Abstract

Data management plays an indispensable role in enabling, improving and enriching various LBS applications. Today’s LBS applications are increasingly expected to be ubiquitous (e.g., functional across space boundaries) and smart (e.g., adaptive to implicit or even unknown user locations). Focusing on such expectations, this talk will introduce three relevant aspects of my research. First, I will present indoor data management that aims to support LBS in a new frontier – indoor space. Second, I will talk about social data management for LBS users with explicit or implicit locations. Third, I will touch upon how to make sense of mobility data generated in broad LBS settings. In the end of the talk, I will share with the audience my thoughts on the directions of future research on LBS in the context of big spatial data.

Bio

Hua Lu is an Associate Professor in the Department of Computer Science, Aalborg 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 data management, geographic information systems, and mobile computing. Recently, he has worked on indoor data management, location related social data management, and mobility data cleansing and analytics. He has served as PC cochair or vice chair for NDBC 2019, MDM 2016 (PhD forum), SSDBM 2014 (demo track), MDM 2012, MUE 2011 and ISA 2011. He has served regularly on the program committees for conferences such as VLDB, ICDE, KDD, CIKM, DASFAA, ACM SIGSPATIAL, SSTD, MDM and PAKDD. He is a senior member of the IEEE.