Related papers: STREAK: An Efficient Engine for Processing Top-k S…
There has been increased interest in data search as a means to find relevant datasets or data points in data lakes and repositories. Although approaches have been proposed to support spatial dataset search and data point search, they…
A major problem of unstructured P2P systems is their heavy network traffic. This is caused mainly by high numbers of query answers, many of which are irrelevant for users. One solution to this problem is to use Top-k queries whereby the…
The ability to update information acquired through various means online during task execution is crucial for a general-purpose service robot. This information includes geometric and semantic data. While SLAM handles geometric updates on 2D…
Low reliability and availability of public SPARQL endpoints prevent real-world applications from exploiting all the potential of these querying infras-tructures. Fragmenting data on servers can improve data availability but degrades…
Modern big data systems run on cloud environments where resources are shared amongst several users and applications. As a result, declarative user queries in these environments need to be optimized and executed over resources that…
How do RDF datasets currently get published on the Web? They are either available as large RDF files, which need to be downloaded and processed locally, or they exist behind complex SPARQL endpoints. By providing a RESTful API that can…
The FAIR (Findable, Accessible, Interoperable, Reusable) data principles are fundamental for climate researchers and all stakeholders in the current digital ecosystem. In this paper, we demonstrate how relational climate data can be "FAIR"…
Road traffic forecasting is crucial in real-world intelligent transportation scenarios like traffic dispatching and path planning in city management and personal traveling. Spatio-temporal graph neural networks (STGNNs) stand out as the…
Scheduling services within the computing continuum is complex due to the dynamic interplay of the Edge, Fog, and Cloud resources, each offering distinct computational and networking advantages. This paper introduces SCAREY, a user…
The Web of Data is an open environment consisting of a great number of large inter-linked RDF datasets from various domains. In this environment, organizations and companies adopt the Linked Data practices utilizing Semantic Web (SW)…
As the volume of the RDF data becomes increasingly large, it is essential for us to design a distributed database system to manage it. For distributed RDF data design, it is quite common to partition the RDF data into some parts, called…
Enterprises rely on RDF knowledge graphs and SPARQL to expose operational data through natural language interfaces, yet public KGQA benchmarks do not reflect proprietary schemas, prefixes, or query distributions. We present PIPE-RDF, a…
Linked Open Data (LOD) has been proliferated over various domains, however, there are still lots of open data in various format other than RDF, a standard data description framework in LOD. These open data can also be connected to entities…
Many applications need to process massive streams of spatio-textual data in real-time against continuous spatio-textual queries. For example, in location-aware ad targeting publish/subscribe systems, it is required to disseminate millions…
Perception in fields like robotics, manufacturing, and data analysis generates large volumes of temporal and spatial data to effectively capture their environments. However, sorting through this data for specific scenarios is a meticulous…
With the ongoing, gradual shift of large-scale distributed systems towards the edge-cloud continuum, the need arises for software solutions that are universal, scalable, practical, and grounded in well-established technologies.…
From biological systems to cyber-physical systems, monitoring the behavior of such dynamical systems often requires to reason about complex spatio-temporal properties of physical and/or computational entities that are dynamically…
Since 2007, geospatial extensions of SPARQL, like GeoSPARQL and stSPARQL, have been defined and corresponding geospatial RDF stores have been implemented. In addition, some work on developing benchmarks for evaluating geospatial RDF stores…
Understanding how users tailor their SPARQL queries is crucial when designing query evaluation engines or fine-tuning RDF stores with performance in mind. In this paper we analyze 3 million real-world SPARQL queries extracted from logs of…
The rapid growth of big spatial data urged the research community to develop several big spatial data systems. Regardless of their architecture, one of the fundamental requirements of all these systems is to spatially partition the data…