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Authors: Robert Scholz ; Nikolay Tcholtchev ; Philipp Lämmel and Ina Schieferdecker

Affiliation: Fraunhofer Institute for Open Communication Systems (FOKUS), Germany

Keyword(s): Smart Cities, Open Data, Distributed Processing, Hadoop, CKAN.

Abstract: Smart Cities will mainly emerge around the opening of large amounts of data, which are currently kept closed by various stakeholders within an urban ecosystem. This data requires to be cataloged and made available to the community, such that applications and services can be developed for citizens, companies and for optimizing processes within a city itself. In that scope, the current work seeks to develop concepts and prototypes, in order to enable and demonstrate, how data cataloging and data storage can be merged towards the provisioning of large amounts of data in urban environments. The developed concepts, prototype, case study and belonging evaluations are based on the integration of common technologies from the domains of Open Data and large scale data processing in data centers, namely CKAN and Hadoop.

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Paper citation in several formats:
Scholz, R., Tcholtchev, N., Lämmel, P., Schieferdecker and I. (2017). A CKAN Plugin for Data Harvesting to the Hadoop Distributed File System. In Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-243-1; ISSN 2184-5042, SciTePress, pages 47-56. DOI: 10.5220/0006230200470056

@conference{closer17,
author={Robert Scholz and Nikolay Tcholtchev and Philipp Lämmel and Ina Schieferdecker},
title={A CKAN Plugin for Data Harvesting to the Hadoop Distributed File System},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER},
year={2017},
pages={47-56},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006230200470056},
isbn={978-989-758-243-1},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER
TI - A CKAN Plugin for Data Harvesting to the Hadoop Distributed File System
SN - 978-989-758-243-1
IS - 2184-5042
AU - Scholz, R.
AU - Tcholtchev, N.
AU - Lämmel, P.
AU - Schieferdecker, I.
PY - 2017
SP - 47
EP - 56
DO - 10.5220/0006230200470056
PB - SciTePress

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