@inproceedings{c052da1badf341c2a1bee639ca47d7bc,
title = "ADACOP: A Big Data Platform for Open Government Data",
abstract = "In modern states, transparency in the public sector has become a critical issue in developing a democratic process. Emerging technologies such as Big Data and Open Government Data have become essential for assuring and improving transparency at all public sector dimensions. Particularly, Big Data has a significant impact potential in fields where data with considerable volume, velocity, and variety properties are present, such as monitoring public procurement. In this work, we present an Open Government Big Data tool for monitoring and exploiting the potential of data from Open Government Data portals. The solution automatically generates descriptive statistics about Open Government Data and allows the verification of Open Government Data quality by contrasting different versions of the data across time. To validate the solution, we develop a case focused on monitoring public procurement data, due to its importance in assuring government transparency. The platform provides a set of analytical tools to resolve specific requirements from public procurement fiscal evaluators.",
keywords = "big data, data analytics, open government data, public procurement",
author = "Andr{\'e}s Moreno and Jos{\'e} Molano-Pulido and Gomez-Morantes, {Juan E.} and Gonzalez, {Rafael A.}",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 15th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2022 ; Conference date: 04-10-2022 Through 07-10-2022",
year = "2022",
month = oct,
day = "4",
doi = "10.1145/3560107.3560310",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "369--375",
editor = "Luis Amaral and Delfina Soares and Lei Zheng",
booktitle = "Proceedings of the 15th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2022",
}