@inproceedings{6225b0b0ada94c52b1618cb3ece39390,
title = "Spatial data quality in the IoT era: management and exploitation",
abstract = "Within the rapidly expanding Internet of Things (IoT), growing amounts of spatially referenced data are being generated. Due to the dynamic, decentralized, and heterogeneous nature of the IoT, spatial IoT data (SID) quality has attracted considerable attention in academia and industry. How to invent and use technologies for managing spatial data quality and exploiting low-quality spatial data are key challenges in the IoT. In this tutorial, we highlight the SID consumption requirements in applications and offer an overview of spatial data quality in the IoT setting. In addition, we review pertinent technologies for quality management and low-quality data exploitation, and we identify trends and future directions for quality-aware SID management and utilization. The tutorial aims to not only help researchers and practitioners to better comprehend SID quality challenges and solutions, but also offer insights that may enable innovative research and applications.",
keywords = "geo-sensory data, internet of things, quality management",
author = "Huan Li and Bo Tang and Hua Lu and Cheema, \{Muhammad Aamir\} and Jensen, \{Christian S.\}",
note = "Funding Information: Huan Li [Homepage] is an EU Marie Curie IF Fellow and Assistant Professor with the Department of Computer Science, Aalborg University. He was an Alibaba engineer working on very-large-scale spatial data intelligence platform. He obtained his BSc from Sichuan University and PhD from Zhejiang University. His research interests lie in IoT data management and mobile computing. Most of his research works are published in top-tier database venues. Bo Tang [Homepage] is an Assistant Professor with the Department of Computer Science and Engineering, SUSTech, China. He is leading the database group there since 2017. He received with BSc from Sichuan University and the PhD degree from Hong Kong Polytechnic University. He won ACM SIGMOD China Rising Star Award in 2021. He was a visiting researcher at CWI Amsterdam and MSRA. His research interests are in the area of data management (e.g., database/big-data systems, query optimization techniques). Hua Lu [Homepage] is a Professor of Computer Science, Roskilde University, Denmark. He received the BSc and MSc degrees from Peking University, China, and the PhD degree in computer science from National University of Singapore. His research interests include databases, data mining, and data science. He has served as PC cochair or vice-chair for many international conferences. He received the Best Vision Paper Award at SSTD 2019. Muhammad Aamir Cheema [Homepage] is an ARC Future Fellow and Associate Professor at the Faculty of Information Technology, Monash University, Australia. He obtained his PhD from UNSW Australia in 2011. He is the recipient of 2012 Malcolm Chaikin Prize for Research Excellence in Engineering, 2013 Discovery Early Career Researcher Award, 2014 Dean{\textquoteright}s Award for Excellence in Research by an Early Career Researcher, 2018 Future Fellowship, 2018 Monash Student Association Teaching Award, and 2019 Young Tall Poppy Science Award. He has also won two CiSRA best research paper of the year awards, and several best paper awards at conferences including ICDE, ICAPS, WISE, and ADC. He is the Associate Editor of IEEE TKDE and DAPD. Christian S. Jensen [Homepage] is a professor of computer science at Aalborg University. He was recently at Aarhus University for three years and at Google for one year. His research concerns data analytics and management with focus on temporal and spatiotemporal data management. He is a fellow of the ACM and IEEE, and he is a member of the Academia Europaea, the Royal Danish Academy of Sciences and Letters, and the Danish Academy of Technical Sciences. He has received several awards for his research, most recently the 2019 TCDE Impact Award. He was Editor-in-Chief of ACM TODS from 2014 to 2020 and an Editor-in-Chief of The VLDB Journal from 2008 to 2014. Publisher Copyright: {\textcopyright} 2022 ACM.; ACM SIGMOD International Conference on the Management of Data 2022, SIGMOD 2022 ; Conference date: 12-06-2022 Through 17-06-2022",
year = "2022",
doi = "10.1145/3514221.3522568",
language = "English",
series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",
publisher = "Association for Computing Machinery (ACM)",
pages = "2474--2482",
editor = "John Paparrizos and Rebecca Taft",
booktitle = "SIGMOD'22 - Proceedings of the 2022 International Conference on Management of Data",
address = "United States of America",
url = "https://dl.acm.org/doi/proceedings/10.1145/3514221, https://2022.sigmod.org/",
}