Communications in Computer and Information Science, pages 242-253

Data Provenance in Citizen Science Databases

Publication typeBook Chapter
Publication date2018-08-30
Q4
SJR0.203
CiteScore1.1
Impact factor
ISSN18650929, 18650937
Abstract
Today, more and more scientific groups are developing citizen science applications. Citizen science is a relatively new domain of science that has already proved to be as beneficial as classical science. One of the major challenges citizen science face is the data quality assurance. It uses several techniques to verify the data quality based on expert evaluation, voting systems, etc. Data provenance is used in many scientific systems and provides reliable mechanism for tracking data history. It includes history of origin, changes, and all interactions between different parts of data. Data provenance by itself has many types such as “Why provenance”, “When provenance”, and “What provenance”. The purpose of this work is to build a prototype of a database with built-in data provenance. Several databases systems and models such as Relational databases, NoSQL databases are taken into consideration. Experiments are been conducted to test limitations of proposed prototype.
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Data Technologies and Applications
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GOST Copy
Tiufiakov N. et al. Data Provenance in Citizen Science Databases // Communications in Computer and Information Science. 2018. pp. 242-253.
GOST all authors (up to 50) Copy
Tiufiakov N., Dahanayake A., Zudilova T. Data Provenance in Citizen Science Databases // Communications in Computer and Information Science. 2018. pp. 242-253.
RIS |
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RIS Copy
TY - GENERIC
DO - 10.1007/978-3-030-00063-9_23
UR - https://doi.org/10.1007/978-3-030-00063-9_23
TI - Data Provenance in Citizen Science Databases
T2 - Communications in Computer and Information Science
AU - Tiufiakov, Nikita
AU - Dahanayake, Ajantha
AU - Zudilova, Tatiana
PY - 2018
DA - 2018/08/30
PB - Springer Nature
SP - 242-253
SN - 1865-0929
SN - 1865-0937
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@incollection{2018_Tiufiakov,
author = {Nikita Tiufiakov and Ajantha Dahanayake and Tatiana Zudilova},
title = {Data Provenance in Citizen Science Databases},
publisher = {Springer Nature},
year = {2018},
pages = {242--253},
month = {aug}
}
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