An Overview of work on the Earthster Core Ontology, a core ontology for Life Cycle Analysis.

1. Earthster Core Ontology A core domain ontology for Life Cycle Assessment

2. Introductions Earthster is a project, led by Greg Norris, to provide free open source solutions supporting Life Cycle Analysis – that is evaluating the environmental and social impacts of products. Brian McBride is a consultant, ontologist, developer and general dogsbody who has worked on semantic web technologies since 2000. He was co-chair of the RDFCore WG in W3C and the initiating developer of the Jena Java library. Epimorphics is a Semantic Web startup based in the UK specialising in Linked Open Data. http://www.earthster.org/ http://www.epimorphics.com/

3. Menu A little bit about LCA Why semantic web? A fragment of ECO A sense of the rest The ECO-system A little bit on method ERF – an application Wrapup Season to taste with questions and discussion anytime

4. Life Cycle Assessment What is a product’s impact on the environment and society? In production aka cradle to gate? In use – total lifecyle?

6. Define the goals of the assessment

7. Analyse your supply chain

8. Create an inventory of emissions and aggregated along the supply chain

9. Assess the impact of those effects on issues of interest e.g. global warming, human health, ...

11. Why Semantic Web? Effects Publish the data on the web makes it most freely available – and that is what the semantic web is for Linking to other data sources – that is what Linked Open Data is for Find an alternative pesticide that targets the same class of organism Link to Good Relations data Operations Interoperability Harmonize competing systems by defining a common conceptual model Harmonize competing vocabularies by defining common reference data LCA research is ongoing – the data required is changing over time Finding the best available data

12. ECO: A Core Domain Ontology Aim is to offer a vocabulary for core concepts in LCA Not lists of instances Instances are present if they are a logical necessity of the concept Core ontology changes when core concepts change not when a new instance is invented Trying to express the consensus conceptual model for the field Reverse engineering existing file formats and database schemas

14. Allows multiple inconsistent descriptions of the process with a contradiction

16. Key feature is that it is aggregatable

17. Abstraction of product flow, waste flow, elementary flow, land use, wages paid, ...

19. Adds the notion of an uncertainty distribution – not part of SUMO

20. There is a separate ontology of uncertainty distributions – they are not a logical necessity of the concept of an uncertainty distribution

21. What about the Zero uncertainty distribution – that is a logical necessityQuantity Effect magnitude units Uncertainty distribution

24. Should we have allowed that extension:

25. giving in to the temptation to ‘improve’ the current shared conceptual model

26. done in a way that extends the legacy and does not contradict it

28. Other Parts OWL Full axioms Mostly in OWL DL – only a few FULL axioms Bridging ontologies To SUMO, FOAF, TIME, GoodRelations, ... Mimimize ontological commitment Extension ontologies FASC, distributions, file formats, attributes, impact assessments, flow reference data, ...

30. Gentle introduction

31. for ontologists

32. Defines scope and purpose

33. Document:

34. principles

35. examples

36. maybe non-examples

37. identity criteria

38. Good discipline to write down design choices and reasons

40. ring 1 : model in detail

41. ring 2 : model lightly

42. ring 3 : aiming for no discontinuities

44. Earthster Reference Flows Problem: Current databases and impact assessment methods use different vocabularies Relevant effects get missed from impact assessments Duplicate effects get ‘invented’ Hard: if the method specifies paraquat ion and you have numbers for paraquat Are they equivalent? Is there a fudge factor?

45. Replace lists with structure Currently LCA databases work with lists of elementary flows and give them Ids ECO has structure for these elementary flows: Flowable Energy – use source + density to identify Substance Chemical – use CAS numbers to identify Isoptopes – use CAS number + atomic weight Ores – use mix of substances Other – adhoclist – bring in a structure if one emerges Compartment taxonomy Time frame These form a taxonomy Using Skos rather than class structure to stay flexible With an extensible set of modifiers

46. Aim ... Much smaller lists to manage Manage modifier attributes instead Ability to extend the list of flows without ambiguity Automated matching of legacy flows to the structure Involve the community Is there a fudge factor? Publish reference data on the web Crowd source corrections/updates Relate different flows in different vocabularies through subsumption Offers a shared resource for defining a vocabulary – that allows competition with interoperability

47. Summary Making better decisions from a sustainability perspective – that’s an important problem Open sharing of information enables market pressure to operate Field Somewhat fragmented Evolving Information rich – the value is in the data Codifiable knowledge Links to other data has economic value Good space for using Semantic Web technology

48. Image Attributions Hot, flickr:judepics Industry, flickr:hans s Crushed by the Wheels of Industry,flikr: ProblemKind Hong Kong supermarket in Chinatown,flikr: vauvau Crushed by the wheels of Industry 2, flikr:Problemkind Barn Owl, flickr:AviaVenefica

49. Image Attributions Offshore Windfarm Turbine, flicr:phault Macro Leaf, flickr:seeks2dream Spaghetti al burro, flickr:cesarastudillo Stop, flickr:active metabolite On Target, flickr:viZZual.com

50. Questions? Thoughts? Observations?