PerfectO: An Online Toolkit for
Improving Quality, Accessibility,
and Classification of Domain-Based
Ontologies
Amélie Gyrard, Ghislain Atemezing, and Martin Serrano
Abstract Sensor-based applications are increasingly present in our everyday life.
Due to the enormous quantity of sensor data produced, interpreting data and building interoperable sensor-based applications is needed. There are several problems
to address the heterogeneity of (1) data format, (2) languages to describe sensor
metadata, (3) models for structuring sensor datasets, (4) reasoning mechanisms and
rule languages to interpret sensor datasets, and (5) applications. Semantic Web technologies (a.k.a, knowledge graphs), are immersed in an increasing number of online
activities we perform today (e.g., search engines for gathering information). There
is a need to find better ways to share data and distribute more meaningful and more
accurate information. Innovative methodologies are needed to link and associate
the data from different domains to improve knowledge discovery. Semantic knowledge graphs, made of datasets and ontologies, are intended to describe and organize
heterogeneous data explicitly. If an ontology is widely used to structure data of a
particular domain, the accessibility and the efficiency in sharing and reusing that
information will increase. For this reason, we focused on the ontology quality used
when building sensor-based applications. We designed PerfectO, a Knowledge
Directory Services tool, focusing on ontology best practices, which: (1) improves
knowledge quality, (2) leverages usability, accessibility, and classification of the
information, (3) enhances engineering experience, and (4) promotes engineering
best practices. PerfectO implementation is applied to the Internet of Things (IoT)
Thanks to the Linked Open Vocabularies (LOV) team for sharing their expertise regarding the usage
of validation tools.
A. Gyrard (B)
Kno.e.sis, Wright State University, Dayton, USA
e-mail: amelie@knoesis.org
Trialog, Paris, France
G. Atemezing
Mondeca, 35, Boulevard Strasbourg, Paris 75010, France
e-mail: ghislain.atemezing@mondeca.com
M. Serrano
Insight Center for Data Analytics, National University of Galway, Galway, Ireland
e-mail: martin.serrano@insight-centre.org
© Springer Nature Switzerland AG 2021
R. Pandey et al. (eds.), Semantic IoT: Theory and Applications, Studies in Computational
Intelligence 941, https://doi.org/10.1007/978-3-030-64619-6_7
161
Improving Quality, Accessibility,
and Classification of Domain-Based
Ontologies
Amélie Gyrard, Ghislain Atemezing, and Martin Serrano
Abstract Sensor-based applications are increasingly present in our everyday life.
Due to the enormous quantity of sensor data produced, interpreting data and building interoperable sensor-based applications is needed. There are several problems
to address the heterogeneity of (1) data format, (2) languages to describe sensor
metadata, (3) models for structuring sensor datasets, (4) reasoning mechanisms and
rule languages to interpret sensor datasets, and (5) applications. Semantic Web technologies (a.k.a, knowledge graphs), are immersed in an increasing number of online
activities we perform today (e.g., search engines for gathering information). There
is a need to find better ways to share data and distribute more meaningful and more
accurate information. Innovative methodologies are needed to link and associate
the data from different domains to improve knowledge discovery. Semantic knowledge graphs, made of datasets and ontologies, are intended to describe and organize
heterogeneous data explicitly. If an ontology is widely used to structure data of a
particular domain, the accessibility and the efficiency in sharing and reusing that
information will increase. For this reason, we focused on the ontology quality used
when building sensor-based applications. We designed PerfectO, a Knowledge
Directory Services tool, focusing on ontology best practices, which: (1) improves
knowledge quality, (2) leverages usability, accessibility, and classification of the
information, (3) enhances engineering experience, and (4) promotes engineering
best practices. PerfectO implementation is applied to the Internet of Things (IoT)
Thanks to the Linked Open Vocabularies (LOV) team for sharing their expertise regarding the usage
of validation tools.
A. Gyrard (B)
Kno.e.sis, Wright State University, Dayton, USA
e-mail: amelie@knoesis.org
Trialog, Paris, France
G. Atemezing
Mondeca, 35, Boulevard Strasbourg, Paris 75010, France
e-mail: ghislain.atemezing@mondeca.com
M. Serrano
Insight Center for Data Analytics, National University of Galway, Galway, Ireland
e-mail: martin.serrano@insight-centre.org
© Springer Nature Switzerland AG 2021
R. Pandey et al. (eds.), Semantic IoT: Theory and Applications, Studies in Computational
Intelligence 941, https://doi.org/10.1007/978-3-030-64619-6_7
161