Track chairs:
Mohamed Reda Bouadjenek, Deakin University, Australia
[email protected]

Khouloud Boukadi, University of Sfax, Tunisia
[email protected]

Haytham Elghazel, Université Claude Bernard Lyon 1, France
[email protected]

Scope
The Data science, Knowledge Engineering, and Ontologies Track welcomes submissions of original, high-quality research related to data analytics, the extraction of information, the analysis, recommendation, and mining of data content. We also encourage submissions that explore how people understand, engage and interact with data content through Information Retrieval, including discovery, recommendations or question answering, and Big Data, Databases and Knowledge Systems. Research on both theoretical and applied aspects of data science and Knowledge Engineering-related tasks is encouraged.

Topics
The topics of interest of the track include, but are not limited to:
– Data science
             – Advanced data analytics
             – Machine learning and data science ( Learning representations and features from data, Machine learning algorithms for large-scale content mining)
             – Data cleaning
             – Data visualization
– Information Search and Retrieval
            – Query and document analysis, representation and understanding
            – Web search models, and ranking
            – Web recommender systems
            – Evaluation methodologies and metrics
– Knowledge engineering, and ontologies
            – Ontologies and semantics
            – Techniques for the creation, curation, publication and consumption of Knowledge Graphs, including Methods for Developing and Maintaining Shared Vocabularies/Ontologies
           – Data Modeling and Inference
           – Explanations and User-friendly Interaction
           – Exploitation of Semantic Data for Machine Learning Tasks

Examples of application areas :
• Healthcare
• Social sciences
• Recommender platforms
• Logistics
• Transportation
• Urban planning
• Resource management (energy, water, air quality, waste management).