(728b) Ontology Engineering Approach to Support Process of Model and Data Integration

Ontology engineering approach to
support process of model and data integration

Linsey
Koo, Edlira Kalemi, Franjo Cecelja,

Process
and Information Systems Engineering, Faculty of Engineering and Physical
Sciences, University of Surrey, Guildford, Surrey, U. K.

Process
modelling and simulation is a vital tool to plan, evaluate, assess, and develop
different alternatives for the design of products and processes. The complexity
of problems as well as heterogeneity of modelling methods make process
modelling and simulation challenging, time consuming and often tedious process
requiring a wide range of expertise. Inconsistencies in model development are
the main cause for redundant work.  Models
remain implicit to the engineers who have built them, which further limits the
potential of reusability.

The only
model integration framework in use, the CAPE-OPEN, addresses the issue of
standardisation of interfaces to enable interoperability between simulator
software components from different sources. It is the framework built around a
middleware, the Common Object Request Broker Architecture (CORBA) that hosts
communication between unit operations defined for a specific function and the
process modelling environments. The standard specification is defined as a
property package which is needed for a thermodynamic or physical property
calculation. The interoperability of models, such as model selection, parameter
identification, and experimental work is enabled through the connection related
to the unit operations and physical properties. It is not necessary to match
all parameters in order to facilitate Input-Output (I-O) matching. However, the
shortcoming of the CAPE-OPEN is in the need for identifying key variables for
each unit operation. Also, it does not facilitate data integration.

In this
paper a new approach for model and data integration is proposed which builds
upon the CAPE-OPEN framework and proposes the use of ontology and replaces the object
bus with more flexible semantic repository (Koo, Trokanas and Cecelja, 2017). Models are
described by Semantic Web Services (SWS) using Ontology Web Service Description
(OWL-S) as an enabler of web services through service discovery, selection,
composition, and execution stages (
REF _Ref511651865 \h Figure
1 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003500310031003600350031003800360035000000
). By The same token, datasets are also described by
the OWL-S through their outputs and auxiliary precondition for their execution,
i.e. extraction, modification and deletion (
REF _Ref511651844 \h Figure
2 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003500310031003600350031003800340034000000
). The discovery stage allows formation of an
integrated model through matching requests from a public repository(ies). The best match that satisfy the requestor’s
functionality is selected in the model selection stage. The model composition
stage then formulates the chain of integrated models and execution of
integrated model takes place during the execution stage.

Figure 1 Semantically
described model

Figure 2 Semantically
described datasets

This paper
focuses on the matching parameters related to the domain of process system
engineering, with emphasis placed on the role of physical properties and unit
operation. Each model and dataset representing a device (e.g. unit operations,
flowsheets, subflowsheets etc.) is semantically
described in domain ontology including domain assumptions and descriptions of
the functionality of the model. The domain ontology guides the process of registering
models and instantiation of ontology through ontology parsing, which makes the
model and data explicit and sharing terminology in domain ontology improves
consistency. The devices in a process are connected via streams that transmit
information through multiple inlets and outlets from one unit to the other. The
connection between devices are described in ontology by introducing the concept
of ‘ports’ and ‘connections’. The ‘ports’ generally describe inlets and outlets
of devices and three different types of streams are distinguished: material,
energy, and information, which are further described by objective properties.
The ‘connections’ are the object that is responsible for establishing a link
between two ports, which contains information regarding methods, types,
quantities, and units of streams.

The whole
process is verified by a case of model integration for a supply chain modelling
in biorefining.

Koo, L., N.
Trokanas, et al. (2017). "A semantic framework for enabling model
integration for biorefining." Computers &
Chemical Engineering 100: 219-231