Finding information in an era of abundance: Towards a collaborative tagging environment in government

  • Authors:

  • Soon Ae Chun;Janice Warner

  • Affiliations:

  • City University of New York, College of Staten Island, Staten Island, NJ, USA. E-mail: Soon.Chun@csi.cuny.edu;Georgian Court University, Lakewood, NJ, USA. E-mail: warnerj@georgian.edu

  • Venue:
  • Information Polity - Government 2.0: Making Connections between citizens, data and government
  • Year:
  • 2010

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Abstract

Collaboration and information sharing among government organizations is becoming increasingly important for promoting efficiency and productivity as well as for enhancing citizen services. With Internet connectivity widely available and with the ease-of-use of social media tools, citizens actively participate in producing content. However, the abundance of content causes another problem for governments - the difficulty of determining what truly useful and relevant information is to be shared for mission critical tasks and to produce better citizen services. Information resources, such as data, documents, multimedia objects and services stored in different agencies and produced by citizens need to be easily discovered and shared. We propose a data model of rich social tags and a Citizen-Government collaborative tagging environment} where governments and citizens can collaboratively annotate the resources, thus facilitating collaboration responsiveness through accessibility to information. The collaborative annotations capture not only the semantics but also the pragmatic and social aspects related to the resources, such as who, when, where, how and for what related tasks the resources are shared. The benefits of the a rich tag data model emphasizing the relationships of a tag to semantic, social, pragmatic and contextual reference frames include the ability to filter, discover and search new and dynamic as well as hidden resources, to navigate between resources in a search by traversing semantic relationships, and to recommend the most relevant government information even when distributed over different agencies. A distributed architecture of a government collaborative tagging system is proposed and tag-based search and recommendations are illustrated.