A SPARQL query engine for binary-formatted IFC building models

Abstract To date, widely implemented and full-featured query languages for building models in their native exchange formats do not exist. While interesting proposals exist for querying Industry Foundation Classes (IFC) models, their functionality is often incomplete and their semantics not precisely defined. With the introduction of the ifcOWL ontology as an equivalent to the IFC schema in the Web Ontology Language (OWL), an option to represent such models in RDF (Resource Description Framework, a general information modeling method) is provided, and such models can be queried using SPARQL (SPARQL Protocol and RDF Query Language). The size of data sets in complex building projects, however, renders the use of clear-text encoded RDF infeasible in many cases. A SPARQL implementation, compatible with ifcOWL, is proposed, directly atop a standardized binary serialization format for IFC building models. This novel format is the binary equivalent of traditional IFC serialization formats but with more compact storage and less overhead than the graph serialization in RDF. The format is based on ISO 10303-26 and relies on an open standard for organizing large amounts of data: Hierarchical Data Format version 5 (HDF5). Due to hierarchical partitioning and fixed-length records, only small subsets of the data are read to answer queries, improving efficiency. A prototypical implementation of the query engine is provided in the Python programming language. In several realistic use cases, the proposed system performs equivalent to or better than the state of the art in SPARQL querying on building models. For large datasets, the proposed storage format results in files that are 2–3 times smaller than the current, most concise, RDF databases while offering a platform-neutral, containerized exchange file.

[1]  Dave Reynolds,et al.  Efficient RDF Storage and Retrieval in Jena2 , 2003, SWDB.

[2]  Seppo Törmä,et al.  Semantic Linking of Building Information Models , 2013, 2013 IEEE Seventh International Conference on Semantic Computing.

[3]  Jyrki Oraskari,et al.  RDF-based signature algorithms for computing differences of IFC models , 2015 .

[4]  Marcelo Arenas,et al.  Semantics and complexity of SPARQL , 2006, TODS.

[5]  Ling Liu,et al.  Scaling Queries over Big RDF Graphs with Semantic Hash Partitioning , 2013, Proc. VLDB Endow..

[6]  Junghoo Cho,et al.  A fast regular expression indexing engine , 2002, Proceedings 18th International Conference on Data Engineering.

[7]  Ana Roxin,et al.  IfcWoD, Semantically Adapting IFC Model Relations into OWL Properties , 2015, ArXiv.

[8]  Thomas Krijnen,et al.  An IFC schema extension and binary serialization format to efficiently integrate point cloud data into building models , 2017, Adv. Eng. Informatics.

[9]  Abraham Bernstein,et al.  OptARQ: A SPARQL Optimization Approach based on Triple Pattern Selectivity Estimation , 2007 .

[10]  Nigel Shadbolt,et al.  SPARQL Query Processing with Conventional Relational Database Systems , 2005, WISE Workshops.

[11]  Abraham Bernstein,et al.  Hexastore: sextuple indexing for semantic web data management , 2008, Proc. VLDB Endow..

[12]  Pieter Pauwels,et al.  Enhancing the ifcOWL ontology with an alternative representation for geometric data , 2017 .

[13]  Diego Calvanese,et al.  Ontop: Answering SPARQL queries over relational databases , 2016, Semantic Web.

[14]  Heeseok Lee Justifying database normalization: a cost/benefit model , 1995 .

[15]  Pieter Pauwels,et al.  Semantic web technologies in AEC industry: A literature overview , 2017 .

[16]  Donald Meagher,et al.  Geometric modeling using octree encoding , 1982, Comput. Graph. Image Process..

[17]  Jakob Beetz,et al.  BIMQL - An open query language for building information models , 2013, Adv. Eng. Informatics.

[18]  Gregory Piatetsky-Shapiro,et al.  Accurate estimation of the number of tuples satisfying a condition , 1984, SIGMOD '84.

[19]  André Borrmann,et al.  Processing of Topological BIM Queries using Boundary Representation Based Methods , 2014, Adv. Eng. Informatics.

[20]  Tf Thomas Krijnen,et al.  Methodologies for requirement checking on building models:a technology overview , 2016 .

[21]  Thierry Bertin-Mahieux,et al.  The Million Song Dataset , 2011, ISMIR.

[22]  Axel Polleres,et al.  Binary RDF representation for publication and exchange (HDT) , 2013, J. Web Semant..

[23]  Konstantina Bereta,et al.  Ontop of Geospatial Databases , 2016, SEMWEB.

[24]  Ana Roxin,et al.  SWRL rule-selection methodology for ontology interoperability , 2016, Data Knowl. Eng..

[25]  Goetz Graefe,et al.  Data compression and database performance , 1991, [Proceedings] 1991 Symposium on Applied Computing.

[26]  Ana Roxin,et al.  FOWLA, A Federated Architecture for Ontologies , 2015, RuleML.

[27]  Mustafa Alshawi,et al.  Exploring how information exchanges can be enhanced through cloud BIM , 2012 .

[28]  Sisi Zlatanova,et al.  Interoperable data models for infrastructural artefacts : a novel IFC extension method using RDF vocabularies exemplified with quay wall structures for harbors , 2014 .

[29]  Ulf Leser,et al.  Querying Distributed RDF Data Sources with SPARQL , 2008, ESWC.

[30]  Jakob Beetz,et al.  BIMSERVER.Org – An Open Source IFC Model Server , 2010 .

[31]  Dave Reynolds,et al.  SPARQL basic graph pattern optimization using selectivity estimation , 2008, WWW.

[32]  Filip Biljecki,et al.  Towards an integration of GIS and BIM data : what are the geometric and topological issues? , 2017 .

[33]  Tf Thomas Krijnen,et al.  Efficient binary serialization of IFC models using HDF5 , 2016 .

[34]  Daniel J. Abadi,et al.  Scalable Semantic Web Data Management Using Vertical Partitioning , 2007, VLDB.

[35]  Michela Bertolotto,et al.  A spatio-temporal index for aerial full waveform laser scanning data , 2018 .

[36]  Ana Roxin,et al.  A performance benchmark over semantic rule checking approaches in construction industry , 2017, Adv. Eng. Informatics.

[37]  Tamer E. El-Diraby,et al.  BIM-based collaborative design and socio-technical analytics of green buildings , 2017 .

[38]  Dave Kolas,et al.  Enabling the geospatial Semantic Web with Parliament and GeoSPARQL , 2012, Semantic Web.

[39]  Gerhard Weikum,et al.  RDF-3X: a RISC-style engine for RDF , 2008, Proc. VLDB Endow..

[40]  Yehia El-khatib,et al.  Web technologies for environmental Big Data , 2015, Environ. Model. Softw..

[41]  Yaron Kanza,et al.  D2RQ/update: updating relational data via virtual RDF , 2012, WWW.

[42]  Jürgen Döllner,et al.  High-level web service for 3D building information visualization and analysis , 2007, GIS.

[43]  Pieter Pauwels,et al.  EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology , 2016 .