Spatial vector data with high-precision and wide-coverage has exploded globally, such as
land cover, social media, and other data-sets, which provides a good opportunity to enhance …

The recent explosion in the amount of spatial data calls for specialized systems to handle
big spatial data. In this survey, we summarize the state-of-the-art work in the area of big …

The widespread use of location-aware devices together with the increased popularity of
micro-blogging applications (eg, Twitter) led to the creation of large streams of spatio-textual …

Huge amount of data with both space and text information, eg, geo-tagged tweets, is
flooding on the Internet. Such spatio-textual data stream contains valuable information for …

Cassandra is a highly available and scalable data store but it provides only limited
capabilities for data analyses. However, database management systems (DBMS) provide a …

The proliferation of mobile phones and location-based services has given rise to an
explosive growth in spatial data. To enable spatial data analytics, spatial data needs to be …

Advances in location-based services (LBS) demand high-throughput processing of both
static and streaming data. Recently, many systems have been introduced to support …

In this paper, we propose a method to ingest big spatiotemporal data using a parallel
technique in a cluster environment. The proposed method includes an indexing method for …

Ease of availability of spatial data has increased the interest in the domain of spatial
computing. Various services such as Uber, Google maps, and Blue Brain Project have been …

Predicting query cost plays an important role in moving object databases. Accurate
predictions help database administrators effectively schedule workloads and achieve …