Implementing big data lake for heterogeneous data sources
| Autor: | Stavros Tekes, Marta Cortes, Ekaterina Gilman, Jukka Riekki, Katerina Valta, Andrew Byrne, Panos Kostakos, Hassan Mehmood |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Big Data
smart City Data collection Computer science business.industry Big data data analysis 02 engineering and technology big Data Data science Visualization Set (abstract data type) data lake Information and Communications Technology Urban planning 020204 information systems Smart city 11. Sustainability Smart City 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business |
| Zdroj: | 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) ICDE Workshops |
| Popis: | Modern connected cities are more and more leveraging advances in ICT to improve their services and the quality of life of their inhabitants. The data generated from different sources, such as environmental sensors, social networking platforms, traffic counters, are harnessed to achieve these end goals. However, collecting, integrating, and analyzing all the heterogeneous data sources available from the cities is a challenge. This article suggests a data lake approach built on Big Data technologies, to gather all the data together for further analysis. The platform, described here, enables data collection, storage, integration, and further analysis and visualization of the results. This solution is the first attempt to integrate a diverse set of data sources from four pilot cities as part of the CUTLER project (Coastal urban development through the lenses of resiliency). The design and implementation details, as well as usage scenarios are presented in this paper. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|