Wukong

Querying graph data is becoming increasingly prevalent and important across many application domains, like social networking, urban monitoring, electronic payment, and semantic webs. In the last few years, we have ben working on improving the performance of graph querying by leveraging new hardware features and system designs. Moving towards this goal, we have designed and developed Wukong, a distributed in-memory framework that provides low latency and high throughput for concurrent query processing over large and fast-evolving graph data. This article overviews our architecture and presents four systems that aim to satisfy diverse challenging requirements on graph querying (e. g. high concurrency, evolving graphs, workload heterogencity, and locality preserving). Our systems also significantly outperform state-of-the-art systems in both latency and throughput, usually by orders of magnitude.

QueDI: From Knowledge Graph Querying to Data Visualization

While Open Data (OD) publishers are spur in providing data as Linked Open Data (LOD) to boost innovation and knowledge creation, the complexity of RDF querying languages, such as SPARQL, threatens their exploitation. We aim to help lay users (by focusing on experts in table manipulation, such as OD experts) in querying and exploiting LOD by taking advantage of our target users’ expertise in table manipulation and chart creation. We propose QueDI (Query Data of Interest), a question-answering and visualization tool that implements a scaffold transitional approach to 1) query LOD without being aware of SPARQL and representing results by data tables; 2) once reached our target user comfort zone, users can manipulate and 3) visually represent data by exportable and dynamic visualizations. The main novelty of our approach is the split of the querying phase in SPARQL query building and data table manipulation. In this article, we present the QueDI operating mechanism, its interface supported by a guided use-case over DBpedia, and the evaluation of its accuracy and usability level.