A major challenge when working with open government data is managing, connecting, and understanding the links between references to entities found across multiple datasets when these datasets use... Show More

A major challenge when working with open government data is managing, connecting, and understanding the links between references to entities found across multiple datasets when these datasets use different vocabularies to refer to identical entities (i.e.: one dataset may refer to Microsoft as “Microsoft”, another may refer to the company by its SEC filing number as “0000789019”, and a third may use its stock ticker “MSFT”.) In this paper the authors propose a naming scheme based on Web URLs that enables unambiguous naming and linking of datasets and, more importantly, data elements, across the Web. They further describe their ongoing work to demonstrate the implementation and authoritative management of such schemes through a class of web service they refer to as the “instance hub”. When working with linked government data, provided either directly from governments via open government programs or through other sources, the issue of resolving inconsistencies in naming schemes is particularly important, as various agencies have disparate conventions for referring to the same concepts and entities. Using linked data technologies the authors have created instance hubs to assist in the management and linking of entity references for collections of categorically and hierarchically related entities. Instance hubs are of particular interest to governments engaged in the publication of linked open government data, as they can help data consumers make better sense of published data and can provide a starting point for development of linked data applications. In this paper the authors present their findings from the ongoing development of a prototype instance hub at the Tetherless World Constellation at Rensselaer Polytechnic Institute (TWC RPI). The TWC RPI Instance Hub enables experimentation and verification of proposed URI design schemes for open government data, especially those developed at TWC in collaboration with the United States Data.gov program. They discuss core principles of the TWC RPI Instance Hub design and implementation, and summarize how they have used their instance hub to demonstrate the possibilities for authoritative entity references across a number of heterogeneous categories commonly found in open government data, including countries, federal agencies, states, counties, crops, and toxic chemicals.

E-government initiatives provide enormous volume of information via online content. As public information changes over time due to changes in laws and regulations, maintaining the currency and... Show More

E-government initiatives provide enormous volume of information via online content. As public information changes over time due to changes in laws and regulations, maintaining the currency and consistency of the web content becomes acutely important. Government agencies have to regularly evaluate the web content (WC) to ensure high quality of information available to the citizens, businesses and public administrators. Currently there exists no standardized approach for monitoring and maintaining WC. By analyzing the guidelines of three government organizations, the authors develop WC ontology for the systematic and formal representation of the concepts and functions in evaluating web content. An ontology-based evaluation tool is proposed that can be used to improve the quality of web content and efficiency of the evaluation process. The ontological approach holds promising features and benefits including information sharing, reducing time and paper work during evaluation, assuring more accurate results, and communicating evaluation results to knowledge engineers, public administrators, evaluators and decision makers associated with e-government initiatives.

A Citizen Relationship Management (OpenCiRM) system was built on a semantic web platform using model-driven development principles, to provide a government call center with operational agility and... Show More

A Citizen Relationship Management (OpenCiRM) system was built on a semantic web platform using model-driven development principles, to provide a government call center with operational agility and improved technical integration options. Business domain experts from municipal agencies administered the system by directly manipulating its ontology model. This paper highlights the new ontology engineering tasks and user roles that may emerge in organizations implementing the OpenCiRM system.

Over the past decade, authorities invested highly in public service provision over the Internet via portals. Back office systems of authorities collect and store data entered by citizens and... Show More

Over the past decade, authorities invested highly in public service provision over the Internet via portals. Back office systems of authorities collect and store data entered by citizens and enterprises to support decision-making by civilians. The data represents both the state of citizens and enterprises, public service transactions, and the physical infrastructure including ownership relations. Whilst civilians use the data for decisions, data quality influences decision quality. As data steward, civilians have improved data quality by removing duplicate data and created specific data stores for reference data like addresses, enterprises, and citizens. Citizens and enterprises can use reference data to complete electronic public service request forms. To further improve data quality, civilians perform physical inspections and/or assess external data sources to validate for instance data consistency. Besides data steward, civilians are also data custodian: they provide processing and storage facilities. In this contribution, the author will argue that an innovative architecture separating data steward and data custodian roles, currently held by civilians, decreases the Total Cost of Ownership of authorities' IT and contributes to economic growth. In the proposed approach, persons and organizations take the data stewardship role, facilitated by a provider of a data custodian role either in the public or private domain. Civilians can access the data for decision-making. Civilians still act as data steward with respect to additional data resources than provided by citizens and enterprises in decision-making. The approach is illustrated by a case and supported by the governance policy of for instance Dutch Customs Authority.

Contemporary societies face complex problems that challenge the sustainability of their social and economic systems. Such problems may require joint efforts from the public and private sectors as... Show More

Contemporary societies face complex problems that challenge the sustainability of their social and economic systems. Such problems may require joint efforts from the public and private sectors as well as from the society at large in order to find innovative solutions. In addition, the open government movement constitutes a revitalized wave of access to data to promote innovation through transparency, participation and collaboration. This paper argues that currently there is an opportunity to combine emergent information technologies, new analytical methods, and open data in order to develop innovative solutions to some of the pressing problems in modern societies. Therefore, the objective is to propose a conceptual model to better understand policy innovations based on three pillars: data, information technologies, and analytical methods and techniques. The potential benefits generated from the creation of organizations with advanced analytical capabilities within governments, universities, and non-governmental organizations are numerous and the expected positive impacts on society are significant. However, this paper also discusses some important political, organizational, and technical challenges.

The increasing number of certification schemes diminishes the utility of certifications as private regulation and creates several policy challenges. The undergoing efforts to help consumers verify... Show More

The increasing number of certification schemes diminishes the utility of certifications as private regulation and creates several policy challenges. The undergoing efforts to help consumers verify the accuracy of information created by private regulation mechanisms such as certification are currently confronted with the complexities of certification and labeling systems and the difficulties in linking data points across various certification schemes. This paper presents the development of certification and inspection ontology to support smart disclosure of product information. This study proposes that the resulting ontology enables information integration and standardization thus supporting knowledge discovery and sharing by synthesizing information across disparate data sources that is valuable for informing data-driven policy formulation. The ontology also supports standardization of an agreed set of terms and semantics for currently fragmented certification and inspection schemes to support comparability across different certification schemes. The accuracy and consistency of the proposed ontology are verified by using current reasoning tools to run queries based on a set of predefined competency questions.