When building reliable data-driven applications for local governments to interact with public servants or citizens, data publishers and consumers have to be sure that the applied data structure and schema definition are accurate and lead to reusable data. To understand the characteristics of reusable local government data, we motivate how the process of developing a semantically enriched exchange standard contributes to resolving this issue. This standard is used, for example, to describe contact information for public services which supports a representative pilot for opening up a variety of local government data. After implementing the pilot, we experienced that supporting the process of converging on semantics has a catalyzing effect on the reusability of government data.
If local governments would repeatedly develop an (ad-hoc) model for this information, it would be really hard for them to maintain the services that offer this information, as they require constant revising of the model of available data while they are not able to cope with newer technologies and applications without heavily investing in new support infrastructure. The opposite is also true, it is extremely easy to ignore this consideration and just publish data in whatever format pops-up at the time. Therefore, we ensure that after the standardization effort and as soon as the data has been described using one or more vocabularies that: the data still remains reusable, even when information technology evolves; and in one way or another, developers and users do not have to cope with the same issues as with custom data models.
Open standards are essential for systems and data to be interoperable [
Historically, governments tend to rely on the free market to disseminate information,
e.g., the federal US Government, on the one hand, tries to reduce the role of the
government in presenting its information to citizens [
Methodologies for linking government data as such are not new: many guidelines
considering applications, methodology, coverage and quality exist [
Some initiatives succeed in this way of standardization, such as the EDGAR
filings with ‘eXtensible Business Reporting Language’ (XBRL)7: the ‘Securities and
Exchange Commission’ (SEC)8 mandate requires that corporations and mutual funds
under the purview of the Commission, file key performance reports in the Commission’s
EDGAR data repository9 in the XBRL format [
In an intergovernmental setting (with different structures as well as diverging public service models) it is complex to optimize the delivery of government services so that citizens and businesses only need to ask the government once for any of them. Even within the same organization, public services are documented following different flavors of national, regional or local public service models. Additionally, public service descriptions delivered through e-Government portals are usually unstructured and not machine-readable. This fragmented view of the public service concept and the absence of machine-readable public service descriptions impacts the quality and the efficiency of public service provision, increases administrative burdens and makes public service provision more costly. This is a major obstacle for citizens and businesses.
Smart Cities [
In a typical scenario, local governments publish the open data, belonging to the deliverable for a project, as part of an application or report. After delivery, shortage of funding or change of focus to new projects leads to data which is not maintained. We assure that the published data can remain correct and up to date. Therefore, we modeled government data, described as Linked Data, with vocabularies in respect to their usage and wide popularity within the Semantic Web community as well as to their applicability for the proposed use case. The main modeling domains of interest as they were indicated by the local governments during the development of OSLO are: people, locations, organizations, products and services. To create new data sources, we aggregated information from different regional and local e-government information systems and combined them with existing services to create machine-readable public service descriptions. These descriptions are reusable, following the Linked Open Government 10 http://fios.ontologycentral.com/ 11 http://www.w3.org/TR/vocab-data-cube/ 12 http://www.w3.org/2011/gld 13 https://github.com/v-ict-or/oslo_xml_
schemas/tree/shared_catalogue_extension
14 https://github.com/v-ict-or/oslo_xml_
schemas/tree/master
Data paradigm [
The Dublin Core vocabulary15 was used for the basic metadata properties, the Friend of A Friend (FOAF)16 ontology to bind the information on titles and descriptions and to enhance the content of the generated dataset. We used the OSLO vocabulary17 and the W3C Organization vocabularies: Organization Ontology18, Registered Organization Ontology19. For contact information we relied on the VCARD Ontology20. We have extended the OSLO vocabulary with three new entities: Channel, Activity and Product. As a result we are able to model the latter three and People, Organizations, Services and Locations. 4
A number of administrations (local municipalities, cities and one regional administration) participated, as depicted in Table 1, in the development of a prototype for the “Shared Catalogue of Public Services”, an ecosystem for sharing contact information from local governments: (i) towards citizens and (ii) between governments. The participating administrations all experienced a considerable “overhead” and “redundancy” in finding relevant contact data. The goal of this catalogue prototype is to disclose products and services more effectively between governments and towards citizens. Figure 1 shows how they interact using a common interface providing access to the data described semantically according to OSLO, enabling them to answer questions such as: (i)“As a Citizen/Public Servant, how to obtain Service X in Municipality Y and who to contact?”; (ii) “Who to contact for Service X in municipalities in a certain region?”.
Administration Type ISRBKGDKVHnieooeeanDgnvlsenroetAlttes-teklreNermBiklejlbikean*uke-r*nlHreagsaeteesinsrt CCCCRMMMMMiiiieuuuuuttttgyyyynnnnnioiiiiicccccniiiiiappppplaaaaallllliiiiitttttyyyyy
Conceptually Mapped Formally Mapped Automatically Linked
XXX XXX* X* X X X X X
X X X
X* X* X
The pilot was initiated by Corve21, the Flemish e-Government coordination cell and the project consortium was coordinated by V-ICT-OR22, the Flemish ICT organization. We analyzed the contact data from several Flemish municipalities and cities and mapped according to the defined vocabularies. We dealt with multiple heterogeneous data that needed to be mapped. Each government had its own data structure. After mapping conceptually, i.e. matching concepts in the original datastructure with the OSLO vocabulary, we defined a formal mapping to RDF in a configuration document. This allowed us to align them for use in a common interface with one ‘move’. A couple of governments, e.g., Beveren and Sint-Niklaas, could then be automatically linked without having to do the conceptual and formal mapping again, as they used a similar back-end data structure. It is noteworthy that for the biggest participating city, Gent, the mapping 15 http://dublincore.org/documents/dcmi-terms 16 http://xmlns.com/foaf/spec/ 17 http://purl.org/oslo/ 18 http://www.w3.org/TR/vocab-org/ is more time consuming. This is expected as the delivery of product and services is more sophisticated and the data is more complex than for smaller governments.
We relied on RML [
In our opinion, supporting data reuse implies preparing facilities in advance with the right vocabularies. This can be guaranteed on the ontology (semantic convergence) level and the data level. Support groups, mailing lists and open maintenance helped ensuring reuse of the ontology. In the case of data, and more specifically Linked Open Data, it is important to have a solid feedback loop so that the original data publishers can be notified at any point if there are any inconsistencies with the data they are responsible for. To avoid inconsistencies, we maximized automation between reliable authentic data sources and the published data.
In this pilot, we have experienced that the Linked Data principles are as suitable for data management on the Web as for local government information systems. We developed a standard as a convergence between various stakeholders in local government data. We showed its applicability using a prototype for a distributed shared catalogue of public services and products from municipalities. We are going to continue improving work in the field of Linked Open Government Data starting by assessing the user perceived usefulness and usability of this approach. On the one hand, this application is a typical use case for Linked Data technologies, given the complex and the dynamic nature of the organizations and data involved. On the other hand, it also takes place in a setting that is slow to evolve, partly for the same reasons. However, governments do have the potential to force or imply a certain structure using their own resources. Depending on the society model, short- and long term objectives, different technological choices need to be made.
We think that the Linked Open Data community should invest more in making its technology essentials clear and in motivating governments to use it as main technology for local government data reuse. It is an interesting research question to measure if and how well agreeing on semantics proves to be useful in tackling issues on converging semantics and reusable government data described in this paper.