• English
  • Deutsch
  • Log In
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Ronda: Real-Time Data Provision, Processing and Publication for Open Data
 
  • Details
  • Full
Options
2021
  • Konferenzbeitrag

Titel

Ronda: Real-Time Data Provision, Processing and Publication for Open Data

Abstract
The provision and dissemination of Open Data is a flourishing concept, which is highly recognized and established in the government and public administrations domains. Typically, the actual data is served as static file downloads, such as CSV or PDF, and the established software solutions for Open Data are mostly designed to manage this kind of data. However, the rising popularity of the Internet of things and smart devices in the public and private domain leads to an increase of available real-time data, like public transportation schedules, weather forecasts, or power grid data. Such timely and extensive data cannot be used to its full potential when published in a static, file-based fashion. Therefore, we designed and developed Ronda - an open source platform for gathering, processing and publishing real-time Open Data based on industry-proven and established big data and data processing tools. Our solution easily enables Open Data publishers to provide real-time interfaces for heterogeneous data sources, fostering more sophisticated and advanced Open Data use cases. We have evaluated our work through a practical application in a production environment.
Author(s)
Kirstein, Fabian
Bacher, Dario
Bohlen, Vincent
Schimmler, Sonja
Hauptwerk
Electronic Government. 20th IFIP WG 8.5 International Conference, EGOV 2021. Proceedings
Project(s)
QuarZ
Funder
Bundesministerium für Wirtschaft und Energie BMWi (Deutschland)
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
Konferenz
International Conference on Electronic Government (EGOV) 2021
DOI
10.1007/978-3-030-84789-0_12
File(s)
N-640719.pdf (350.12 KB)
Language
Englisch
google-scholar
FOKUS
Tags
  • Open Data

  • Big Data

  • real-time

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022