TY  - JOUR
T1  - Fast Access to Large Timeseries Datasets in SCADA Systems
AU - Tyukov, Anton AU - Khrzhanovskaya, Olga AU - Sokolov, Alexander AU - Shcherbakov, Maxim AU - Kamaev, Valerij 
JO  - Research Journal of Applied Sciences
VL  - 10
IS  - 1
SP  - 12
EP  - 16
PY  - 2015
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2015.12.16
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2015.12.16
KW  - SCADA
KW  -machine learning
KW  -data quality
KW  -timeseries data
KW  -building energy management system
KW  -BEMS
KW  -big data
AB  - This study presents a new method of working with timeseries data gathered from sensors. Researchers use natural time cycles of timeseries to create data packages of different type. Each data package is a small piece of timeseries data of fixed size and granularity, supported with statistical information and data quality certificate. Data quality certificate provides information about following aspects of data: syntactic, semantic, pragmatic and punctuation. This study contains a concept of data infrastructure and experimental results which proves significant increase of data extraction time and perform data quality certification of each data package. All experiments were performed on large time series data collected from electricity, water and gas meters in public buildings.
ER  -