (Howell, Pettit, Ormond, & Kingsley, 2003;
Kingsley & Hendey, 2010). Figure 2 provides an example of a map showing a NNIP community
indicator, population change.
FIGURE 2: EXAMPLE OF COMMUNITY INDICATOR MAP
[Reprinted with permission from Data Driven Detroit]
The Open Indicators Consortium (OIC) consists of universities, community organizations,
foundations, and regional and state agencies that have come together to promote access and use
of high-quality data pertaining to community indicators, services, and government performance.
Launched in 2008, the OIC has 16 sites organized in a collaborative network around the
development and refinement of “Weave,” an open-source platform. The OIC formed “to support
and guide the development of Weave and its application as a high-performance open source data
analysis and visualization platform free to all” (Open Indicators Consortium, 2009). Weave
enables the user to visualize social indicator data, and the patterns underlying them, nested within
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and across geographic locations, whether neighborhoods, municipalities, states, regions and
nations. Weave is supported by a sliding fee-based membership (www.openindicators.org).
Mapping/Accessing Community Assets
A related dimension of the movement toward community data platforms has focused on
geographic displays of information about community assets and resources. The premise for this
approach is that needs assessment also requires identifying and understanding community assets
as a central feature of community conditions, and that positive community change emanates from
an asset-based approach (Kretzmann & McKnight, 1993). In practical applications, this premise
often led to the creation of community maps that revealed not only needs but also key assets such
as schools, parks, community gardens, nonprofit organizations, and governmental services. Such
maps are useful in informing community planning efforts but are restricted by the detail available
on the particular assets, and can quickly become dated. We return to this issue later in our
discussion of challenges to these community data systems.
In addition to its benefits for community planning, resource mapping is crucial in connecting
individuals and families in need with relevant and proximal community resources. Since 1997,
the United Way has undertaken a national effort to meet community needs through its 2-1-1
referral systems. Originally, 2-1-1 systems developed as telephone-based referral points for
individuals seeking assistance in a wide range of service domains including food, housing,
employment, childcare, mental health, substance abuse, and more. The 2-1-1 systems have
gradually migrated to the Internet so that they allow individuals to search for referrals in their
area with the aid of geographic mapping.
Merging Data on Community Conditions and Assets
The most recent initiative in the movement toward community data systems is to bring
together data on needs and assets in a single, dynamic system. Launched in 2010, the Urban
Institute’s Community Platform, is the most notable example. Under development or in operation
in over 10 states and counties nationwide, the Community Platform provides sites access to base
data on community conditions from the U.S. Census Bureau. This information includes
population and social/economic data from the American Community Survey. In addition, sites
receive relevant data on nonprofit organizations (i.e., 501c3’s that serve the region encompassed
in the community platform, ranging from single cities to multi-county areas, to entire states,
based on IRS Form 990 data (Urban Institute, 2011). The data on nonprofit organizations include
geographic location, core services, size and history (e.g., year of incorporation). According to the
Urban Institute, easily accessible core data allow participating sites to launch a community
platform at relatively low cost (an estimated $20,000-40,000 for initial start-up) that provides
basic data on community conditions and resources. Sites can also upload locally-available data
from nonprofits operating “under the radar” (see above) as well as other information such as
crime rates, housing/business foreclosures, and local school and district performance. Individual
nonprofit organizations can add data about their programs and services to the sites to enhance the
information available. Figure 3 illustrates how a community platform brings together or maps a
community need (in this case child poverty rates) with community assets (relevant human service
agencies) to address the problem.
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FIGURE 3: EXAMPLE OF COMMUNITY MAP SHOWING SERVICE LOCATIONS AND NEED INDICATOR
[Reprinted with permission from the Louisiana Initiative for Nonprofit & Community Collaboration
(LINCC)]
Another unique mapping platform, Philanthropy In/Sight, focuses on grant makers and grant
recipients data overlaid with demographic and socio-economic data. The Foundation Center
leverages its wealth of institutional philanthropy data to create an interactive mapping tool for
grant makers, grant seekers, policy makers, researchers, and service providers where they can
display giving patterns, analyze foundation impact, or see areas of greatest need. Launched in
2009, users can select from a wide range of customizable options to create maps revealing
funding and giving patterns locally, regionally, nationally and globally, and overlay the data with
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a choice of over 200 demographic, socio-economic and other data sets. The data sets come from
a variety of national and international sources including the U.S. Census Bureau, the Social
Science Research Council’s American Human Development Project, the United Nations Annual
Human Development Report, the Data Catalog of the World Bank and many other government
agencies (Foundation Center, 2013). The mapping makes evident areas where funding exists,
areas of limited resources and allows a direct comparison to community need. Features allow the
user to drill down to reveal detailed information on organizations, funders, and recipients. The
Foundation Center customizes the platform for specific community needs or areas of interest, and
pledges to update the philanthropic data weekly, and demographic and socio-economic data as it
becomes available. While data is available at the local level, by zip code, city or metro area, the
system does not allow direct data input by individuals or community organizations.
CHALLENGES TO THE MOVEMENT
The considerable benefits and advantages of these community geographic data systems
notwithstanding, like any other management or research tool, they confront challenges that
should be taken into account.
Data Access
Community data systems are powered and limited by the underlying data available. Though
some data are publicly and readily available (e.g., Census Bureau), access to many other types of
data must be negotiated at the local and regional levels. Such data often emanate from
administrative databases maintained by public entities as well as nonprofit organizations
operating in a specific domain. These data pertain to such phenomena as crime, early childhood
services, use of public assistance, child mistreatment, court involvement, school performance,
and unemployment. Such data often require the negotiation of data use agreements between the
data provider and the community data repository and may involve costs associated with
providing and processing the data. Negotiations may need to address such topics as data security,
protection of human subjects, as well as compliance with relevant protections under federal law
(i.e., Health Insurance Portability and Accountability Act of 1996 [HIPAA], Family Educational
Rights and Privacy Act of 1974 [FERPA]). Such considerations have implications for the level of
data availability (i.e., individual or group); the need for review of these systems by Institutional
Review Boards when universities are involved, and the possible requirement of informed consent
procedures in obtaining particular individual-level data. Normally, such concerns do not extend
to publicly-available data such as those provided through the Community Platform, but they are
relevant when sites pursue locally-available data for inclusion in their community geographic
data systems.
Data Quality
Community data systems earn credibility in communities by having data that are accurate,
recent, and available for the geographies relevant to users. Typically, better performance on each
of these dimensions requires higher burdens placed on the data partners and greater costs
associated with managing the data system. More accurate data are achieved by understanding the
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institutional processes that generated the data, subjecting files to data cleaning procedures, and
even suppressing some data of lower reliability. In order to be useful, data provided by local
entities must be subjected to routinized approaches to cleaning and verification. Even national
data that have been subjected to extensive analysis are fraught with serious weaknesses and
errors, such as with IRS Form 990 data (Froelich & Knoepfle, 1996; Froelich, Knoepfle, &
Pollak, 2000). The risk of analytic errors becomes even more of a concern when dealing with
smaller geographies such as those used in local level data portals.
Data systems require continuous updating of data in order to meet the real-time demands of
users. More recent data are achieved by having more frequent data extracts from relevant sources
and timely processing of these data for inclusion in the community data system. Some data,
however, may be available only at specific intervals due to limitations or procedures adopted by
various data providers. Geographically relevant data are achieved by having source data that can
be geo-coded into a range of geographic boundaries or jurisdictions (for example, municipalities,
neighborhoods, city wards or districts, etc.). Yet, street address information may be considered
identifying information that is protected by the data provider and may be suppressed prior to
transmission. Providing for the accuracy and updating of the data in these portals must be taken
into account in system funding.
Access to nonprofit organization data raises its own set of challenges. Available literature has
certainly benefitted from the accessibility and digitizing of IRS Form 990 data for nonprofit
organizations, but this same research has also documented the limitations of these data, which are
exacerbated at the local, community level as in the nonprofit geographic data systems described
in this study (Froelich & Knoepfle, 1996; Froelich, Knoepfle, & Pollak, 2000; Roudebush &
Brudney, 2012). IRS tax data may only capture as little as 10 percent (Smith, 1997) to as much
as 75 percent (Salamon & Dewess, 2002) of nonprofit organizations. As in any data-driven
system, the results must be limited by the quality of the input data.
Data Visualization
Community data systems seek to convey information about the scope and scale of community
issues and assets and their geographic location. Presenting such information in the most usable
fashion remains a distinct challenge for data systems. Often systems allow the creation of tabular
information and/or location data in map form. Such output can be very useful but can have
limitations as well, particularly for specific users. For example, individuals seeking a childcare
facility may be able to use a map to find a nearby provider but may need to search other sources
to find detailed information on the program, its quality, and availability in real time. Similarly, a
funder of after-school programs may be able to see on the map the programs that exist in an area
but may need to use other means to assess whether a shortage or surplus of services is available.
Recent developments in the field include strategies to integrate geographic and tabular data so
that users can see multiple presentations of data in an interactive fashion. Such data visualization
techniques allow users to more intuitively explore the relationship between social conditions and
their geographic spread. The Open Indicators Consortium is (re)developing and refining the
Weave open-source application around such strategies.
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Sustainability of Data Systems
Even with the facilitation and technical support provided by such entities as the Urban
Institute (2011) for one of the geographic data systems, the Community Platform initiative,
funders must step forward to underwrite these systems locally. Despite the evident benefits of
these systems, as yet only a handful of communities have been able to mobilize the financial
commitment (for example, the 12 sites for the Community Platform shown in Figure 1). This
situation is aggravated by the fact that these data systems require not only start-up funding but
also ongoing, operational support—the kind of “ask” that oftentimes presents a more daunting
challenge. Although considerable community interest may accompany (and motivate) the launch
and front-end investment in such systems, community data systems require a significant
investment of funding and data over their useful life cycle.
These systems thrive when data agreements are reliable and provide for regular updates over
time. Commitments for data access can be difficult to maintain, especially when the
organizations that provide data experience organizational and leadership changes that impact data
sharing philosophies. Changes in elected or appointed leadership in public agencies or in
CEO/board leadership positions in nonprofit organizations can lead to disruptions or restrictions
in data access. Negotiations for data access must consider how to develop arrangements that are
reliable and durable over time and resistant to organizational changes. Similarly, the funding
required to host and maintain data systems should be developed toward a multiple year horizon.
Start-up funding partnerships are crucial, but systems will require sustained core funding over
time to support further growth, applications, and functionality of such community data systems.
As communities change and evolve, additional funding may be necessary to underwrite specific
projects, special analyses and reports, dissemination activities, and system extensions.
Technological Divide
Although the goals of these systems typically embrace “community building” (Urban
Institute, 2011), access to the interactive GIS technology is not distributed evenly throughout the
relevant communities of either residents or nonprofit organizations. Those who may need the
technology and data most, both individuals and organizations, may encounter greatest obstacles
to locating and using them. Portions of the data, or access to the geographical information system
itself, may remain proprietary or restricted to a membership group who can best afford it, thus
limiting involvement and benefits for the entire community. Another challenge involves building
community capacity to use these data systems, which can present a formidable task to those new
to the technology. Unless marketing, education, and training are provided—and budgeted—
residents, families, and other individuals, as well as charitable and nonprofit organizations, will
not know that these resources exist and how to use them effectively. And not all nonprofits will
be enthusiastic about having their organizational information posted on a public website that is
not controlled by them.
Assessing Program Quality: Nonprofit Rating Agencies
Ideally, community geographic data systems, such as the ones discussed here, would provide
information indicating which nonprofit organizations are best suited to respond to a community
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need (Never, 2011). Yet, available data on the existence of a nonprofit organization(s) does not
convey information about the performance of the nonprofit, who it serves, or how effective it is.
In an attempt to make up for this shortcoming and generate high quality data for informed giving,
several organizations have been founded with the goal of rating nonprofits and publishing
evaluative information about them on the internet. Most of these watchdog organizations rate
nonprofits based on financial information from IRS Form 990 and annual reports, and many are
limited to large organizations with revenues over $1 million. GuideStar, an online reporting
service, covers the broadest range of nonprofit organizations, hosting information on over 1.8
million of them, but it is still limited by a lack of performance or effectiveness measures
(GuideStar, 2012). The focus on providing information to aid in donor decision making does not
include discussion of geographical areas served, area service competition, duplication of services,
or service gaps. The movement toward community geographic data systems aims to provide such
information. System designers and funders should endeavor to integrate the evaluative data from
the rating agencies to provide a more complete picture of the community nonprofit landscape.
CONCLUSIONS
Community geographic data systems have emerged in the absence of great scrutiny from
practitioners and academic researchers. Accordingly, in this article we have described the
different systems that encompass the movement toward community geographic data systems,
illustrated their considerable advantages, and elaborated the serious challenges that must be
confronted to realize their full potential. In our view, these systems can be a highly useful tool to
promote positive community change provided they are used and embraced broadly across
relevant stakeholders in the community. We believe that the joint mapping of socio-economic
needs alongside nonprofit resources can help to promote knowledge, engage community
discussion, and enable more efficient use of resources as gaps as well as duplication in services
are more easily identified.
The design of community geographic data systems will benefit from increased attention to the
interests of various stakeholders, as well as funding arrangements that provide for both start-up
and ongoing developments and changes. For communities to realize the potential advantages of
such data systems that will allow for dynamic analysis of both needs and assets of a community,
plans must be built on a sustainable model. In addition to providing high quality data in a timely
fashion, a marketing, and education plan must be put in place to encourage and train public,
private and nonprofit leaders and individuals to use and support the system. Plans must include
the participation of data providers along with data users. The design and implementation process
merits the kind of systematic scrutiny we have endeavored to present in this article.
Given its distinctive history and service-delivery patterns, each interested community will
likely approach creation and implementation of a community geographic data system somewhat
differently. The lack of standardized measures threatens the usefulness of the data beyond the
local community. Nevertheless, we anticipate that the reliance on the same established sources
for most data, such as the U.S. Census Bureau and the Internal Revenue Service, will help to
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standardize data collection for use by nonprofit managers for benchmarking and scholars for
comparative research. Because local governments and philanthropic funders might have the most
to gain from these systems with respect to increasing their ability to make informed decisions,
they might reasonably be expected to take a leading role in this process.
As pointed out at the outset of this article, the emergence of community geographic data
systems has outpaced academic attention to them -- despite their importance for both government
and nonprofit practitioners and academic researchers. We have been able to provide the current
state of the art, which combines disparate threads and developments, but many questions and
issues lie beyond the scope of our inquiry as well as available data and published research. First,
although the community portals vary by host site, we do not know the advantages and
disadvantages of their different features. Second, at this writing we have not been able to obtain
information on the operation of these systems, including the crucial questions of data accuracy
and updating. Third, research has not yet assembled evaluations from the various stakeholders
that will be key to the further development and improvement of these community data systems.
With such new information, we could begin to offer informed advice concerning whether the
potential benefits of these data portals warrant some form of federal or state reporting mandate to
participate in data collection. We are at work investigating these questions and hope that our
continuing study will inform academic research, community practice, and public policy
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