How many truths can you handle? Strategies and techniques for handling vagueness in data models
Dr. Panos Alexopoulos, Textkernel
Vagueness is a common human knowledge and language phenomenon, demonstrated by terms and concepts with blurred boundaries, like tall, expert etc., whose extensions is difficult to precisely determine (e.g. some people are borderline tall: neither clearly “tall” nor “not tall”). When building (semantic) data models, modelers and domain experts often need to use such vague concepts. If this is not done properly, then these vague concepts will influence in a negative way the comprehension of the models by other parties and will limit their value as a reusable source of knowledge. The reason is the subjective interpretation of vague definitions that can cause disagreements among the people who develop, maintain or use a data model.
In this talk I will present a set of practical strategies and techniques for tackling vagueness in data modeling and creating models that are semantically more accurate and interoperable. Key take aways for the audience include:
- How to detect and measure the existence and impact of vagueness in a data model
- How to explicitly represent vagueness in a data model
- How to make data-intensive applications benefit from vagueness.
Panos Alexopoulos has been working for more than 12 years at the intersection of data, semantics, language and software, contributing in building semantics-powered systems that deliver value to business and society. Born and raised in Athens, Greece, Panos currently works as Head of Ontology at Textkernel, in Amsterdam, Netherlands, where he leads a team of data professionals (Linguists, Data Scientists and Data Engineers) in developing and delivering a large cross-lingual Knowledge Graph in the HR and Recruitment domain. Prior to Textkernel, he worked at Expert System Iberia (former iSOCO) in Madrid, Spain, as a Semantic Applications Research Manager, and at IMC Technologies in Athens, Greece, as a Semantic Solutions Architect and Ontologist.Academically, Panos holds a PhD in Knowledge Engineering and Management from National Technical University of Athens, and has published ~60 papers at international conferences, journals and books. He strives though to present his work and experiences in all kinds of venues, trying to bridge the gap between academia and industry so that they can benefit from one another.