FOR FURTHER INFORMATION REFERENCES [1] T. Lebo, S. Sahoo, D.L. McGuinness, PROV-O: The PROV Ontology, (2013). <http://www.w3.org/TR/prov-o/> [2] <https://github.com/CSIRO-LW-LD/prov/tree/master/real-things> [3] S J D Cox, Ontology for observations and sampling features, with alignments to existing models, Sem. Web J. (in press) [4] S J D Cox & N J Car, PROV and Real Things. MODSIM 2015 <https://www.researchgate.net/publication/284180374_PROV_and_Real_Things>. ACKNOWLEDGEMENTS Thanks to Keith Sircombe of Geoscience Australia for providing the story upon which this example is based. A second example based on identification of an insect specimen was provided by Catherine Car of the Western Australian Museum, is documented in [4] and is also available from GitHub [2]. Provenance of things Flexibility required While laboratory notebooks are used for private record-keeping, and laboratory information systems (LIMS) on a facility basis, this data is not generally published. Workflows are often scoped to a lab, or an instrument. New procedures and workflows are frequent, so formalization of the description of sample preparation and observations must be both rigorous and flexible. Geochemistry observations typically follow a complex specimen preparation process after field sampling. Details of this are required to support assessment of the reliability of the data produced, and to ensure reproducibility. We have applied W3C PROV [1] in describing complex retrieval, processing and observation processes associated with physical specimens. Describing sample preparation and observation workflows using PROV-O Simon J D Cox, Nicholas J Car LAND AND WATER Simon J D Cox e simon.cox@csiro.au w www.csiro.au/research/lwf Summary PROV-O provides a rigorous yet flexible tool for recording the workflow associated with sample preparation, with intermediate and final specimens used in observations, and the observation results themselves, to be linked back to the sample retrieved in the field. This complements the IGSN system, which focuses on registration of field samples. Core PROV model The core W3C PROV model [1] (shown above) distinguishes entities, agents and activities. Its design was primarily conditioned by stories around information resources (datasets, papers, reports). Here we extend its application to non-information assets. Application to geochemistry A provenance trace for a geochemistry workflow provided by Geoscience Australia is shown graphically (shown at left), with the RDF representation available from GitHub [2]. Note that both people and machines are modelled as ‘agents’ – this follows the precedent of W3C PROV which has a specialization for ‘Software agents’. Registers of agents should be established, allowing them to be referred to using stable URIs. In an OWL implementation of the O&M Standard that has recently been developed [3], the Specimen class is explicitly sub-classed from prov:Entity in order to utilize the capability illustrated here (see above). PROV supports a comprehensive trace of predecessor entities and transformations at any level of detail. Tony Jones Maham Aziz Amelia Davis Michelle Rouse Hammer: b45 SieveStack :80-200 CPV:2015-07-23 Viz:2015-08-02 Seiving:2015-07-18 Grinding:2015-07- 18/6 Splitting:2015-04- 18/9 FieldSampling:2015- 03-25/47 LF-09/2-gt- 80 81.6% CO3 75% CO3 LF-09/2- pulp LF-09 IGSN:CSIWALF09 Leederville formation Visual analysis protocol CC Entities: specimens, data, reports, protocols Agents: people, machines Activities: prep-phases, observations Activity Person Machine Physical entity Physical entity (destroyed) Record (data or report) Plan or protocol Key wasAssociatedWith wasAssociatedWith wasAssociatedWith wasAssociatedWith wasAssociatedWith Saw:s4 Mill:m7 wasAssociatedWith used used used used used used used used wasGeneratedBy wasGeneratedBy wasGeneratedBy wasDerivedFrom wasDerivedFrom wasDerivedFrom wasDerivedFrom LF-09/2-lt- 80 wasGeneratedBy CPV protocol LF-09/2 LF-09/1