10 th iccs/ gcc noordwijkerhout , the netherlands
DESCRIPTION
Automatic completion of COSHH risk assessment forms using semantic representation of GHS and CLP regulation. 10 th ICCS/ GCC Noordwijkerhout , The Netherlands. Mark I. Borkum and Jeremy G. Frey 5 June 2014. Overview. Problem Statement Methodology Results Discussion - PowerPoint PPT PresentationTRANSCRIPT
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Automatic completion of COSHH risk assessment forms using semantic representation of GHS and CLP regulation10th ICCS/GCCNoordwijkerhout, The Netherlands
Mark I. Borkum and Jeremy G. Frey5 June 2014
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Overview• Problem Statement
• Methodology
• Results
• Discussion
• Conclusion and Future Work
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Risk Assessment• Risk assessment is the determination of the risk
associated with a given hazard.
• In the context of chemistry research, risk assessment determines the risk associated with chemical hazards, e.g.,
– Explosive,– Flammable,– Carcinogenic,– etc.
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COSHH• The Control of Substances Hazardous to Health
(COSHH) Regulations 2002 are a UK statutory instrument.
• COSHH requires employers to protect their employees from the effects of exposure to hazardous chemical substances.
– (The main mechanism for this is risk assessment.)
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c/o SmartTea project
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COSHH Risk Assessment Methodology0. Plan scientific experiment.
1. Enumerate collection of chemical substances.
2. Discover relevant health and safety information.
3. Interpolate assessment form template.
c/o SmartTea project
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GHS• The Globally
Harmonized System for Classification and Labelling of Chemicals (GHS) is a UN system.
– Designed to supersede the various C&L systems that are currently in use around the world.
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CLP Regulation• In the EU, the GHS is implemented as the CLP
Regulation (see: Regulation (EC) No 1272/2008).
– Came into force in January 2009.– Mandatory from June 2015.
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Problem Statement• For humans, performing a risk assessment has two
main drawbacks:
– Less time spent performing experiments; and,– Potential for human error, e.g.,
• Incomplete enumeration of chemical substances;
• Use of incorrect information;• Transcription errors; and,• Tacit assumption of “common” elements.
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Let’s Automate!
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Automation Strategy• Given a description of a scientific experiment:
1. Discover and resolve all chemical identifiers;
2. Aggregate relevant health and safety information; and,
3. Feed the results through a template.
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Methodology
1. Formalise content of CLP Regulation document:
– Annex I Definitions– Annexes III—V Instances (C&L elements)– Annex VI Instances (classifications for approx.
3000 chemical substances and mixtures)
2. Implement Web application.
3. Profit!
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Resource Description Framework (RDF)
http://www.w3.org/TR/rdf11-primer/example-graph.jpg
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“ghs” Ontology
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“Flammable solid. Category 1”
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“EC (No) 007-001-01-2”
ammonia …%
H314
H400
hasHazardStatement hasHazardStatement
Danger
Warning
hasSignalWord hasSignalWord
Skin Corr. 1B
Aquatic Acute 1
hasHazardCategory hasHazardCategory
GHS09
GHS05
hasHazardPictogram hasHazardPictogram
Skin Corr.
Aquatic
hasHazardClass hasHazardClass
hasSubstance
STOT SE 3
hasHazardCategory
H335
hasHazardStatement
C ≥ 5%
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“(EC) No 001-001-00-9”
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Results• Dataset is available at:
– http://bit.ly/1fvDO5u
• Provides descriptions of approx. 3000 chemical substances and mixtures.
– However, on its own, the dataset is not very practical (for use in production environments).
– The critical observation is that, for many researchers, chemical substances are procured.
• In Autumn 2013, we approached a major supplier...
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“12540 FLUKA”@base <http://www.sigmaaldrich.com/catalog/product/> .@prefix chemaxiomprop: <http://www.polymerinformatics.com/ChemAxiom/ChemAxiomProp.owl#> .@prefix chemdomain: <http://www.polymerinformatics.com/ChemAxiom/ChemDomain.owl#> .@prefix ghs: <http://xmlns.com/ghs/0.1/> .@prefix sial: <http://www.sigmaaldrich.com/ns#> .
<fluka/12540> a chemdomain:NamedChemicalSpecies; chemdomain:hasIdentifier [ a sial:ChemicalNumber; chemdomain:hasValue "042802"], [ a chemdomain:Name; chemdomain:hasValue "Benzene"], [ a chemdomain:CASNumber; chemdomain:hasValue "71-43-2"], [ a chemdomain:SMILES; chemdomain:hasValue "c1ccccc1"], [ a chemdomain:MolecularFormula; chemdomain:hasValue "C6H6"]; ghs:hasHazardCategory <http://id.unece.org/ghs/hazard_categories/Flam_Liq_2>, <http://id.unece.org/ghs/hazard_categories/SPEC_RE_1>, <http://id.unece.org/ghs/hazard_categories/Skin_Irrit_2>, <http://id.unece.org/ghs/hazard_categories/Carc_1A>, <http://id.unece.org/ghs/hazard_categories/Asp_Tox_1>, <http://id.unece.org/ghs/hazard_categories/Eye_Irrit_2>, <http://id.unece.org/ghs/hazard_categories/Muta_1B> .
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Red square = Chemical substance
Orange square = Mixture part
Green square = PPE product
Blue square = GHS hazard category
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Demo
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List of Technologies• Web technologies:
– JavaScript Object Notation (JSON)
– Representational State Transfer (REST)
• Semantic Web technologies:
– Resource Description Framework (RDF)
– SPARQL Query Language for RDF (SPARQL)
– Web Ontology Language (OWL)
• Programming languages:
– JavaScript– Ruby
• Libraries:
– handlebars.js– jQuery / jQuery UI– RDF.rb– Sinatra
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Software Architecture
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1) Load Web application
“Generate” button
is disabled
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2) Search for products by name
Dynamic search
with auto-completio
n
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2) Search for products by name
Selected product is added to
list
Link to Sigma-Aldrich product page
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3) Accept terms and conditions
“Generate” button
is enabled
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One row per product
Editable text area for
“Nature of Process”
Editable text fields for “Physical Form” and “Quantity”
The University requires that
assessment forms are printed and
signed
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Toggle visibility of classificatio
n and labelling elements
Integration with
purchasing platform
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Sigma-Aldrich one page safety data
sheet (“one pager”)
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Discussion
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Stakeholders
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The Wrong Question• Who is to blame when the end-user obtains and
relies upon the “correct” answer to the “incorrect” question?
– User Can I drink this poison?– System Yes– User Is it safe to drink this poison?– System No
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Conclusion
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Conclusion• If you have high-quality, machine accessible
chemical information, automated completion of risk assessment forms templates is trivial.
• Need to mitigate risk of end-users relying on correct answers to incorrect questions.
– Use disclaimers– Capture and curate provenance information
• Try to collaborate with chemical manufacturers, suppliers, transporters, etc. They have large volumes of relevant data.
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Future Work• Approach UN/EC to host dataset.
• Enhanced input for service, either:
– List of “chemical identifier—phase—quantity” triples; or,
– Whole “plan” for scientific experiment.
• Full-blown Web application with template designer.
• RDF formalisation of Sigma-Aldrich “product catalog.”
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Acknowledgements• University of Southampton:
Doug Akins, Phil Jewell
• Sigma-Aldrich: Bo Jin, Jane Murray, Tom Pieper, Judith Pruss