The document discusses the relationship between building information modeling (BIM) and the semantic web. It provides an introduction to linked data and describes how semantic web technologies can be used to add contextual and background knowledge to BIM data, such as geographical, historical, and statistical information. It also addresses challenges around preserving and maintaining the evolution of linked BIM and architecture data on the semantic web.

1. The Semantic Web and the Building Domain –
an Introduction
Stefan Dietze
L3S Research Center
- GeoBim 2015, 11.12.2015 -
11/12/15 1Stefan Dietze

2. Recent work on Linked Data exploration/discovery/search
 Entity linking
 Entity & fact retrieval
 Human computation for data-intensive tasks
Research areas
 Web science, Information Retrieval, Semantic Web & Linked
Data, data & knowledge integration (mapping, classification,
interlinking)
 Application domains: Web archiving, Temporal Analytics,
TEL/Education, Smart Cities...
Some projects
Introduction
http://www.l3s.de/
11/12/15 2
 See also: http://purl.org/dietze
Stefan Dietze

3. 11/12/15 3Stefan Dietze
Semantic Web “in the wild”: Google Knowledge Graph

4. Google Knowledge Graph
 Structured factual knowledge
(eg DBpedia, Freebase etc)
 Represented in machine-
readable format „RDF“
(Resource Description
Framework, W3C standard)
 Used for disambiguating
queries, retrieving facts
dbp:United_States
http://dbpedia.org/resource/Cambridge_MA
dbp:W3C
country
cityOf
dbp:MIT
ru.dbp:Кембридж_(Массачусетс)
sameAs
headquarterOf
Semantic Web “in the wild”: Google Knowledge Graph
11/12/15 4Stefan Dietze

5. Semantic Web/Linked Data
 RDF datasets on the Web,
compliant with LD principles
(RDF, SPARQL, URIs)
 Linked Data graph/cloud:
graph of Web datasets (1000+
datasets & 100 billion RDF
statements)
dbp:United_States
http://dbpedia.org/resource/Cambridge_MA
dbp:W3C
country
cityOf
schema:City
typeOf
dbp:MIT
ru.dbp:Кембридж_(Массачусетс)
sameAs
headquarterOf
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geonames:4931972
sameAs
Semantic Web “in the wild”: Google Knowledge Graph

6. What is LD/SW good for?
Stefan Dietze 11/12/15
http://dbpedia.org/resource/Cambridge
Shared background knowledge
and semantics (data, schema) for
enrichment, disambiguation etc
(data consumer perspective)
 „HTTP-accessibility“
(SPARQL, URI-dereferencing)
 „Structure“ & „Semantics“
(=> shared/linked vocabularies)
 „Interlinked“
 „Persistent“
40688713.213379
http://sws.geonames.org/2653940/
dbpedia:UnitedKingdom
Established principles, W3C
standards & tools for data sharing
(data provider perspective)

7. Building Information Modeling and the Semantic Web?
11/12/15Stefan Dietze 7

8. 11/12/15Stefan Dietze 8
 RDF Vocabularies
 Contextual & background knowledge, e.g.:
 Geodata
 Historical information
 Statistical information
(infrastructure, traffic, environment etc)
Gadiraju, U., Kawase, R., Dietze, S., Extracting Architectural Patterns
from Web data, in Proceedings of 13th International Semantic Web
Conference (ISWC2014), Riva Del Garda, Italy, October 2014 [ Best
ISWC2014 Poster Award ]
Gadiraju, U., Dietze, S., Diaz-Aviles, E., Ranking Buildings and Mining
the Web for popular Architectural Patterns. ACM Web Science 2015
(WebSci2015), 28 June – 1 July, Oxford, United Kingdom.
Building Information Modeling and the Semantic Web!

9. …why are there so few datasets actually used?
 Date reuse and in-links focused on trusted „reference
graphs“ such as DBpedia (i.e. Wikipedia)
 Long tail of LD datasets which are neither reused nor linked
to (LOD Cloud alone consists of 300+ datasets)
 Explanations?
That’s awesome, but...
11/12/15
Hm,
really?
Stefan Dietze

10. Stefan Dietze
Linked Data is more diverse than we think
SPARQL Web-Querying Infrastructure: Ready for Action?,
Carlos Buil-Aranda, Aidan Hogan, Jürgen Umbrich Pierre-Yves
Vandenbussch, International Semantic Web Conference 2013,
(ISWC2013).
SPARQL endpoint availability over time [Buil-Aranda et al 2013]
Accessibility of datasets?
 Less than 50% of all SPARQL endpoints actually responsive
at given point of time
 “THE” SPARQL protocol? No, but many variants & subsets
 …
Shared vocabularies & schemas, but:
 …still very heterogeneous [d’Aquin, WebSci13]
 …data partially messy and not conformant
(RDFS, schemas) [HoganJWS2012]
 …even widely used reference datasets such as
DBpedia noisy [Paulheim2013, Demidova2014]
Co-occurence graph of data
types in 146 datasets: 144
Vocabularies, 588 highly
overlapping types, 719
Properties
Assessing the Educational Linked Data Landscape, D’Aquin, M., Adamou, A.,
Dietze, S., ACM Web Science 2013 (WebSci2013), Paris, France, May 2013.
Analyzing Relative Incompleteness of Movie Descriptions in the Web of Data:
A Case Study, Yuan, W., Demidova, E., Dietze, S., Zhu, X., International
Semantic Web Conference 2014 (ISWC2014)
An empirical survey of Linked Data conformance. Hogan, A., Umbrich, J.,
Harth, A., Cyganiak, R., Polleres, A., Decker., S., In the Journal of Web Semantics
14: pp. 14–44, 2012

11. <geoLatLong:52/13>
 Building Information Models and correlated (Linked) data evolve
 Dependencies: in RDF graphs (such as the LOD Cloud), „all“ nodes are connected
 Which datasets to preserve (only direct links or also more distant neighbours)?
(semantic relatedness, see [ESWC2013])
 Efficient & scalable preservation strategies
<dbp:Berlin(east)>
<dura:GDR Peoples Palace>
<dbp:Berlin>
Traffic statistics
(1986-1989)
Traffic statistics
(2013-…)
Energy efficiency
policies
What about data evolution? - BIM, Linked Data & preservation
11/12/15Stefan Dietze 11

12. DURAARK Consortium
http://www.duraark.eu
Goals
 Semantic enrichment & preservation of architecture data
(3D models, metadata, Web & Linked Data)
“DURAARK: Durable Architectural Knowledge”
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13. Thank you!
WWW
 http://duraark.eu
 http://data.duraark.eu
 http://stefandietze.net
REFERENCES
Extracting Architectural Patterns from Web data, Gadiraju, U., Kawase, R., Dietze, S., in Proceedings of 13th International Semantic Web
Conference (ISWC2014), Riva Del Garda, Italy, October 2014 [ Best ISWC2014 Poster Award ]
Ranking Buildings and Mining the Web for popular Architectural Patterns, Gadiraju, U., Dietze, S., Diaz-Aviles, E., ACM Web Science 2015
(WebSci2015), 28 June – 1 July, Oxford, United Kingdom.
Assessing the Educational Linked Data Landscape, D’Aquin, M., Adamou, A., Dietze, S., ACM Web Science 2013 (WebSci2013), Paris, France,
May 2013.
Analyzing Relative Incompleteness of Movie Descriptions in the Web of Data: A Case Study, Yuan, W., Demidova, E., Dietze, S., Zhu, X.,
International Semantic Web Conference 2014 (ISWC2014)
Generating structured Profiles of Linked Data Graphs, Fetahu, B; Dietze, S., d’Aquin, M., Nunes, B.P., ISWC2013 – 12th International
Semantic Web Conference;
Type Inference on Noisy RDF Data, Paulheim H., Bizer, C. Semantic Web – ISWC 2013, Lecture Notes in Computer Science Volume 8218,
2013, pp 510-525
An empirical survey of Linked Data conformance. Hogan, A., Umbrich, J., Harth, A., Cyganiak, R., Polleres, A., Decker., S., In the Journal of
Web Semantics 14: pp. 14–44, 2012
SPARQL Web-Querying Infrastructure: Ready for Action?, Carlos Buil-Aranda, Aidan Hogan, Jürgen Umbrich Pierre-Yves Vandenbussch,
International Semantic Web Conference 2013, (ISWC2013).
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