Guo Tong Xie

EIAW: towards a business-friendly data warehouse using semantic web technologies

Data warehouse is now widely used in business analysis and decision making processes. To adapt the rapidly changing business environment, we develop a tool to make data warehouses more business-friendly by using Semantic Web technologies. The main idea is to make business semantics explicit by uniformly representing the business metadata (i.e. conceptual enterprise data model and multidimensional model) with an extended OWL language. Then a mapping from the business metadata to the schema of the data warehouse is built. When an analysis request is raised, a customized data mart with data populated from the data warehouse can be automatically generated with the help of this built-in knowledge. This tool, called Enterprise Information Asset Workbench (EIAW), is deployed at the Taikang Life Insurance Company, one of the top five insurance companies of China. User feedback shows that OWL provides an excellent basis for the representation of business semantics in data warehouse, but many necessary extensions are also needed in the real application. The user also deemed this tool very helpful because of its flexibility and speeding up data mart deployment in face of business changes.

The Object Management Group Ontology Definition Metamodel

Report of a submission being made to a major international software engineering standards group, the Object Management Group which ties together OMG standards with World-Wide Web Consortium and International Standards Organization standards. Major industry bodies including IBM are collaborating, and the submission has the support of 24 companies. OMG, W3C and ISO standards strongly influence the industry, especially in combination. Colomb was a major contributor, responsible for 30% of the submission, and the primary author of the paper.

SQLGraph: An Efficient Relational-Based Property Graph Store

We show that existing mature, relational optimizers can be exploited with a novel schema to give better performance for property graph storage and retrieval than popular noSQL graph stores. The schema combines relational storage for adjacency information with JSON storage for vertex and edge attributes. We demonstrate that this particular schema design has benefits compared to a purely relational or purely JSON solution. The query translation mechanism translates Gremlin queries with no side effects into SQL queries so that one can leverage relational query optimizers. We also conduct an empirical evaluation of our schema design and query translation mechanism with two existing popular property graph stores. We show that our system is 2-8 times better on query performance, and 10-30 times better in throughput on 4.3 billion edge graphs compared to existing stores.

ORIENT: integrate ontology engineering into industry tooling environment

Orient is a project to develop an ontology engineering tool that integrates into existing industry tooling environments - the Eclipse platform and the WebSphere Studio developing tools family. This paper describes how two important issues are addressed during the project, namely tool integration and scalability. We show how Orient morphs into the Eclipse platform and achieves UI and data level integration with the Eclipse platform and other modelling tools. We also describe how we implemented a scalable RDF(S) storage, query, manipulation and inference mechanism on top of a relational database. In particular, we report the empirical performance of our RDF(S) closure inference algorithm on a DB2 database.

Market intelligence portal: an entity-based system for managing market intelligence

Gathering market intelligence (MI) can be critical for the success of an enterprise, and in-depth analysis of this information is helpful in understanding products, business trends, and information concerning competitors. Because of the huge volume of this information and the high rate of its growth, there is a great demand from enterprises for automated MI management systems. In this paper, an information portal for MI management systems is presented. It is based on a semantic web approach and provides the user a single access point for all relevant information about a specific MI topic. In contrast with traditional knowledge portal methods, our work is based on entity-level computing technologies rather than document-level technologies. We present a knowledge network called EntityNet, which is generated by an information synthesis process and enables the network to store entity-level knowledge and provide semantic services for the knowledge worker. From the systems perspective, EntityNets most significant features are its customized document-processing flow and personalized category view. The framework can integrate various text collections, apply data-mining and dissemination functions on the collections with a defined process flow, and present a personalized browsing and searching interface.

A Practical Approach for Scalable Conjunctive Query Answering on Acyclic

Conjunctive query answering for

\mathcal{EL}^+

\mathcal{EL}^{++}

Knowledge Base

ontologies has recently drawn much attention, as the Description Logic

Actively Learning Ontology Matching via User Interaction

\mathcal{EL}^{++}

System and method to validate consistency of component business model maps

captures the expressivity of many large ontologies in the biomedical domain and is the foundation for the OWL 2 EL profile. In this paper, we propose a practical approach for conjunctive query answering in a fragment of