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|
Identifier |
000441078 |
Title |
Interoperability over meteorological and spatial big data warehouse |
Alternative Title |
Διαλειτουργικότητα σε αποθήκες μεγάλου όγκου μετεωρολογικών και χωρικών δεδομένων |
Author
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Μπαριτάκης, Παύλος Δ.
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Thesis advisor
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Πλεξουσάκης, Δημήτριος
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Reviewer
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Τζίτζικας, Ιωάννης
Μαγκούτης, Κωνσταντίνος
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Abstract |
Nowadays with climate change being a major issue in Scientific Community and to citizens
too, the scientific community struggles to find causes, results and make predictions about
future impacts to our lives.
Having Internet Of Things, like Meteorological Sensors, like an arrow in the quiver, helps
the Scientific Community collect important meteorological and spatial data in a manner
of using this kind of data to build statistical and mathematical models to guide them to
more accurate results, plus faster than the existing models.
The frequent collection of the meteorological and spatial data from het- erogenous
sources of information, drives to huge portions of data that have to be stored and
managed efficiently in a sense of being useful to users by converting raw data format into
knowledge.
The solution to the efficient storage and management of these big portions of data was
given firstly by building a data warehouse with a collection of different databases,
regarding the sources of information and secondly by using a Knowledge Base Layer over
the data warehouse. With this approach, we create interoperability over the data
warehouse.
The approach of the thesis is a Web-Based Management Information Sys- tem that uses
NoSQL databases to build the Storage Layer so as the Knowledge Base Representation
Layer. The Apache Cassandra DB is used as the Storage Layer and the Knowledge Base
Layer implemented with the usage of Neo4j Graph DB. The combination of these two
NoSQL Databases leads to a dynamic M.I.S. Web-Based Application that can handle the
load of data from sensors. The Web App can be used easily from novice to more advanced
users to gather and manage the data, create statistics, views and execute dynamic queries
to the database warehouse to have results on demand.
|
Language |
English |
Subject |
Μεγάλος όγκος δεδομένων |
Issue date |
2021-07-30 |
Collection
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School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
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Type of Work--Post-graduate theses
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Permanent Link |
https://elocus.lib.uoc.gr//dlib/b/a/e/metadata-dlib-1625732169-317679-25262.tkl
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Views |
623 |