Following the analysis of existing BIM and GIS standards, formats, differences in the interpretations of the underlying concepts have been identified. Still, in each of the two considered domains several ontologies have been defined for these terms without seeking an alignment among their definitions. With this scope in mind, this article presents several mappings expressed by means of explicit semantic links between GIS concepts (as present in the related ontologies for the ISO 191XX standard family) and BIM concepts (as represented in the IFC standard ISO 16739:2018). Such semantic mappings are defined in order to ensure a knowledge continuum between both domains, thus enabling seamless reasoning in application contexts spanning over them e.g. urban contexts.
Building Information Modeling (BIM) and Geographical Information Systems
(GIS) both address modelling of environments: traditionally GIS focus on natural
environment, whereas BIM targets built environments. Developed until now
independently, both domains are addressed by different standards. Following " Building
information models — Information delivery manual — Part 1: Methodology and
format"
BIM is the process of generating, storing, managing, exchanging, and sharing
building information [8] in an open format, namely IFC. BIM focuses on the creation of
virtual 3D models that can be explored and modified by all the stakeholders involved
in a construction project. At the level of the ISO, it is the Technical Committee ISO/
TC 59/SC 13 "Organization and Digitization of information about buildings and civil
engineering works, including building information modelling (BIM)" that is in charge
of developing BIM-related standards. Three main ISO standards exist for BIM: (1)
Information Delivery Manual (IDM)
When considering standard BIM ontologies, only one ontology exists namely the ifcOWL ontology. The process generating this ontology is described in [22]. The ap proach of [22] implements a conversion pattern (algorithm) provided in Java and C++ to convert the considered EXPRESS schema (simple, defined, list aggregation, array aggregation data types, etc.) into OWL (OWL class hierarchy, object properties, etc.). The generated ifcOWL ontology is in OWL2 DL, matches the original EXPRESS schema, and allows the conversion of IFC STEP files into equivalent RDF graphs. Different ifcOWL versions have been generated for each version of the IFC standard and are available online1. Several researches have tackled improving the standard ifcOWL ontology. [7] proposes an ifcOWL ontology where EXPRESS collections (e.g. LIST) are mapped as OWL properties, and IFC defined types are not directly converted to OWL classes. [7] proposes an IfcWoD ontology that has a lower expressivity (ALUIF(D) instead of SHIQ(D) for ifcOWL). IfcWoD comes with two main advantages compared to the standard ifcOWL version: (1) EXPRESS collections are mapped as OWL properties instead of RDF or OWL Lists, and (2) IFC defined types aren't directly converted into classes. This allows having shorter and more efficient SPARQL queries. [4] transforms the Construction Operations Building Information Exchange (COBie) standard into the COBieOWL ontology (in OWL Lite with an ALCHIF(D) expressivity) and apply Linked Data principles for linking it to vocabularies such as FOAF. The COBieOWL ontology is also aligned to the ifcOWL ontology by transforming the COBie MVD into SWRL rules [6]. Federation among the Ifc 1 https://github.com/buildingSMART/ifcOWL WoD and the COBieOWL ontologies is implemented using the FOWLA framework [5]. 3 3.1
As mentioned in the Introduction, GIS refers to "information systems dealing with
information concerning phenomena associated with location relative to the Earth"
[10]. ISO/TC 211 "Geographical Information" is the ISO technical committee in
charge of standardization in the field of digital geographic information. Its goal is to
"establish a structured set of standards for information concerning objects or
phenomena that are directly or indirectly associated with a location relative to the Earth" [18].
GIS represents the information system that allows handling such objects and
phenomena [10]. ISO/TC 211 has defined the different standards forming the ISO 19100
standard family. Conceptual modelling in the ISO 19100 series is based Model-driven
Architectures (MDA). Four levels are considered: (1) Metamodel level contains
“Geographic information — Rules for application schema.”
ISO/TC 211 established a group for the maintenance of ontologies (GOM) respon sible to create and publish ISO/TC 211 ontologies (https://github.com/ISO-TC211/ GOM). The table below lists the standards that have associated ontology representa tions (as published on the TC211 website: https://def.isotc211.org/ontologies/). These ontologies are also published on the ISO/TC211 GitHub repository: https://github.com/ISO-TC211/ontologies. Elements in bold in the table below are the standards concerned by the mappings defined in this paper. The ISO reference model dealing with geographic information, described from 4 viewpoints: semantic, syntactic, service, and procedural. One of the goals of this reference model is to "ensure interoperability" with other domains and to ease the integration of "integrate geographic information with other types of information and conISO 19103 ISO 19109
ISO standard
versely".
Conceptual It provides rules and guidelines for the use of a conceptual schema schema lan- language within the context of geographic information. The concepguage tual schema language used is the Unified Modeling Language (UML).
The RulesForApplicationSchema imports UtilityClasses and GeneralfeatureModel ontologies from ISO 19109:2015, along with the base Rules for ontology from ISO 19150-2:2012.The GeneralFeatureModel ontology application imports UtilityClasses ontology from ISO 19109:2015, NameTypes schema ontology from ISO 19103:2015, MetadataEntitySetInformation ontology from ISO 19115:2003 along with the base ontology from ISO 19150-2:2012.
The SpatialSchema ontology imports Geometry and Topology ontologies from ISO 19107:2003 along with the base ontology from ISO 19150-2:2012. The Topology ontology imports TopologicalComplex, Spatial TopologicalPrimitive, and TopologyRoot ontologies from ISO 19107:2003 along with the base ontology from ISO 19150-2:2012. schema
The Geometry ontology imports CoordinateGeometry, GeometricAggregates, GeometricComplex, GeometricPrimitive, GeometryRoot ontologies from ISO 19107:2003 along with the base ontology from ISO 19150-2:2012 Temporal The TemporalSchema ontology imports TemporalObjects and TemporalReferenceSystem ontologies from ISO 19108:2006 along with schema
the base ontology from ISO 19150-2:2012.
Methodology The MethodologyForFeatureCataloguing ontology imports FeatureCfor feature ataloguing and FeatureCatalogueRegister ontologies from ISO cataloguing 19110:2016 along with the base ontology from ISO 19150-2:2012. Referencing The ReferencingByCoordinates ontology imports CommonClasses,
Coordinates, CoordinateReferenceSystems, CoordinateSystems, by coordinates Datums and CoordinateOperations ontologies from ISO 19111:2019 along with the base ontology from ISO 19150-2:2012.
Spatial refer- It establishes a general model for spatial referencing using geographic encing by ge- identifiers and defines the components of a spatial reference system. It ographic only covers the definition and recording of the referencing feature, identifier and does not consider the forms of the relationship.
It defines the schema required for describing geographic information and services. It provides information about the identification, the exMetadata tent, the quality, the spatial and temporal schema, spatial reference, and distribution of digital geographic data.
Schema for The Coverages ontology imports CoverageCore, DiscreteCoverages, coverage ge- ThiessenPolygon, QuadrilateralGrid, HexagonalGrid, TIN, and Segometry and mentedCurve ontology from ISO 19123:2005 along with the base onfunctions tology from ISO 19150-2:2012.
Core profile It defines a core profile of the spatial schema detailed in ISO 19107 of the spatial that specifies, following ISO 19106, a minimal set of geometric eleschema ments necessary for the efficient creation of application schemata. Schema for It defines a method to describe the geometry of a feature that moves as moving fea- a rigid body, such as feature that moves along a planned route, or motures tion influenced by physical forces.
Schema of The standard provides ways to specify locations along linear elements 19148 ISO 19157
ISO standard
ISO 19104 linear refer- such as transport network links or alignments. In essence, any object encing where a location can be referenced using one measure.
It establishes principles for reporting data quality, and also defines a Data quality set of data quality measures for use in evaluating and reporting data quality.
Terminology
The Terminology ontology imports TermRegister ontology from ISO 19104 along with the base ontology from ISO 19150-2:2012.
sensor mod- The ImagerySensorModelsForGeopositioningPart1_Fundamentals onels for tology imports SensorData ontology from ISO 19130-1:2018 along geoposition- with the base ontology from ISO 19150-2:2012.
ing
The DataProductSpecification ontology imports DPS, SpecificationAdditionalInformation, SpecificationContentAndStructure, SpecificationDataCaputreInformation, SpecificationDataQualityRequirement, SpecificationDeliveryInformation, SpecificationIdentification, SpecificationMaintenanceInformation, SpecificationPortrayalInformation, SpecificationReferenceSystem, and SpecificationScopes ontolgies Data product specifi- from ISO 19131:2007 along with the base ontology from ISO 191502:2012. The DPS ontotology imports SpecificationPortrayalInformacations tion, SpecificationScopes, SpecificationDataCaptureInformation, SpecificationDeliveryInformation, SpecificationReferenceSystem, SpecificationDataQualityRequirement, SpecificationIdentification, SpecificationMaintenanceInformation, SpecificationContentAndStructure, SpecificationAdditionalInformation ontolgies from ISO 19131:2007 along with the base ontology from ISO 19150-2:2012.
Positioning services Portrayal Encoding Services
It specifies the data structure and content of an interface that permits communication between position-providing device(s) and position-using device(s) to interpret position information and determine whether the resulting position information meets the requirements of the intended use.
It provides an abstract model for developers of portrayal systems so that they can implement a system with the flexibility to portray geographic data to a user community in a manner that makes sense to that community.
It specifies the requirements for encoding rules, encoding services and XML-based encoding, for the interchange of data that conform to the geographic information in the set of International Standards known as the "ISO 19100 series".
The Services ontology imports ServiceMetadata, and ServiceModel ontologies from ISO 19119:2005 along with the base ontology from ISO 19150-2:2012.
Feature con
The FeatureConcepts ontology imports FeatureConceptDictionary, cept dictio- and HierarchicalFeatureInformationRegister ontologies from ISO naries and
19126:2009 along with the base ontology from ISO 19150-2:2012. registers ISO 19128 ISO 19129 ISO 19132 ISO 19133 ISO 19134 ISO 19135 ISO 19136 Procedures It specifies procedures to be followed in establishing, maintaining and publishing registers of unique, unambiguous and permanent identififor item registration ers, and meanings that are assigned to items of geographic information.
It is developed within the Open Geospatial Consortium (OGC). GML is an XML schema for the description of application schemas as well as the transport and storage of geographic information.
Core profile It defines a core profile of the spatial schema detailed
in ISO 19107 that specifies, following ISO 19106, a minimal set of of the spatial schema geometric elements necessary for the efficient creation of application schemata.
Metadata - It provides the XML implementation schema for ISO 19115 specifyXML schema
ing the metadata record format and may be used to describe, validate, implementa- and exchange geospatial metadata prepared in XML tion
It is divided into two parts Classification system structure, and Land Cover Meta Language (LCML). The first part aims to develop future Classification systems classification systems that offer more reliable collection methods. The second part allows different land cover classification systems to be described based on the physiognomic aspects.
Registry of representa- It specifies the process for establishing, maintaining and publishing tions of geo- registers of representation of geographic point location in compliance graphic point with ISO 19135.
location
Cross-do- It establishes a methodology for cross-mapping between vocabularies main vocabu- used by geospatial communities. Its purpose is to provide rules for enlaries suring consistency when implementing cross-mapping processes. ISO 19150 ISO 19154 ISO 19156 ISO 19159 ISO 19160
It defines rules and guidelines for the development of ontologies to Ontology support geographic information over the Semantic Web. It defines the conversion of the UML standards into OWL. pUubbliiqcuaictocuesss fTohrims asttiaonnd.aIrtddceofinnseidserresqUuibreiqmueitnotussinPtuebrlmicsAofccsetasnsdtoargdeizoagtriaopnhoicf siny-s- Reference tems and services supporting it.
model aOnbdsmemrevenaatstsiuornes- ((vFSOiooWlGulosCEwl)y0ianp7cg-ut0ibtv2hlii2etsyrhc1)eo,)dotahpOniedsGrsaPCttaaiornstntda2awnr–dditaShcradoOmsm:GppPClriain'rsstgeSs1Fe2—enapstoauOrrrtbeWsssaee(srObvdaGEetrinCoiavn0be7lsdec-mf0hr0eeo2mnmrta3p).reCalibration and valida- It comprises 4 parts: Part 1 addresses optical sensors (published in tion of re- 2014), Part 2 covers the domains of laser scanning e.g. LIDAR (pubmote sensing lished in 2016), while Part 3 addresses SAR/InSAR (published in imagery sen- 2018) and SONAR will be considered by Part 4 (to be published). sors and data
5 parts are considered for this standard, but only Part 1 Conceptual Addressing model has been published so far. It defines an address model along with definitions of concepts present in the model. 4
Previous sections (2 and 3) introduced existing BIM and ISO/TC 211 ontologies.
However, there is no previous studies that tackled or created any links between them.
This section lists several approaches addressing semantic links among BIM and GIS
application. Semantic Web Technologies link BIM and GIS domains through
uni/bidirectional integration [21], [22] or unification e.g. ontology covering both domains
[3]. However, the presented approaches focus only on building models and treat spe
cific use cases. [2] worked on automatically generating CityGML LoD3 (City
Geographic Markup Language is an open standardized data model and exchange format
that stores digital 3D models of cities and landscapes. The extendible international
standard for spatial data exchange is issued by the OGC and the ISO/TC211) building
models from IFC using Semantic Web Technology by mapping different entities and
properties (e.g. IfcRoof equivalent to RoofSurface). [3] semantically integrated IFC
and CityGML by conceiving the UBM ontology (Unified Building Model). For this
authors defined semantic relationships between IFC and CityGML schemas through
transformation rules (e.g. IfcBuilding is equivalent to UBMBuilding and
UBMBuilding is equivalent to _AbstractBuilding). [20] introduces BIM to GIS (B2G) mapping
by applying perspective definition (B2G PD), element mapping (B2G EM) and LoD
mapping (B2G LM) mechanisms. Where B2G PD concerns data extracting depending
on the use case, B2G EM defines the object mapping mechanism in terms of BIM to
GIS transformation of model elements. B2G LM concerns LoD definition and
mapping from BIM to GIS model. [21] integrates BIM and GIS by applying the following
steps: (1) ontology construction, (2) semantic integration through Graph Matching for
Ontologies (GMO), and finally (3) query execution. In addition, IFC ontology is
linked to other building ontologies, for example [24] presents mapping results
between BOT (Building Topology Ontology) and other building ontologies such as IFC
(e.g. bot:Site owl:equivalentClass ifc:IfcSite), SAREF4BLDG (SAREF Ontology for
Building) (e.g. bot:Building owl:equivalentClass saref4bldg:Building), and BRICK
(e.g. bot:Building owl:equivalentClass brick:Building). Following our analysis, we
noticed the following limitations in existing approaches: (1) the mappings defined are
mainly among IFC and a GIS application schema (CityGML, IndoorGML, etc.) and
do not address GIS standard ontologies; (2) unification or integration approaches only
link two ontologies (e.g. CityGML and IFC) and cannot be applied to link all existing
BIM and GIS ontologies; (3) most mapping concentrate only on IfcProductExtension
and the IFC concepts in the interoperability layer. Thus in the next section we'll
examine and define several semantic links among concepts from ifcOWL and standard GIS
ontologies. Our mapping concerns IFC4.1 (IFC4_ADD1 Ontology) which is the
lasted IFC ontology published by buildingSMART and ISO/TC 211 ontologies
[2529]
IFC4.1 = "http://ifcowl.openbimstandards.org/IFC4_ADD1#" 5.1
In this section we are mapping GIS abstraction schema
ISO1911:CoordinateSystemAxis.axisDirection GM_Curve represent sections of curvilinear geometry, and therefore share a number of operation signatures.
In this section we are mapping GIS application schema
IfcRoot is the most abstract and root class for all entity definitions that roots in the kernel or in subsequent layers of the IFC specification. It is therefore the common super type of all IFC entities, beside those defined in an IFC resource schema Further specializes the concepts of a (physical) product, i.e. a component likely to have a shape and a placement within the project context
Any It represents the set of all Feature classes which are feature
types Attribute Type
It recognizes all kinds of attributes: temporal, spatial geometry, spatial topology, data quality, generic metadata, and location.
The above mappings rely on concepts' and properties' definitions to instantiate equivalent relationships. However, those relations are not enough to achieve full semantic interoperability. In order to push our contribution further, we need to confront conceptual and semiotic heterogeneities which address differences in modelling, coverage and granularity representation between ontologies. We also need to implement structural ontology matching techniques that could enable a more robust mapping between BIM and GIS domains. Mapping BIM and GIS conceptual schema via ontologies will enable us to create data continuity between both domains, plug BIM model into any GIS application (e.g. CityGML, IndoorGML, LandInfra, etc.). Furthermore, the mapping is not limited to a specific use case and both domains must remain inde pendent from each other because no meta-model is conceived or taken as reference. The mapping between BIM and GIS enables horizontal federation in our approach [23]. However, our approach also comprises vertical federation and for reaching it, the next elements must be considered: (1) Definition of mediator ontologies which es tablish terminological equivalences among schemas. (2) Definition of complex semantic mappings: which require exchanges with business experts. (3) Implementation of a granular approach: the concept of granularity, seems intuitive and easy to implement, still the associated abstraction levels and perspectives must be specified [23].