Keywords:
Ontologies
Semantic Web
Query answering on graph databases
Query answering on data streams
Query processing in graph-based data models
Conception of flexible query answering mechanisms for complex
databases modeled as graphs. Support to similarity queries with
semantically meaningful structural approximations.
Data storage and real-time query processing in data stream
management systems for infomobility
Definition of efficient techniques for data storage either in
main or secondary memory, according to different information
availability needs. Complex event detection to trigger alerting
systems and monitoring of traffic data. Real-time processing of
queries with geo-referenced and temporality requirements.
Effective query processing and efficient access to distributed and
heterogeneous information like that available on the Web imply
sophisticated techniques which range several information management
areas. The Semantic Web is developed to help the user to take
advantage of this information.
Query processing in graph-based data models
In several application areas in the database field graph-based
data models prove to be particularly suitable for information
representation. In these application domains, largeness and
heterogeneity of information are common features which
characterize the datasets. These peculiarities make it impractible
to exactly query the data due to the lack of a complete knowledge
of the vocabulary used, as well as of the information about how
data is organized. A primary goal os then the definition of
flexible query mechanisms which allow the user to easily query
complex databases modeled as graphs and get relevant answers. The
research activity is devoted to the study of a general model for
processing queries, where query approximations are supported in a
two-fold fashion: 1) node and edge label mismatch and 2) structural
relaxation of relationships between data. A key contribution is the
definition of Semantic Relatedness relation to allow
semantically meaningful relaxations only.
Data storage and real-time query processing in data stream
management systems
The support to sustainable urban mobility of people and goods
in a territory has become one of the major challenges which has
recently gained much interest in several ICT research areas. The
development of new transport and mobility concepts have been
promoted in the EU with the aim of developing innovative and
effective initiatives, bringing together all elements of a clean,
energy-efficient, safe and intelligent transportation. The research
context is that of Intelligent Transportation Systems (ITSs) which
provide reliable and timely information to improve the safety and
the efficiency of vehicles' and goods' flows, as well as to make
transportation a smart experience. One of the major challenges is
the management of the multitude of stream items which originates
from vehicles. The research activity is dedicated to storing
real-time temporal stream items which must be
accessed and manipulated efficiently to promptly answer users'
requests. Scalability, modularity, and temporal data
management capabilities are thus essential requirements to be
supported.
