Wee Tiong Ang

Towards ontology-driven navigation of the lipid bibliosphere

BackgroundThe indexing of scientific literature and content is a relevant and contemporary requirement within life science information systems. Navigating information available in legacy formats continues to be a challenge both in enterprise and academic domains. The emergence of semantic web technologies and their fusion with artificial intelligence techniques has provided a new toolkit with which to address these data integration challenges. In the emerging field of lipidomics such navigation challenges are barriers to the translation of scientific results into actionable knowledge, critical to the treatment of diseases such as Alzheimers syndrome, Mycobacterium infections and cancer.ResultsWe present a literature-driven workflow involving document delivery and natural language processing steps generating tagged sentences containing lipid, protein and disease names, which are instantiated to custom designed lipid ontology. We describe the design challenges in capturing lipid nomenclature, the mandate of the ontology and its role as query model in the navigation of the lipid bibliosphere. We illustrate the extent of the description logic-based A-box query capability provided by the instantiated ontology using a graphical query composer to query sentences describing lipid-protein and lipid-disease correlations.ConclusionAs scientists accept the need to readjust the manner in which we search for information and derive knowledge we illustrate a system that can constrain the literature explosion and knowledge navigation problems. Specifically we have focussed on solving this challenge for lipidomics researchers who have to deal with the lack of standardized vocabulary, differing classification schemes, and a wide array of synonyms before being able to derive scientific insights. The use of the OWL-DL variant of the Web Ontology Language (OWL) and description logic reasoning is pivotal in this regard, providing the lipid scientist with advanced query access to the results of text mining algorithms instantiated into the ontology. The visual query paradigm assists in the adoption of this technology.

Ontology-centric integration and navigation of the dengue literature

Uninhibited access to the unstructured information distributed across the web and in scientific literature databases continues to be beyond the reach of scientists and health professionals. To address this challenge we have developed a literature driven, ontology-centric navigation infrastructure consisting of a content acquisition engine, a domain-specific ontology (in OWL-DL) and an ontology instantiation pipeline delivering sentences derived by domain-specific text mining. A visual query tool for reasoning over A-box instances in the populated ontology is presented and used to build conceptual queries that can be issued to the knowledgebase. We have deployed this generic infrastructure to facilitate data integration and knowledge sharing in the domain of dengue, which is one of the most prevalent viral diseases that continue to infect millions of people in the tropical and subtropical regions annually. Using our unique methodology we illustrate simplified search and discovery on dengue information derived from distributed resources and aggregated according to dengue ontology. Furthermore we apply data mining to the instantiated ontology to elucidate trends in the mentions of dengue serotypes in scientific abstracts since 1974.

Experiences on developing SOA based mobile healthcare services

Mobile healthcare (m-Healthcare) systems are regarded as a solution to address skyrocketing healthcare costs without reducing the quality of patient care. It is our aim to build an m-Healthcare platform based on the service-oriented computing paradigm. We are developing a Service-oriented Architecture (SOA) for m-Healthcare services platform, called SOAMOH that shall also support interfacing with the HL7 standard and facilitate the provisioning of healthcare to people anywhere, anytime using mobile devices that are connected through wireless communication technologies.

Correlation-based Attribute Outlier Detection in XML

Compared to relational data models, the hierarchical structure of semi-structured data such as XML provides semantically meaningful neighbourhoods advancing data cleaning problems such as outlier detection. In this paper, we introduce the concept of correlated subspace that leverages on the hierarchical relationships between XML attributes to provide contextually informative neighbourhoods for attribute outlier detection. We also design two correlation-based attribute outlier metrics for XML, namely the xO-Measure and xQ-Measure. The effectiveness of our XML outlier detection approach is supported with experimental results.

Ontology-centric, Service-Oriented Enterprise Campaign Management System

Public relations is an important management staff function in this computer age, and accurate media information retrieval and appropriate measurement for publicity tracking in a campaign management system is of utmost importance. This paper proposes an intelligent campaign management system, called KnowleTracker, based on a semantic service-oriented approach. KnowleTracker has powerful deep mining functions to pull out news and other information that may lie several layers below the front page based on a semantic search for not only the specific keyword, but also the associated concepts that are not part of the keywords. The returned results are presented at different levels of detail and viewed from different angles, and show customers, detailed information of where their news releases are distributed. We demonstrate the utility of KnowleTracker in a real-world scenario through a case study on “A*STAR Event Campaign Management”, and argue that our system is an effective tool to tackle the complex task of campaign management and tracking. A Web Demo is available at: http://datam.i2r.a-star.edu.sg/est/demo/icsc2009/.

Managing Publicity Campaigns with Semantic Technologies

Tracking accurate readership, impact and timely delivery of the news is an important problem faced by Publicity Campaign managers. We present a solution for publicity campaign management and tracking with an integrated semantic infrastructure, called Knowle. Through detailed a walkthrough, we show how the system can be used for campaign management in a real-world scenario through a case study on “A*STAR Publicity Campaign Management”.

Slicing through the Scientific Literature

Success in the life sciences depends on access to information in knowlegde bases and literature. Finding and extracting the relevant information depends on a users domain knowledge and the knowledge of the search technology. In this paper we present a system that helps users formulate queries and search the scientific literature. The system coordinates ontologies, knowledge representation, text mining and NLP techniques to generate relevant queries in response to keyword input from the user. Queries are presented in natural language, translated to formal query syntax and issued to a knowledge base of scientific literature, documents or aligned document segments. We describe the components of the system and exemplify using real-world examples.