US Government Linked Open Data: Semantic.data.gov

May/June 2012 1541-1672/12/$31.00 © 2012 IEEE 25Published by the IEEE Computer Society

L i n k e d O p e n G O v e r n m e n t d a t aL i n k e d O p e n G O v e r n m e n t d a t a

US Government Linked Open Data: Semantic.data.govJames Hendler, Rensselaer Polytechnic Institute

Jeanne Holm, Jet Propulsion Laboratory

Chris Musialek, US General Services Administration

George Thomas, US Department of Health and Human Services

This article discusses

Data.gov, the

world’s largest open

government, data-

sharing website, and

the use of linked data

in some of the site’s

community pages.

innovation and startup activities outside the government and improve service provision within it. One particular focus of such data sharing is open government data (OGD), the sharing of machine-readable datasets cover-ing government activity.

In recent years, OGD has emerged as a vital communication channel between gov-ernments and their citizens. Numerous na-tional and international Web portals have been deployed to release OGD datasets online. The four largest sites to date are in the US (www.data.gov), the UK (www.data.gov.uk), France (www.data.gouv.fr), and Singapore (www.data.gov.sg), and on-line catalogs index more than a hundred other websites from countries, states, cit-ies, nongovernment organizations (NGOs), and other entities. (At the time of this writing, a list of more than 710,000 data-sets from 115 catalogs in 32 countries can

be found at http://logd.tw.rpi.edu/demo/international_dataset_catalog_search.)

These datasets encompass a wide range of information significant to our daily lives, in-cluding locations of toxic waste dumps, re-gional healthcare costs, and local govern-ment spending. A study conducted by the Pew Internet and American Life Project re-ported that 40 percent of adults went online in 2009 to access government data.1

For governments, the cost of releasing data through these OGD portals is less than rendering it into reports or applications. However, for data consumers, publishing data online can cause interoperability, scal-ability, and usability problems. Raw OGD datasets are typically available “as is,” in heterogeneous structures and formats, re-quiring substantial work to clean them up for machine processing and to make them comprehensible. To accelerate the use of

Open-government advocates have argued that there are many advan-

tages to governments sharing the large amount of information they col-

lect with their citizens and others. These benefits range from a more transpar-

ent government to the creation of public-private partnerships that can drive

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26 www.computer.org/intelligent Ieee InTeLLIGenT SySTeMS

L i n k e d O p e n G O v e r n m e n t d a t a

government data by citizens and de-velopers, we need an effective infra-structure with sufficient comput-ing power to process large OGD datasets and better social mechanisms

to distribute the necessary hu-man workload among stakeholder communities.

The Data.gov project’s Semantic Community (http://semantic.data.gov)

provides access to, and guidance on the use of, linked data and Seman-tic Web technologies for improving users’ ability to find and retrieve US government datasets (see Figure 1). Using linked data rather than being merely “read-only” users, public or private developers can now partici-pate in collaborative government data access, including “mashing up” dis-tributed government data from differ-ent agencies, discovering interesting patterns, customizing applications, and providing feedback to enhance the quality of published data.

Data.gov was first conceived in February 2009 by Vivek Kundra, the first US Chief Information Of-ficer, and by the US CIO Council. It was originally intended to be a cen-tral repository from which to access government data from many orga-nizations. In its first year, agencies could publish, review, and approve data for the public to find, access, and download. Agency data had to comply with a multitude of govern-ment regulations, such as the Quality of Information Act and Section 508 of the US Rehabilitation Act as well as rules about personally identifiable information and issues of national se-curity. Using rapid application pro-totyping, Data.gov launched in May 2009 with 47 datasets. Today, it offers access to more than 400,000 data-sets from 185 US government orga-nizations. The project continues to be managed by the US General Services Administration, Office of Citizen Services and Innovative Technolo-gies. Key milestones have included the integration of Geospatial One Stop (a large repository of govern-ment geospatial data and services), the deployment of communities that focus on key topical areas (such as health, energy, and business), the use of challenges and prizes to encourage the development and implementation

Figure 1. The Semantic.data.gov home page. The page supports a community working on the continued development of linked data for the Data.gov project.

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May/June 2012 www.computer.org/intelligent 27

of apps around government data, the increasing adoption and use of se-mantic technologies and linked data, and the integration of the US govern-ment’s official Web portal (www.usa.gov) search capability to find content, data, apps, and tools shared through Data.gov.

Since the beginning of the Data.gov project, the Semantic Web has been considered an important technologi-cal area for the project’s develop-ment, and a “linked-data lead” was a member of the management team. To date, more than a thousand of the datasets have been made available in Resource Description Framework (RDF) format, with a total of about six billion triples. These triples in-clude specific links via namespace ref-erence to linked data vocabularies—such as Friend of a Friend (FOAF), Dublin Core (DC), and so on—and have been enhanced with more than 15 thousand links to other linked data. To use the current parlance, all of these translated datasets are at Berners-Lee’s four-star level (they all have URIs), and most are five star (they’re linked to other data). In addi-tion, nearly a thousand more datasets have been translated and enhanced outside the government, bringing the total of triples to more than 12 bil-lion and the number of links into the millions.

Simplifying somewhat, the philoso-phy behind the Data.gov project, as expressed in the US Open Govern-ment National Action Plan (www.whitehouse.gov/blog/2011/09/20/united-states -releases- it s -open- government-national-action-plan), is that the site would both increase government transparency via the en-hanced release of government data and create public-private partner-ships that would stimulate the devel-opment of innovations based on the government’s data.

Developing Communities of Practice Around (Linked) DataData.gov was intended to be a data publishing and access platform. However, within the first year it be-came clear that the public wasn’t in-terested in general government data but in specific types. Data.gov com-munities are public-facing spaces that present data, discussions, and subject matter expertise about a single topic from many agencies in one place. The topics for these communities are chosen on the basis of agencies’ mis-sions or on issues of national impor-tance to American citizens. The first five communities launched focused on business, the oceans, restoring the Gulf, the Semantic Web, and open data. In September 2011 at the UN General Assembly, President Obama announced that the number of com-munities would double in the next year, with new ones focused on health, energy, law, education, public safety, and research and development. The first four of these have already been launched (see www.health.data. gov, www.energy.data.gov, www.law.data.gov, and www.education. data.gov).

The Data.gov team provides ser-vices to help each community de-termine how they’ll deliver value to American citizens; their outcomes and how they’ll be measured; who will lead and participate in the com-munity; and what types of function-ality, interactivity, and content will be included. Participation in com-munities is open to the public, and community members come from aca-demia, government, and industry in the US and abroad. Outcomes include applications or guidelines that help people make better decisions, new APIs or data libraries, and the cre-ation of smartphone apps, visualiza-tions, and mashups.

Quantifying these outcomes helps clarify the value of communities. For example, the health community has created 140 applications in response to 18 challenges. In the last challenge, one criteria was the presentation of a sustainable business plan to en-sure the longevity of the application and service. Fifty companies success-fully developed apps with sustainable business plans that are delivering in-formation and services to improve citizens’ health. These applications range from Patients Like Me (www. patientslikeme.com), which lets pa-tients connect to others with similar symptoms and find treatment options, to Asthmapolis (http://asthmapolis.com), which uses a GPS-enabled in-haler to find hot spots in cities that trigger asthma attacks.

These communities bring peo-ple together along topical areas cen-tered around open, linked, and structured data. This allows con-versations that can create change in a specific field. These conversations occur within the Data.gov frame-work and are extended through so-cial media (on Twitter, @usdatagov) and with partner organizations such as the World Wide Web Consortium’s eGovernment Interest Group (www.w3.org/egov/IG/charter-2011) and Government Linked Data Working Group (www.w3.org/2011/gld/wiki/Main_Page).

Open Linked Data in UseThe community mechanism has been an important way to share linked data and related applications with the public. Two ongoing efforts, one in the health sector and one in the en-ergy area, explicitly use a linked-data approach. A separate community, Semantic.data.gov, explicitly focuses on providing a place for linked-data developers and supporters to come to-gether. This community is particularly

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aimed at forward-looking efforts that will not only improve Data.gov by use of linked data, but also provide tools and technologies that help others find and use the linked data available.

Health.data.govTo date, the most extensive use of linked data has been by the health community, working with the De-partment of Health and Human Ser-vices. As part of an ongoing collab-oration to democratize OGD, the Centers for Medicare and Medicaid Services are now publishing clinical- quality linked data on Health.data.gov (http://health.data.gov/def/cqld) based on a system called Hospital Compare that has been releasing data related to the US Medicare program since 2005, expanding its coverage every year. It has been the basis of a significant amount of medical re-search since 2006.2

Like earlier Hospital Compare re-leases (www.hospitalcompare.hhs.

gov/hospital-search.aspx), the Hos-pital Compare linked data provides reports and survey results about how well hospitals treat various condi-tions, each with specific metrics de-signed to let citizens understand a hospital’s performance compared with state and national statistics. What’s different about this linked- data implementation is that the def-inition of each class of object (in-cluding but not limited to Hospital, Condition, Measure, and Metric) and the identity of every instance of each class have globally unique URIs, in-dependent from the temporal data-sets that contain periodically sampled statistical values about them. This makes it easier to accumulate more samples about how well a specific hospital is doing over time, as subse-quent publications will automatically aggregate new data around each do-main concept and its instances.

Humans and computers alike have many ways to investigate and interact

with the Hospital Compare linked data. A user can download datasets in their entirety but can also access and refer to the data they contain in a much more fine-grained way. Most datasets are published as a collec-tion of recordsets with records, each record containing the statistical val-ues about a particular instance of a domain entity (a hospital, a state, or the US) regarding various conditions, each with corresponding measures and metrics.

A typical interaction might be-gin with a user browsing these do-main entities, with each entity pro-viding a dynamically created list of its instances and links to other things those instance are related to. So if us-ers start at the definition of the Hospi-tal class, they’ll also find a list of hos-pitals. Clicking on a specific hospital brings up links to more information about that hospital and to records automatically aggregated from all of the dataset publications containing data about that hospital. In following links this way, the user is interacting with the conceptual data model that relates all the domain entities. If new hospitals come under the purview of these reports and surveys, they’ll show up on the list of instances of the Hospital class. If new conditions are tracked against new measures and metrics, these new instances will show up on their respective pages as well. Figure 2 shows an example of the linked-data page describing the concept “hospital,” which an appli-cation could use to retrieve relevant information.

An additional interface would let a user—even one with no a priori knowledge—discover more about the domain by surfing this data Web via a “faceted browsing” approach, whereby the facets come from the domain metadata. Users can employ the “follow your nose” approach by

Figure 2. Linked-data description of “hospital” from www.health.data.gov. The linked data, displayed here in human-readable form, lets an application use appropriate URIs for concepts and instances in the US Department of Health and Human Services’ published data.

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clicking on links that lead from one area of interest to another. In ad-dition to these data element access services and faceted-browsing capa-bilities, the site offers powerful key-word and metadata search features and various structured-query Web services. All the data is available in multiple popular formats to fa-cilitate application-specific process-ing, whether by specifying formats in HTTP request headers or by sim-ply appending the format extension. For example, a user can get a Java-Script Object Notation (JSON) rep-resentation by appending “.json” to a URI; comma-separated values (.csv), atom feeds (.atom), and many other formats are similarly available. Thus, users interested in hospital data can either browse the linked data via the portal or query the linked data to use Health.data.gov as a platform for de-veloping their own applications.

energy.Data.govThe energy community (www.energy.data.gov) provides a second example of the use of open linked data. This community’s focus is on driving inno-vation and access to data across the energy field, from government to util-ities to homeowners. A requirement from community leaders and partici-pants was to integrate search across multiple energy data sources, beyond Data.gov. One of the leaders in this endeavor is the National Renewable Energy Laboratory’s OpenEI system (http://openei.org). Because OpenEI and Data.gov both have a Sparql end point, it was possible to create an efficient, reconfigurable faceted browser across both sets of assets. We’ve also used this Sparql endpoint to provide search metadata utiliz-ing a common model for open gov-ernment dataset catalogs around the world (http://logd.tw.rpi.edu/demo/international_dataset_catalog_search).

The lesson here was simple—when a standards-based approach is used, future integration and extended ca-pability is extremely cost effective. What might have taken weeks or months of work was accomplished in a fraction of the time and allows new knowledge discovery to come online that much sooner.

Extending Partnerships beyond the GovernmentOne of the goals set by the adminis-tration was that Data.gov should en-courage innovative new public-private partnerships to link government data sharers with user communities. A particular target was encouraging universities and other educational groups to work with the government to improve e-government technolo-gies, outreach, and services. One par-ticularly successful partnership has been forged with the Tetherless World Constellation at Rensselaer Polytech-nic Institute (RPI), focused on Linked OGD (LOGD).

In May 2010, the LOGD team at RPI was recognized as a private partner working with the Data.gov team, and this ongoing relation-ship has been represented in the Semantic Web Community (http:// semantic.data.gov), which focuses on the shared development of linked-data techniques between the gov-ernment and RPI, as well as other linked-data providers for the govern-ment. The RPI team has been devel-oping tools and techniques for inter-acting with government data from Data.gov and other government data-sharing sites around the world. The team has made specific contributions in the following areas:

•Production. The RPI team has de-veloped an approach to converting government datasets to RDF and enhancing them with links to other

datasets and/or other linked-data resources such as DBpedia (http://dbpedia.org), the New York Times linked open data (http://data. nytimes.com), and government data-sets from the UK, the World Bank, and other international organiza-tions. From the US and abroad, the RPI team has converted more than 10 billion triples of data. About six billion of these triples are now available directly from Data.gov as downloadable files. The links from these triples to other datasets is being enhanced by the develop-ment of a URI scheme for govern-ment data.

•Consumption. The adoption of LOGD depends on its perceived value as evidenced by compelling LOGD-based applications. More than 60 online demos have been built and hosted on the RPI portal using a wide range of Web technol-ogies, including data-visualization APIs and Web service composi-tion. Several of these demos, and links to tutorials detailing how to develop them, are available directly through Data.gov or linked to the Semantic.data.gov community.

•Tools. The growth of govern-ment LOGD systems demands ac-tive community participation. To enhance this community’s devel-opment, RPI has documented its methods for converting and us-ing government data, and has provided tutorials on developing LOGD mashups. The Data.gov site provides links to these re-sources to support knowledge sharing and promote best practices in the LOGD community.

•Search. Data.gov hosts several tools for searching government data through various interfaces. These are generally keyword-based searches using commercial or contractor-provided search engines.

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RPI has been exploring the use of semantic search techniques to en-hance open government search. A joint effort by the Data.gov devel-opment team and the RPI research group is exploring both the sepa-rate use of faceted search based on new metadata standards and ways to use new semantic technologies, especially those of Schema.org and various search techniques en-hanced with RDF with attributes (RDFa). To enhance users’ abilities to more easily find and use govern-ment data.

The details of the approach under-lying this work and of the capabili-ties described are beyond the scope of this paper. Li Ding and his colleagues have covered them in greater detail.3

Partnerships with the International CommunityAs far as future initiatives go, the US and Indian governments have cre-ated a formal agreement to build the Open Government Platform (OGPL; www.data.gov/opengovplatform), an entirely open source and completely self-sustaining software package. The teams creating this are the Data.gov team and the government of India’s National Informatics Center. The OGPL project intends to expand open government to other nations by lowering the barrier for creating their own open-data, open source

platform. The software package has two major components, an exter-nally facing, publicly accessible web-site and an internally facing metadata manager. The initial code release is available from https://github.com/ opengovplatform/opengovplatform-dms, and the first additional module will be for communities. The open source community is expected to contribute to the code, create new modules, and help evolve the platform.

The OPGL is currently focusing on the dataset management system that government data users need, and on the front end enabling consumption of that data. For example, OGPL contains significant workflow com-ponents so that shared data can un-dergo appropriate review (by agency and central government, for ex-ample), have its metadata checked, and be published to an external site. Other projects are exploring common hosting as well, especially in the UK and the EU, including the Compre-hensive Knowledge Archive Network (CKAN) project run by the Open Knowledge Foundation (http://ckan.org). Recent discussions between the OGPL and CKAN teams are explor-ing how these systems could become more interoperable in the future.

The RPI team has been meeting with both the US and Indian part-ners, and is exploring how to enhance the OGPL platform to make five-star linked data a natural offshoot

of the tools’ use. One particular fo-cus has been automatically publish-ing the datasets’ metadata in RDF, using common namespaces (FOAF, DC, Data Catalog Vocabulary, and so on) wherever possible. A second has been making the use of common terms (such as agency names, gov-ernment sectors, and parts of coun-tries) automatically generate com-mon URIs so that the published RDF is easily linked to other linked data both within and beyond the government.

Next StepsSignificant opportunities remain for Data.gov’s architecture and linked data technologies to help drive the fu-ture goals of the US data-sharing pro-gram. Users have a variety of mech-anisms for providing feedback to the Data.gov team—over Twitter to @usdatagov, via comments or ratings on a dataset, in community forum discussions, with comments at the site, and at events. (See the “Call for Participation” sidebar for opportuni-ties to contribute.)

As an important part of meeting the needs of the Obama administration and the American public, Data.gov has begun the process of simplify-ing the architecture. Over the past two years, as the program’s scale has grown both in capabilities and data-sets, the architecture has outgrown its original intent of simply provid-ing a mechanism to access data. The emergent architecture will incorporate OGPL, better integrate a recent infu-sion of geospatial data, and provide more on-site functionality for data exploration, access, and visualization. These tools will also make the publica-tion and use of linked data a byprod-uct of the normal use of this site, mak-ing data linking significantly easier.

Additionally, the Data.gov team has recently launched Vocab.data.gov

In addition to the efforts described in the main article, the Semantic.data.gov portal (www.data.gov/semantic) is open to the public, and we encour-age participation not just by US groups but by anyone interested in the

Semantic Web for government data sharing. We’re currently working on devel-oping standard URI schemes for the US government’s linked data. We’ve pro-posed a design for these URIs, intended to be maximally compatible with the URI scheme used at http://data.gov.uk. We expect eventually to have resolv-able and permanent URIs for the many billions of triples that will be accessible through Data.gov. The team welcomes feedback on the scheme proposed, on how it could fit into international schemes, and on how it might affect linking with US state, municipal, and tribal sites. To see the current proposal and to join the discussion, visit www.data.gov/communities/node/116/forums.

Call for participation

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(http://vocab.data.gov), a site that can host government-related semantic vo-cabularies. The current site, which is based on the Neologism vocabu-lary platform developed at the Digital Enterprise Research Institute (http:// neologism.deri.ie),4 contains several vocabularies that have been used for the health project, ontologies devel-oped by government agencies, and some suggested vocabulary for de-scribing government entities. Cur-rently, as a joint Data.gov-RPI effort, we’re working to include a tool for hosting sets of instance URIs on top-ics ranging from US states and gov-ernment agencies to agency-specific topics such as crops and toxic chemi-cals. We also plan to host government- related Simple Knowledge Organiza-tion System vocabularies from vari-ous government agency libraries, as well as other government-related vo-cabularies developed by NGOs and private entities.

The roadmap for any open-data project can be difficult, and

Data.gov is no exception. From a rapid prototype deployment, through funding uncertainty and person-nel change, to an onslaught of new requirements, the site continues to evolve. The principles that apply to every large venture were important: get executive sponsorship early and often, build the project into the in-frastructure of key programs, and manage change.5 However, this case offered additional lessons. The wholehearted embrace of evolving technologies and capabilities (includ-ing linked data, Semantic Web stan-dards, and open source development) has kept Data.gov relevant and use-ful. Additionally, the move from a collection of hundreds of thousands of datasets to a community-oriented springboard for action has been criti-cal. This change allowed Data.gov to

move from an IT platform to a criti-cal part of the national conversation around energy, health, business, law, oceans, and education.

Linked data is becoming an in-creasingly important aspect of gov-ernment data sharing around the world. The Data.gov site is a leader in government information shar-ing and, with new efforts in open source architecture and dataset in-tegration and search, will continue to provide a vital service to the citi-zens of the US and to others around the world interested in US govern-ment data. The US is a large and di-verse country, with a governmental structure that requires the integration of both top-down, mandated data sharing and bottom-up, community-developed technologies and data. semantic.data.gov, health.data.gov, and Energy.data.gov are examples of how these approaches have success-fully come together. The Semantic Web efforts at Data.gov have been moving from evangelism to adoption, and future plans will increase the role that semantics play in government data-sharing efforts.

AcknowledgmentsRensselaer Polytechnic Institute acknowl-edges sponsorship from Micro soft Research Laboratories, which provides support to the

Tetherless World Constellation, and from the US National Science Foundation, which awarded an Early-Concept Grant for Ex-ploratory Research for exploring next-generation Semantic Web Technologies.

References1. A. Smith, Government Online, Pew

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Reports/2010/ Government-Online.aspx.

2. R. Werner and E. Bradlow, “Relation-

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vol. 296, no. 22, 2005, pp. 2694–2702.

3. L. Ding et al., “TWC LOGD: A Portal

for Linked Open Government Data

Ecosystems,” J. Web Semantics, vol. 9,

no. 3, 2011, pp. 325–333.

4. C. Basca et al., “Neologism: Easy

Vocabulary Publishing,” Proc. 4th

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Web, CEUR Workshop Proc., 2008;

http://aran.library.nuigalway.ie/xmlui/

bitstream/handle/10379/555/10.pdf.

5. B.S. Noveck, Wiki Government: How

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Better, Democracy Stronger, and

Citizens More Powerful, Brookings

Institution Press, 2009.

t h e a u t h O r sJames Hendler is the Tetherless World Professor of Computer and Cognitive Science at Rensselaer Polytechnic Institute. Hendler provides guidance to the Data.gov project and other US open-data-sharing efforts. Contact him at [email protected].

Jeanne Holm is the evangelist for Data.Gov, overseeing the work on communities, out-reach, and collaboration. She also serves as the chief knowledge architect at NASA’s Jet Propulsion Laboratory and is an instructor in knowledge management, social network analysis, and collaborative systems at the University of California, Los Angeles. Contact her at [email protected].

Chris Musialek is the chief software architect for Data.gov, where he leads the architec-tural strategy and provides overall technical direction to the program. Additionally, he serves as the program manager for geo.data.gov and geoplatform.gov. Contact him at [email protected].

George Thomas is an enterprise architect in the office of the Chief Information Officer at the US Department of Health and Human Services. He leads the US Data.gov linked-data team and cochairs the World Wide Web Consortium’s Government Linked Data Working Group. Contact him [email protected].

Selected CS articles and columns are also available for free at

http://ComputingNow.computer.org.

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Documents

US Government Linked Open Data: Semantic.data.gov