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incorporate a wide scale of automated systems, such as security system, access con-
trol system, fire alarm system or building automation systems that controls Heating,
Ventilation, Air Conditioning (HVAC) devices. Building Management System (BMS)
facilitates remote monitoring and controlling of the building operations. The detailed
description of CAFM and BMS software can be found in [1, 2].
Currently the integration of BMS data with CAFM and BIM is simplified, which
is not effectively queried because the integration is missing. The integration between
them is impossible, without semantic structure because BMS data is determined by net-
work topology. The semantic structure is required for the advanced analytical features
of CAFM software, which are currently not integrated with BMS data. The missing
integration between CAFM, BMS and BIM does not affect small sites with less instal-
lation, as long as data collection and analysis are performed manually. However, for
large sites (i.e. installation of hundreds of devices, thousands of sensors), manual data
collection prevents effective gathering of required information. Despite of large sites,
BMS contains large amount of accurate, up-to-date and detailed data which is valuable
for building operation analysis. This data cannot be collected by any other way, other
than semantic structure (i.e. designing Ontology Model).
Currently the integration of BMS data with CAFM and BIM is simplified to a simple
structure that cannot be effectively queried because the integration part is completely
missing. The integration is impossible because BMS data structure is determined by the
network topology, not by the semantic structure. The semantic structure is required be-
cause the advanced analytical features of CAFM software are currently not integrated
with for BMS data. This does not affect the small installations, where data retrieval
and analysis can be easily performed manually. However, for large sites (hundreds of
devices, thousands of sensors), the amount of data prevents effective gathering of re-
quired information. Despite of this, BMS contains large amount of accurate, up-to-date
and detailed data which are valuable for building operation analysis. This data cannot
be collected by any other way, other than semantic structure (i.e. designing Ontology
Model).
Development of analytical systems for building operations requires expertise in
fields of building automation protocols and building technologies, which is not common
among commercial IT experts. Vendors of building automation systems focus on devel-
opment of the hardware. Software, which is provided by vendors with the hardware, is
used for management and programming the building technologies system in everyday
operations, rather than for analytical operations. Developing the complex systems for
analytical operations is commercially unprofitable in large sites; therefore, development
of such systems is rare in current time. Comparing to small sites, data analysis is per-
formed by simple approaches such as defining manual reports, exporting raw data (an
ad-hoc analysis is performed by end users) or using purely financial data (i.e. invoices)
for operation analysis.
Overcoming the issue of analytical system complexity, the goal of this research pro-
posal is to define a middleware layer. The middleware layer will simplify development
of advanced applications in the field of building operation analysis. It is worth to note,
that the aim of the work is not to provide tools for building operations analysis, but to
develop a middleware layer. The development of middleware tools, models, methods
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Smart Building: SemanticWeb Technology Services for BIM (Location and Device Information)
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