Automatic Construction of Nanotechnology Ontology

Nanotechnologies – Vocabulary
Platform for Ontology Engineering and Evolution for Nanotechnology
AUTOMATIC CONSTRUCTION
OF NANOTECHNOLOGY
ONTOLOGY STANDARDS
23RD INTERNATIONAL CODATA CONFERENCE
“OPEN DATA AND INFORMATION FOR A CHANGING PLANET”
Academia Sinica, Taipei, Taiwan, 2012-10-28
AXEL PETER MUSTAD
NORDIC QUANTUM COMPUTING GROUP AS © 2012
Nordic Quantum Computing Group AS @ 20122012-10-28 1

Outline
q  Introduction (Motivation, Background, Objective, Scope)
q  Development of example nano carbon nomenclature and integration of
data in an ontology for nanomaterials
o  Nomenclature for NanoCarbon
o  Integration of physical/chemical properties and data in an OWL 2 ontology
for NanoCarbon
o  Ontology evaluation and further development
q  Ontology evolution process
o  Ontology learning
o  Ontology merging
o  Ontology updating
q  Platform for Ontology Engineering and Evolution for Nanotechnology
q  Project structure
q  Conclusions
23RD INTERNATIONAL CODATA CONFERENCE, ACADEMIA SINICA, TAIPEI, TAIWAN2012-10-28 2

Motivating factors on implementing IFT
q  EU's Digital Agenda for Europe has called for the development of
research infrastructures and e-Infrastructures, including for scientific
data, as data itself is becoming a fundamental infrastructure, resulting
in open access to the scientific data becomes more important.
q  Governments and industry increasingly engage in launching programs
for collaboration in research and development through use of an
emerging number of online databases, electronic journals and media,
social networks, etc.
q  Private and public stakeholders all over the world need to ensure that
every future research project funded has a clear plan on how to manage
the data it generates. Such plans should foster openness and economies
of scale, so that data results can be re-used many times rather than
duplicated.
23RD INTERNATIONAL CODATA CONFERENCE, ACADEMIA SINICA, TAIPEI, TAIWAN2012-10-28 3

Project Background
2012-10-28
q  A key concept in the Semantic Web initiative of the WWW consortium
is the notion of ontologies. In the nanotechnology field, there is still no
ontology standard in place.
23RD INTERNATIONAL CODATA CONFERENCE, ACADEMIA SINICA, TAIPEI, TAIWAN 4

Project Objective
q  To automate engineering and maintenance of integrated international
nanomaterials and nanotechnology ontology standards for improved
data integration and interoperability in order to bring big savings for
the industry and public sectors:
http://www.codata.org/Nanomaterials/A.%20Mustad.pdf
2012-10-28 23RD INTERNATIONAL CODATA CONFERENCE, ACADEMIA SINICA, TAIPEI, TAIWAN 5

Project Scope
q  To provide a collaborative environment www.iftglobal.org for financing,
research, standardization and innovation in nanotechnology and the
integration of advanced techniques of ontology design.

IFT Inaugural Focus
q  IFT is planned to initially evolve around four synergetic projects:
1.  Project for development of a platform for ontology engineering
and evolution for nanotechnology (Ontolution platform)
2.  Development of a systematic framework for nanosafety
ARACNOS (Advanced Risk Assessment and Categorization
Nanomaterials Ontology System)
3.  Development of a robust platform Ontology Based Data Access
(OBDA) and to demonstrate the potential of this technology by
deploying it in industry specific use cases and research clusters
4.  Harmonization of international standards, classifications and
national and global safety and compliance regulations for
nanotechnology NanoS (Nanotechnology Standards)

Ontology Standards for Nanotechnology
q  Ontologies are the central elements in any open e-infrastructure for
information exchange across disciplines, organizational and
geographical borders
q  In the nanotechnology research field there is still no ontology standard
in place, in spite of a strong need to coordinate and relate the diverse
research conducted in this interdisciplinary field
q  Ontologies are used to realise improved data integration and
interoperability and can potentially bring big savings for both the
industry and the public sectors
q  Realising this potential requires efficient ontology construction,
merging and evolution technologies

Ontology Standards for Nanotechnology, cont.
q  The integration of people and applications into more efficient
collaborative processes is central to the work on ontology engineering
and evolution
q  To make this happen, the applications and the information sources
must all understand the annotations with respect to a common
language, the ontology
q  This ontology is an explicit and commonly accepted terminology
standard that allows us to describe the content of data and services in a
machine-processable and unambiguous way

q  Nanomaterials, Nanotechnology, Nano- Safety, Standards, Policy, Regulation
o  Norwegian Academy of Science and Letters (ICSU), Standards Norway (ISO),
Norwegian National Technical Committee (IEC), Norwegian Ministry of Trade and
Industry, Norwegian Ministry of Defense, global network of research organisations
o  Outreach is a major task as an ontology depends on consensual contributions from a
greater number of international users. This does include participation to OECD, EU
Committees and ISO/CEN – in addition over 30 additional groups have endorsed
their membership in our advisory board and stakeholders panel, covering the
Americas, Oceania, Middle East, Africa and Asia. We will continue to invite further
members to ensure that our results will make a difference.
q  Computer Science and Information Technology
o  University of Oslo, University of Oxford, University of Manchester, Karlsruhe
Institute of Technology, Accenture (global)
q  Computers and Law
o  Clifford Chance LLP, Norwegian Research Center for Computers and Law (NRCCL,
University of Oslo), Simonsen Vogt Wiig
Partners, Stakeholders, External Advisory Committees

Project background
q  Used the following documents
o  ISO/IEC 80004 Nanotechnology Vocabulary Series (specified in OWL2)
o  Nomenclature sp2 carbon nanoforms (I. Suarez-Martinez, N. Grobert, Chr.
P. Ewels)
o  Informal standards, like the PAS, and scientific articles from the
nanotechnology domain
q  Ontology lifecycle model used
o  Both manual modeling tasks and automatic tool support
o  The ontology learning workbench (OWB) maps existing standards onto
OWL2 (Ontology Web Language) structures and suggests new ontology
structures from mining scientific domain documentation
o  Results from the OWB can be viewed, evaluated and modified with any
ontology editor (e.g., Protégé)
o  Whereas the OWB speeds up the analysis of domain documents, the
decisions on what to include in the final ontology still rests with the
ontology modelers (nano domain experts)

Difficulties with the use of ontologies
q  Ontologies are being developed independently for different
subdisciplines of nanotechnology
q  New ontological elements (terminologies and definitions) continuously
emerge from researchers and standardization groups
q  Some old elements become irrelevant or find more popular
corresponding synonyms
q  The dynamic nature of this process requires continuous update of
existing ontologies
q  Collaboration between distinct subdisciplines requires safe techniques
for merging of independently developed ontologies
Managing ontologies manually is not a simple task

Nomenclature for NanoCarbon
Nomenclature sp2 carbon nanoforms

Nomenclature for NanoCarbon, cont.
q  The nomenclature is developed in accordance with the guidelines in;
Nomenclature for sp2 carbon nanoforms
q  Exception: The term helical nanocones is used instead of screwed
stacked nanocones, as we think the latter is incorrect; screwed cones
cannot be exploded into single graphene cones – they concist of a single
layer wrapped around itself. (See next picture)

Nomenclature for NanoCarbon, cont.

Single Walled Carbon Nano Tubes
q  SWNT[R13/L100/M6/N5] = Single Walled Carbon Nano Tube with
Radius R = 13 nm, Length L = 100 nm and chiral vector (see next
picture) (M,N) = (6,5)
q  This specifies completely an open-ended tube without functionalized
surface or defects. Suggestions to alternative syntax are welcome; e.g.
SWNT_R{13}L{100}…etc

Chiral Vector

Multi-Walled Carbon Nanotubes
q  MWCNT[R34/L460/M7/N1/W5] = Carbon Nano Tube with # Walls W
= 5 where the outer wall has Radius R = 34 nm, Length L = 460 nm and
chiral vector (M,N)=(7,1).

Graphene Cones
q  Single Walled Carbon Nano Cones are called Graphene Cones in the
ontology, as they can be transformed from graphene by removing 1 to 5
sectors of disclination angle 60° and rejoining the resulting dangling
bonds.
q  GC[D240/R250] = Graphene Cone transformed from circular graphene
of Radius R=250 nm and total disclination angle D = 240° = 4 x 60°.

Integration of physical/chemical properties and data in
an ontology for NanoCarbon

Model Ontology for Nano Carbon

Representation of Nano Carbon entities. Below:
SWNCT with methyl-functionalized surface

Graphene Cone

Heterogeneities in NanoCarbon ontologies
q  Heterogeneity can be:
o  assembly of higher order structures not having same size with
disparate geometric arrangements,
o  that represents dissimilar level of perfection,
o  both static and dynamic.
q  Transferability to other systems / challenges:
o  Hierarchical structure is probably possible, but the shape of this is
likely to be material dependent.
o  Should also be compatible with other relevant nomenclature
      - Eg. crystallographic in the case of crystals can be formed
      - Chemical (eg, self-organizing forms)
      - Biological (eg, PDB database, gene sequences, etc.) when
such building blocks included in nanostructures.

Heterogeneities in NanoCarbon ontologies
q  Heterogeneities and structural defects can hardly be addressed through
the ontology alone.
q  Complete specification in these cases can however be achieved by a link
under Datatype Properties in the OWL2 interface to a molecular
file, e.g. in Protein Data Bank (PDB) format.
q  The molecular file defines the complex completely, and can be
displayed graphically. If possible, a standard naming convention is still
desirable for these cases.

Ontology evaluation and further development
q  Is the nomenclature convenient? Complete specification through
nomenclature alone seems infeasible due to e.g. the pletora of
topological variations at the open ends of tubes and cones.
q  Building model ontologies is a good method to test nomenclatures. For
example, integration of numerical data requires a more specific
nomenclature than qualitative properties.
q  Further development requires expert input on dependencies of
physical/chemical properties on structural details.

Project: Ontology Engineering and Evolution for
Nanotechnology (Ontolution platform)
q  A collaborative environment to support the use and development
of nanotechnology ontologies
o  To learn new ontological elements
•  highlighting emerging terms among researcher and standardization groups
•  identifying relations between them
o  To combine ontologies
•  helping to merge existing ontologies from different subdisciplines of
nanotechnology
•  locating overlapping and conflicting regions
o  To update ontologies
•  finding ontology elements that become out-of-date or are irrelevant for
researchers and standardization groups
•  identifying elements that should be renamed
•  identifying new elements that should be included

Ontology Learning
q  Goal: (semi-)automatically identify and extract relevant concepts and
relations from a given corpus to form an ontology
q  Documents are parsed; indexed and subject to statistical analyses for
concept extraction;
q  This produces statistical reports including
o  suggestion scores (how often has a candidate term been suggested),
and
o  the suggested neighborhood in an existing ontology

Ontology Merging
q  Some ontologies are developed in totally different scientific and
industrial contexts
q  However, the inter-disciplinary nature of the field requires
collaboration between academics and industrial partners
q  Safe merging of ontologies is important and tools are needed to
o  detect possible inconsistencies
o  assist in the repair of these inconsistencies

Merging of Ontologies
Ontology
Merging
• Merging ISO/IEC 80004 Vocabulary Series ontologies with other ontologies for nanotechnology
Indexing
• Split documents into text units
• Store each unit in a search index
Information
Retrieval
• Retrieve and concatenate textual paragraphs that are related to concepts in the basis ontology
• Stores the result set size for each concept
Keyword
extraction
• Extracting phrases and terms that are prominent in the concatenated texts
Evaluation
of results
• Export of results to an excel spread sheet for human inspection
Extending
ontology
• Incorporating the accepted suggestions into the ontology

Ontology Merging
NanoElectronics
NanoPhotonics
Merged

Ontology Updating
q  Ontologies evolve naturally
q  Most industries experience that ontologies are very dynamic and grow
over time
q  Manual update is complex; costly and time consuming
q  Document analysis tools can suggest the removal; renaming; or
inclusion of new terms in an ontology

Extending the ontology (1)

Extending the ontology (2)

Integrating these techniques
q  Learning, merging and updating ontologies are relevant for all cases of
nanotechnology
q  Industrial collaborators need a unified tool-supported platform
integrating all of these aspects of ontology design
q  Research collaborators can contribute with cutting-edge techniques and
benefit from tests in real-case scenarios
q  An iterative development process that gradually integrates the
techniques can mitigate risks and offer real benefits to all concerned

Project: Ontology Engineering and Evolution for
Nanotechnology
q  Goal:
o  To provide a collaborative environment for the development and use of
ontologies and the integration of advanced techniques for ontology design
o  To demonstrate ontology learning in the nanotechnology domain
q  Approach:
o  Development of a core basis and subsequent incorporation or more
sophisticated components
o  Use of existing ontologies in nanotechnology as a case study to support the
development
q  Ontology basis:
o  ISO/IEC TS 80004 Nanotechnology Vocabulary Series
o  IUPAC terminology http://goldbook.iupac.org/
o  Crystallographic/chemical/biological nomenclatures
o  Gene Ontology (GO) and other ontologies, e.g. NPO
q  Document corpus:
o  Documents on nanotechnology in relevant fields
o  Documents from ISO/TC 229, IEC/TC 113, CEN/TC 352, OECD WPMN

Platform architecture
Access
control

unit

Ontology
server

Processing

modules

Documents

Web
frontend
Users

Document

store

Ontology

store
Indices
Statistics
• Learning

• Merging

• Updating

• etc


Platform architecture, cont.

Project structure
WP2

WP4

WP3

WP0 - Management

WP1

WP5


Project structure, cont.
q  WP0 – Project management
o  NQCG
q  WP1 – Ontology Evolution Platform
o  NQCG
q  WP2 – Integrated Ontology Evolution Framework
o  Oxford/Manchester: Prof. Ian Horrocks and Prof. Uli Sattler
q  WP3 – Ontology Learning and Extraction
o  KIT: Prof. Rudi Studer
q  WP4 – Collaborative Ontology Engineering
o  Oxford/Manchester: Prof. Ian Horrocks and Prof. Uli Sattler
q  WP5 – Ontology Engineering for the Nanotechnology Domain
o  NQCG / NQCG coordinated projects (ARACNOS)

Project structure, cont.
q  WP1 – Ontology Evolution Platform
o  Specification, design and implementation of the platform
q  WP2 – Integrated Ontology Evolution Framework
o  Representation language and structures
q  WP3 – Ontology Learning and Extraction
o  Data acquisition, linguistic processing, ontology learning, trend-
detection
q  WP4 – Collaborative Ontology Engineering
o  Composition and decomposition framework for collaborative
engineering
q  WP5 – Ontology Engineering for the Nanotechnology Domain
o  Use case study and evaluation aspects

Integrated Ontology Evolution Framework
q  Integrated ontology representation language
o  extension of OWL 2 to handle information about
•  provenance
•  trust of ontology components (e.g., axioms and modules)
•  composition of an ontology
o  so as to allow
•  representation of uncertainties
•  a more powerful OWL 2 import and export mechanism

Ontology Learning and Extraction
q  Tools and techniques for detection of occurrences of ontology
components (classes, individual, etc) in natural language text
o  Data acquisition: document crawlers and data infrastructure for
textual knowledge
o  Linguistic processing
o  Ontology learning and mapping
o  Ontology-based trend detection
•  identify trends and emerging topics in newly published
documents

Collaborative Ontology Engineering
q  Development of methods that allow independent manipulation of parts
of ontologies with subsequent re-integration into the overall ontology
q  Ontology decomposition, version control and reconciliation
o  analysis of the logical modular structure of the ontologies
o  support for version management
o  support for conflict resolution

Conclusions
q  Ontology learning should be used as an effective tool in
o  Development of standard nanotechnology terminologies and nomenclature systems
o  Maintenance of standard nanotechnology terminologies and nomenclature systems
o  Harmonization of different standard nanotechnology terminologies and nomenclature
q  Collaborative ontology engineering platform can effectively assist in
o  Construct and maintain nomenclature systems for nanoscience and nanotechnology
o  Collaborative environment to support the use and development of nano ontologies
o  Internet platform for collaboration and cooperation in nano research and development
q  A broad representation of experts should take part in this work
—  ICSU, CODATA and Scientific Unions like IUPAC
—  Materials Research Societies
—  ISO/TC 229, CEN/TC 352, IEC/TC 113
—  OECD WPMN, OECD WPN
—  IP5 Foundation Projects (EPO, JPO, KIPO, SIPO, USPTO)
—  World Intellectual Property Organization (WIPO)
—  National academies of science and national standards development organizations
—  Organizations involved in developing classifications for nanotechnology
—  Leading scientific journals and publishers in relevant domains

Automatic Construction of Nanotechnology Ontology

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