Xiaogang Ma a , Jin Guang Zheng a , Justin Goldstein b,c ,

1. AGU Fall Meeting 2013, San Francisco, CA Ontology Development for Provenance Tracing inNational Climate Assessment of the US Global Change Research Program Xiaogang Ma a, Jin Guang Zheng a, Justin Goldstein b,c, Linyun Fu a, Brian Duggan b,c, Patrick West a, Jun Xu a, Chengcong Du a, Anusha Akkiraju a Steve Aulenbach b,c, Curt Tilmes c,d, Peter Fox a a Tetherless World Constellation, Rensselaer Polytechnic Institute; b University Corporation for Atmospheric Research; c U.S. Global Change Research Program; d NASA Goddard Space Flight Center

2. Background • United States Global Change Research Program (USGCRP): An interagency program that coordinates and integrates Federal research on changes in the global environment and their implications for society • National Climate Assessment (NCA): An assessment conducted under the auspices of the Global Change Research Act of 1990, which requires a report to the President and the Congress every four years that evaluates, integrates and interprets the findings of the USGCRP with the intent to advance an inclusive and sustained process for assessing and communicating scientific knowledge of the impacts, risks and vulnerabilities associated with a changing global climate in support of decision making across the United States • Global Change Information System (GCIS): An information system under development through the USGCRP that establishes data interfaces and interoperable repositories of climate and global change data which can be easily and efficiently accessed, integrated with other data sets, maintained over time and expanded as needed into the future From: The National Global Change Research Plan 2012 - 2021 2

3. Collaborators National Science and Technology Council (NSTC) GCIS: Information Model and Semantic Application Prototypes (GCIS-IMSAP) Global Change Information System (GCIS) Committee on Environment, Natural Resources and Sustainability (CENRC) National Climate Assessment (NCA) White House Office of Science and Technology Policy (OSTP) Subcommittee on Global Change Research (SGCR) U.S. Global Change Research Program (USGCRP) National Climate Assessment Development Advisory Committee (NCADAC) 3

4. What we do • Ongoing: provenance* for the NCA3** report • Future: provenance of publications, datasets, models, organizations, instruments, experiments, people, etc. eventually covering the entire scope of global change * Provenance-Information about entities, activities, people and organizations involved in the production of the research findings and the supporting datasets and methods (cf. Moreau and Missier, 2013) ** NCA3 - The National Climate Assessment Development Advisory Committee (NCADAC) engaged more than 240 authors in the creation of the third NCA (NCA3) report, which is to be released in early 2014 4

5. An example “Figure 1.2: Sea Level Rise: Past, Present, and Future” in draft NCA3 5

6. Remote sensing sensors, platforms, and instruments are used in global change research Image source: Yang et al., 2013. Nature Climate Change 6

7. An example question of provenance tracing: What are NASA contributions to Figure 1.2 in the draft NCA3? “Figure 1.2: Sea Level Rise: Past, Present, and Future” in draft NCA3 7

8. Ontology Development for Provenance Tracing in the third National Climate Assessment The third National Climate Assessment Report (NCA3) Provenance–Information about entities, activities, people and organizations involved in the production of the research findings and the supporting datasets and methods Ontology –In this work the ontology (GCIS ontology) is a conceptual model of classes, properties and instances that can be used to capture provenance information in the NCA3 Image courtesy of nature.com 8

9. Method: a use case-driven iterative approach Source: Fox and McGuiness, 2008. http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology 9

10. Identifies: • goals/objectives to be accomplished • resources to be used to achieve these objectives • methods to be used to produce the desired results A template for documenting use cases: http://tw.rpi.edu/media/2013/07/25/ae99/UseCase_Template_SeS.doc Source: Fox and McGuiness, 2008. http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology 10

11. A facilitator: • sets and monitors direction • provides guidance for scoping the use case • milestonesfor implementation Team formation: domain experts, data and information producers, knowledge and information modelers, software engineers, and a scribe. Source: Fox and McGuiness, 2008. http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology 11

12. In GCIS-IMSAP works we used: • Group meeting: Titanpad, Skpye, GotoMeeting • Conceptual modeler: CMapTools • Ontology editor: Protege, Notepad++ • Ontology documentation: LODE, Parrot • Evolution environmens: TopBraid • Validator/Browser: ELDA, S2S Source: Fox and McGuiness, 2008. http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology 12

13. Provenance-explicit use cases • Title: Visit data center website of dataset used to generate a report figure • Actor and system: a reader of the draft NCA3 on the GCIS website • Flow of interactions: A reader wishes to identify the source of the data used to produce a particular figure in the draft NCA3. A reference to the paper in which the image contained in this figure was originally published appears in the figure caption. Clicking that reference displays a page of metadata information about the paper, including links to the datasets used in that paper. Pursuing each of those links presents a page of metadata information about the dataset, including a link back to the agency/data center web page describing the dataset in more detail and making the actual data available for order or download. The first use case 13

14. An intuitive concept map of the use case 14

15. An intuitive concept map of the use case Classes and properties recognized from the use case 15

16. An intuitive concept map of the use case • From an intuitive model to an ontology: • A defined class or property should be meaningful and robust enough to meet the requirements of various use cases • An ontology can be extended by adding classes and properties recognized from new use cases through the iterative approach Classes and properties recognized from the use case 16

17. Title: Identify roles of people in the generation of a chapter in the draft NCA3 • Actor and system: a viewer of the GCIS website • Flow of interactions: A viewer sees that Chapter 6 (Agriculture) in the draft NCA3 was written by a group of authors mentioned in a list. On the title page of that chapter the reader can view the role of each author, e.g., convening lead author, lead author or contributing author, in the generation of this report chapter. • We decided to use the PROV-O ontology to describe this use case The second use case 17

18. The three Starting Point classes in PROV-O ontology and the properties that relate them Source: http://www.w3.org/TR/prov-o/ 18

19. Mapping the use case into PROV-O Author of Chapter 6 Chapter 6 in NCA3 isA isA Writing of Chapter 6 in NCA3 isA 19

20. Roles of agents in an activity in PROV-O Source: http://www.w3.org/TR/prov-o/ 20

21. Mapping roles of chapter authors into PROV-O Writing of Chapter 6 in NCA3 Author of Chapter 6 isA isA Convening lead author Lead author isA Contributing author 21

22. Roles of people in the activity ‘Writing of Chapter 6’ Here only three of the eight authors of this chapter are shown. Each author had a specific role for this chapter.

23. We used PROV-O for describing roles of agents in an activity We can also describe roles of agents for an entity 23

24. Roles of people to the entity ‘Chapter 6: Agriculture’ Here only three of the eight authors of this chapter are shown. Each author had a specific role for this chapter. 24

25. More instances of prov:Role collected in the GCIS ontology 25

26. Re-using existing ontologies for the GCIS ontology By such mappings we can use reasoners that are suitable for the PROV-O ontology, and thus to retrieve provenance graphs from the established GCIS 26

27. Title: Provenance tracing of NASA contributions to Figure 1.2 in the draft NCA3 • Actor and system: a viewer of the GCIS website • Flow of interactions: A viewer sees that the caption of Figure 1.2 “Sea Level Rise: Past, Present and Future” of the draft NCA3 cites four data sources. Selecting the third citation displays a page of information about the cited paper and a citation to the dataset used in that paper. Information about the dataset includes a formal description of its origin, that is, the dataset is derived from data produced by the TOPEX/Poseidon and Jason altimeter missions funded by NASA and CNES. Clicking a link to each of these missions presents a page about the platforms, instruments and sensors in that mission. The third use case 27

28. “Figure 1.2: Sea Level Rise: Past, Present, and Future” in draft NCA3 28

29. (a) Instances of calibration, model and software underpinning “paper/103” Here only the details of one paper (i.e., “paper/103”) cited by that figure are shown Here only the details of Topex-Poseidon mission are shown (b) Instances of sensor, instrument and platform underpinning that paper Provenance tracing of NASA contributions to Figure 1.2 in draft NCA3 29

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33. Current result • GCIS ontology version 1.1 • http://tw.rpi.edu/web/project/gcis-imsap/GCISOntology • Ontology documentation • Conceptual map • Ontology RDF • We have had and will have more use cases, and • New versions of GCIS ontologies gcis ontology rpi 33

34. Current result: GCIS ontology version 1.1 GCIS ontology version 1.1 (a) Classes and properties representing a brief structure of the draft NCA3

35. GCIS ontology version 1.1 (b) Classes and properties related to the findings of the draft NCA3 and each chapter in it 35

36. GCIS ontology version 1.1 (c) Classes and properties about sensors, instruments, platforms, and algorithms, etc. that datasets are derived from 36

37. A few classes are asserted as sub-classes of “prov:Entity” and “prov:Activity”, respectively 37

38. Wrap up • The use case-driven iterative method bridges the gap between Semantic Web researchers and Earth and environmental scientists • It is capable of rapid deployment for Semantic Web application developments • First-hand experience for re-using the W3C PROV-O ontology in the field of Earth and environmental sciences • GCIS will enrich the GCIS ontology in its provenance tracing capability, eventually for covering provenance information for the entire scope of global change • Collaboration for a PROV-ES ontology for Earth and environmental sciences 38

39. Sponsors gcis rpi max7@rpi.edu Thank you!