Session 2.4 virtual construction (v-con) and top braid cde – a linked data/semantic asset management solution

Virtual
Construc.on
(V-‐Con)
and

TopBraid
CDE
–
a
linked
data/seman.c

asset
management
solu.on

David
Price

TopQuadrant
Limited

dprice@topquadrant.com

© Copyright 2015 TopQuadrant Inc. Slide 2
Seman.cs
2017
Agenda

§  Introduc.on
to
TopQuadrant

§  Ini.al
Situa.on
–
Na.onal
Road
Authori.es

§  Approach
and
IT
solu.on

– TopBraid
EDG

– Virtual
Construc.on
(V-‐Con)
project

– TopBraid
Common
Data
Environment
(CDE)

§  Conclusions

INTRODUCTION
TO
TOPQUADRANT

Who
is
TopQuadrant?

§  a
leading
seman.c
data
integra.on
company,
SME
with
a
big

footprint
in
the
Seman.c/Linked
Data
community

–  UK
subsidiary
TopQuadrant
Limited
ini.ated
in
2010

§  commi[ed
to
a
standards-‐based
approach
focusing
on

prac.cal
applica.on
of
seman.c
technology,
W3C
member

–  From
2001
–
2010,
ﬁrst
a
Services
Company,
then
a
Tools/Pla_orm/
Technology
Transfer
Company

–  Since
2010,
a
Business
Solu.ons
Company
1)
ﬁrst
for
collabora.ve

vocabulary
development;
and
then
2)
for
enterprise
metadata
and

reference
data
management

–  In
2017,
star.ng
with

BIM,
engineering
asset
data

TopQuadrant
Business

§  TopQuadrant
customers
are
from
a
range
of
industries

Background

§  Na.onal
Road
Authori.es
(NRA)

–  Manage
road
network
as
an
asset

–  Create
new
road
and
road
maintenance
projects

–  Project
work
is
performed
by
construc.on
companies
but

approved
by
NRA
project
organisa.on

§  Key
data
areas
(in
many
formats)

–  Building
Informa.on
Model
(BIM)
data
(e.g.
3D
design)

–  Geographic
informa.on
system
(GIS)
data

–  Interna.onal,
Country,
Authority/Company
and
Project

level
data
deﬁni.ons,
including
large
Object
Type
Libraries

NRA
Asset
Management

Organisa.on

Construc.on

Company

NRA
Project

Organisa.on

… And Other Governments
Have Digital/BIM Strategies

V-‐Con
Project

§  The
Dutch
and
Swedish
NRAs
jointly
sponsored
an

EU
Pre-‐commercial
R&D
project
to
improve
data

interoperability
and
reuse

§  Based
in
standards
and
standard
formats

§  Taking
advantage
of
linked
data
and
seman.c

technologies
for
cross-‐discipline
linking,
enrichment,

and
conversion

§  Desire
from
NRAs
to
help
build
a
market
for
tools
to

support
their
needs

NRA
Asset
Management

Organisa.on

Construc.on

Company

NRA
Project

Organisa.on

V-‐Con
Key
Technical
Challenges

§  TC1:
Support
ontology-‐based
handling
of
datasets

§  TC2:
Support
handling
datasets
in
non-‐linked
data

formats

§  TC3:
Manage
and
store
data
structures
and
datasets

§  TC4:
Connect
datasets
from
diﬀerent
domains

§  TC5:
View
(connected)
informa.on

§  TC6:
Ensure
system
quality

§  TC7:
Ensure
a
future
proof
system

APPROACH
AND
IT-‐SOLUTION

V-‐Con:
Lightweight
data
interoperability

Leave
Deep
technical

data
in
context
form,

conver.ng
only

overlapping
scope

into
common
form

Use
reasoners,
rule

engines
and
humans
to

make
links
between

diﬀerent
datasets

across
disciplines

Our Layered V-Con Solution Strategy

TopBraid
Enterprise
Solu.ons

IDE
Search / Content Enrichment
through the use of
Taxonomies and Ontologies
Data Governance: Reference Data
Management / Metadata
Management / Data Lineage/EA

Data

Layer

TopBraid
Common
Data
Environment

Components from TopBraid Solutions
New Components specific to Eng Asset Mgmt
Support for standards (e.g. IFC STEP File)
A Configuration of CDE

TopBraid
Pla_orm
Solu.on
Engine

EDG
as
a
Technology
Pla_orm

Capabili.es
for
all
EDG
assets

•  Role-‐based
access
control

•  Audit
trail
of
change
history

•  Sandbox
working
copies

•  Mul.-‐lingual
content

•  SPIN
Rules
for
enrichment

•  Data
quality
rules

–  With
valida.on,
using
SPIN
and

SHACL

•  Event
no.fica.ons

•  Tasks
and
comments
(op.onal

integra.on
with
JIRA)

•  Traceability
within
and
across

different
asset
types
e.g.,:

–  Glossary
terms
to
data
elements
to

reference
data
to
applica.ons
to

business
processes
to
…

•  Custom
extensions

•  Configurable
dashboards

•  Imports/Exports

–  Some
common,
some
asset-‐specific

•  Search
(parametric,
faceted)

–  Within
and
across
assets

•  Visualiza.on

–  Varies
per
asset
e.g.,
UML-‐like
class

diagrams,
NeighborGram

•  Configurable
web
services

•  Model-‐driven
edit
widgets

–  Model
driven
auto-‐complete,
in-‐line

edi.ng,
specialized
widgets
and

forms
for
OWL
Manchester
syntax,

SPIN
rules
and
SHACL
shapes

•  Extensive
configurable
metadata

at
the
asset
level

–  E.g.,
where
used,
version
number,

etc.

Role-‐based
Access
Control

§  Assign
users
diﬀerent
roles
for
using
the
system
at

various
levels
of
authority:

–  Manager

–  Editor

–  Viewer

§  System-‐wide
read-‐only
role
is
also
available
to

support
search
and/or
comment-‐only
use
cases

Manager Editor Viewer

Built-‐in
Review
Workﬂow

Production Version
Working Copy
Working Copy in
Review*
Rework?
Archive/Delete
create
approve
and publish
make changes
freeze for
review
reject
unfreeze
No
Yes
Review* = Comparison Report, View
Change History, Bespoke reports
Solves asset “versioning”
requirements in an interesting way.

Edit
Working
Copy
and
Show
History

View
Change

§  Can
commit
or
reverted
individual
changes

W3C
Shapes
Constraint
Language

Severity:
Info,
Warning,

Viola.on

Min
and
max
count

integer,
max
can
be
zero

Further
constraint
value

type

Business
user
can
deﬁne

SHACL
Data
Constraints
in

a
Web
form

Neighborgram
Visualisa.on

§  A
navigable
graph
visualisa.on

Requirements
&
Glossary
Linked

§  Glossaries:

terms
and
deﬁni.ons
(SKOS)

§  Requirements:
requirement
deﬁni.ons,
structure,

kinds
and
rela.ons

Link
to
Glossary
term

“Ontology”

Links
to
sub-‐requirements

TC1.1,
TC1.2

CDE
Conﬁgura.ons
and
Extensions

TopBraid
CDE
Solu.on
for
V-‐Con

Ontology-‐based
Datasets

§  Ontology
–
collabora.ve
development
of
ontologies
(EDG)

§  Dataset
–
based
on
any
ontology

§  Dataset
IFC
OWL
–
based
on
IFC
OWL
ontology
and
supports

IFC
STEP
import/export

§  Dataset
CityGML
XML
–
based
on
generated
GityGML
XML

schema
“proxy”
ontology

–  Uploaded
XML
ﬁles
are
read-‐only
and
UI
is
showing
XML
data
as

triples

–  Use
Conversion
Rule
(SPIN)
to
make
triples
from
read-‐only
XML
if

required

§  Dataset
XML
XSD-‐based
–
based
on
any
“proxy”
ontology

–  Uploaded
XML
ﬁles
are
read-‐only

Import
Mul.ple
Data
Formats

Dataset
XML
–
LandXML
1.2
example

§  LandXML
data
can
be
linked
to
IFC
OWL
data,
for

example

CityGML
importer

§  Visualisa.on
of
an
X3D
ﬁle
generated
from
a
CityGML
ﬁle

–  This
is
an
ini.al
implementa.on,
improvements
to
come

–  Similar
capability
in-‐development
for
IFC
STEP
3D
geometry

Rotated in browser

IFC
STEP
converted
to
RDF
and
X3D.
In
browser,
selec.ng

3D
item
shows
related
RDF
from
the
database.

If
IFC
and
CityGML
data
is
“enriched”

IFC
OWL
instance
set
sameAs

CityGML
XML
instance
via
rules-‐
driven
enrichment
(SPIN
rules

in
this
case)

From
3D
vis
=>
IFC
=>
CityGML

User
found
CityGML
data
about
a
thing
by
star.ng
in
an
IFC-‐
based
3D
visualisa.on
of
that
thing

Enrichment
and
Conversion

§  Conversion
Rule
Sets:
supports
“beyond
OWL”
conversion

between
source
and
target
datasets
using:

–  W3C
member
submission
SPIN
Rules
language

–  Rules
wri[en
by
power
user
in
TopBraid
Composer,
then
deployed
to

the
server
for
use
by
end
users

–  SPIN
Rules
can
be
managed
as
separate
files
and
a
Conversion
Rule
Set

can
include
more
than
one
SPIN
rules
file

§  Support
for
DL
reasoner
for
enrichment
defined
in
Alignment

Ontologies

Conversion
Rule
Set
(CRS)

Selected
SPIN
Rules
ﬁle

deployed
to
CDE
server.

CRS
can
“convert”
or
“enrich”

§  Conversion:
translate
data
in
source
dataset
to
data
in
target

dataset
based
on
diﬀerent
ontology

§  Enrichment:
add
new
data
to
current
dataset
(e.g
OWL

sameAs
linking
asser.ons
in
an
alignment
dataset)

Data
Transforma.on
via
Conversion
Rules

1
–
Select
source
Dataset
2
-‐
Select
Conversion
Rule
Set

4
-‐
Select
“Run
Conversion”
bu[on
and

generated
triples
are
stored
in
current

(i.e.
target)
Dataset,
where
you
should

have
“Included”
the
target
Ontology

3
–
Check
and
to
Run
OWL
RL
or
OWL

DL
inferences
as
a
ﬁrst
step
in
the

conversion.

Run
Enrichment

3
-‐
Select
“Run
Enrichment”
bu[on
and

generated
triples
are
stored
in
current

dataset

1
-‐
Select
Conversion
Rule
Set

2
–
Check
and
to
Run
OWL
RL
or
OWL

DL
inferences
as
a
ﬁrst
step
in
the

enrichment.

Data
Valida.on

§  For
engineering
data,
the
“open
world

assump.on”
causes
problems

§  The
W3C
Shapes
Constraint
Language
(SHACL)

closes
the
world
allowing
“full”
data
valida.on

– SHACL
is
now
a
W3C
Recommenda.on

– TopQuadrant
was
instrumental
in
its
development

– Built-‐in
constraint
vocabulary
plus
“SPARQL

query”
constraints
for
complex
cases

Data
Valida.on
Constraints

Severity:
Info,
Warning,

Viola.on

Min
and
max
count

integer,
max
can
be
zero

Further
constraint
value

type

Business
user
can
deﬁne

SHACL
Data
Constraints
in

a
Web
form

Example
property
constraint

§  Construc.on
body
layer
thickness
value
is

required
to
be
from
50
to
100

Edi.ng
user
warned
of
viola.on

Report
can
be
generated
later

Run
report

Get
report

SUCCESS
CRITERIA
FOR
/
BENEFIT

OF
THE
SEMANTIC
SOLUTION

Success
Criteria

§  NRA-‐deﬁned
Test
Scenarios
–
an
example

Navigated
3D
view
to
IFC
to
CityGML

CityGML
instance
is
sameAs

IFC
instance

Cross-‐discipline
capability
is
a
signiﬁcant
beneﬁt
of
a
linked
data/
seman.c
solu.on.

PROSPECTS
AND

RECOMMENDATIONS

End-‐of-‐project
Status

§  Barriers
to
wide
use
of
Linked/Seman.c
Data
coming
down
–

graph
databases
far
more
common
today

§  Gaps
in
seman.c
technology
being
ﬁlled
(e.g
SHACL)

§  Cross-‐discipline
characteris.c
of
Building
&
Construc.on
and

Infrastructure
make
them
good
industries
where
Linked
Data/
Seman.cs
can
be
important

§  IFC
OWL
approach
adds
value
to
exis.ng
data
and
IFC-‐
conforming
applica.ons

–  Encouraging
support
for
buildingSmart
Linked
Data
WG

§  V-‐Con
project
was
a
good
example
of
ﬁlling
gaps
and
pushing

at
boundaries

Informa.on
Modelling
&
Management,

Common
Data
Environment

From
London
Transport

Conference
Oct
2016
–

This
is
where
TopBraid
CDE

can
ﬁt

TopBraid
CDE
Summary
-‐
business

§  TopBraid
CDE
is
a
new,
standards-‐based
entry
into
the
BIM

market

–  a
lightweight,
browser-‐based
solu.on
with
a
lot
of
capability
that
is

highly
ﬂexible
and
extensible

–  applicable
in
smaller
organisa.ons
in
the
supply
chain
too

–  easy
to
use
as
UI
is
designed
for
business
users

–  power
users
handle
any
complex
tasks
using
the
industry-‐leading

TopBraid
Composer
desktop
app,
then
deploy
to
server
for
business

user
usage

–  Being
standards-‐based
means
less
lock-‐in
and
means
data
useful

outside
the
silo
in
which
it
was
created

–  Easily
deployed
in
cloud
or
in-‐house,
on
large
and
small
machines

depending
on
customer
scaling
requirements

TopBraid
CDE
Summary
–
technical

§  TopBraid
CDE:

–  Supports
informa.on
modeling

–  Supports
common
data
and
linking
across
datasets

–  Supports
mul.ple
data
formats
(OWL,
XML
Schema/XML,
EXPRESS/
STEP,
spreadsheets)

–  Supports
mul.ple
possibili.es
for
ontology
and
data
visualisa.on

–  Supports
valida.on,
repor.ng,
enrichment
and
conversion
using

standard
SPARQL,
our
SPIN
extension,
and
new
standard
SHACL

–  Is
based
on
graph
database
technology

Session 2.4 virtual construction (v-con) and top braid cde – a linked data/semantic asset management solution

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