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1 Supporting Information Toward Automated Inventory Modeling in Life Cycle Assessment: The Utility of Semantic Data Modeling to Predict Real-World Chemical Production Vinit K. Mittal 1, Sidney C. Bailin 2, Michael A. Gonzalez 3, David E. Meyer 3, William M. Barrett 3, Raymond L. Smith 3 1 Oak Ridge Institute of Science and Education (ORISE) Hosted by U.S. Environmental Protection Agency Office of Research and Development 26 West Martin Luther King Drive Cincinnati, Ohio 45268, United States 2 Knowledge Evolution, Inc Seaton Street NW Washington DC 20009, United States 3 U.S. Environmental Protection Agency National Risk Management Research Laboratory 26 West Martin Luther King Drive Cincinnati, Ohio 45268, United States The supporting information contains the following figures, List of Figures S1. The type of an individual chemical can be described through subclasses of class Chemical S2. Terms in a controlled vocabulary are instances of a class that represents the vocabulary as a whole S3. Object properties defined in Process ontology S4. Data properties defined in Process ontology S5. Chemical reaction and process plant for caprolactam synthesis S6. Web form to collect data from user community

2 As described in the manuscript, a choice was made between depicting subsets of chemicals via subclasses or via a controlled vocabulary. Figure S1 illustrates the use of subclasses, while Figure S2 shows a controlled vocabulary. Figure S1. The type of an individual chemical can be described through subclasses of class Chemical Figure S2. Terms in a controlled vocabulary are instances of a class that represents the vocabulary as a whole

3 Figure S3 describes the object property hierarchy for the Process ontology. Object properties link two individuals or instances. For example, the production process of a desired chemical is linked to its chemical reaction through the property has chemical reaction. The choice of a chemical process depends on whether the chemical is solid, liquid or gas; the phase of a chemical will be linked through the property has phase. Production of a chemical involves various subprocesses or subsystems. The subsystem class of the Process ontology (shown in Figure 3) will be linked with Chemical, InputsAndOutputs, and ChemicalReaction through subproperties of has subsystem property. The has subsystem property hierarchy has a similar structure as the subsystem class of the Process ontology. Instances of ChemicalReaction class will be linked to the instances of subclasses of Reactor_system, Separation_system, Storage_system, Utilities, Treatment_system, Miscellaneous_system, and Pretreatment_system classes of the Process ontology by subproperties of has reactor system, has separation system, has storage system, has utilities, has treatment system, has mscellaneous system, and pretreatment system respectively. Similarly, instances of the ChemicalReaction class will be linked to Inputs_and_Outputs through subproperties of the has_input_and_output property. Figure S3. Object properties defined in the Process ontology

4 Figure S4 shows the data properties defined in the Process ontology to specify equipment and process-specific parameters. Each data property and subproperty has a data type associated with it. For example, an instance of the Distillation column subclass, distillation column type 1 can be associated with data property has packed height which specifies the height of packing of this particular column. The property unit (in this example, unit of height) is specified informally in an annotation on the property. In a subsequent version we may convert the annotation to a formal object property of the data property (mapping the data property to a Unit object within a Units ontology), so that the unit of measure can be formally specified. Another annotation on the property can specify the type of packing material. The list of data properties shown here is not complete and will be extended as the need arises. Figure S4. Data properties defined in Process ontology

5 In order to populate the Process ontology, one of the intermediate reaction steps in the Nylon 6 lineage, cylohexanone to caprolactam, was chosen as an example. Figure S5 shows the bridging of the chemical reaction (Lineage ontology) to the manufacturing process (Process ontology) of caprolactam 1. The process plant design for caprolactam is a two-step process. The first step involves the conversion of cyclohexanone to cyclohexanone oxime, followed by conversion of cyclohexanone oxime to caprolactam. The Lineage ontology specifies cyclohexanone as a reactant of caprolactam and in addition also specifies other reaction participants; however, the Process ontology captures details of caprolactam production in a process plant, which involves details and specification of all the equipment and subprocesses involved. The Process ontology also specifies releases to the environment. Cyclohexanone Caprolactam Oleum Caprolactam (NH 3 OH) 2 SO 4 Cyclohexanone Ammonia Solid Waste Toluene (NH 4 ) 2 SO 4 Wastewater Figure S5. Chemical reaction and process plant for caprolactam synthesis 1

6 Figure S6 shows the web form for collecting data from the scientific community to populate the Lineage ontology. This approach of collecting ontology data from users has been successfully implemented by Rubin et al, 2002 for submitting polymerase chain reaction (PCR) assay data to the PharmGKB ontology 2. The web form is designed to capture basic information regarding a chemical reaction which can feed into the Lineage ontology. Some of the data obtained through the web form will be stored as instances of the Chemical, ChemicalReaction, ChemicalFamily, or ReactionParticipant class or a subclass thereof. Other data will be stored as values of data properties in the Lineage ontology corresponding to the instance for which the data is defined. The web form also requires the user to provide details about the reference, researcher and date on which data was entered. This is a very basic design of the web form, which can be modified to include more fields. A similar web form is also planned for collecting data from the user community for the Process ontology, capturing process-related details. Figure S6. Web form to collect data from the user community

7 Reference [1] Ritz, J.; Fuchs, H.; Kieczka, H.; Moran, W. C. Caprolactam. In Ullmann s Encyclopedia of Industrial Chemistry; Wiley-VCH Verlag GmbH & Co. KGaA: [2] Rubin, D. L.; Hewett, M.; Oliver, D. E.; Klein, T. E.; Altman, R. B. Automating data acquisition into ontologies from pharmacogenetics relational data sources using declarative object definitions and XML, Pac Symp Biocomput, pp , 2002.