| | 73 | At GEC13 we delivered a whitepaper on proposed changes to the MDOD structure and incorporating provenance into the MDOD. In the I&M session at GEC13, Giridhar Manepalli of CNRI presented a summary of the MDOD and some open issues. Based on his presentation, subsequent discussions with Giridhar and Harry Mussman and Jeanne Ohren of BBN, and NetKarma meetings after GEC 13, we revised our proposal to reflect these discussions and competed a draft of the schema which is included below in the publicatinos and documents section. |
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| | 75 | Some of the changes that are reflected are: |
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| | 77 | * The MDOD, is broadened to describe the experiment and measurements relating to the experiment. The original vision of the MDOD as presented by Harry Mussman was to describe all of the measurements related to an experiment. the proposed schema is extended to include the provenance of the experiment based on the OPM graph generated by NetKarma. Since the provenance graph for an experiment can be large, the annotations are stripped out of the provenance graph, leaving the structure of actors, processes, and artifacts. The example included below embeds the provenance for the XSP experiment. Removing the annotations reduced the size by 75%. |
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| | 79 | * An open issue discussed at GEC13 was how the identifier for the MDOD should be generated and whether any semantics should be embedded in the identifier. The revised proposal uses a DOI generated by NetKarma that can be used to link back to the data captured for an experiment in the Portal. the DOI would be used when an MDOD is being archived, but also allows for relative identifiers (path within the experiment) or other assigned IDs prior to an experiment being archived. Using the DOI leverages existing technology that can be used to track and update the ownership and custody of the measurement data. |
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| | 81 | * Since the MDOD needs to be dynamic and handle new measurement capabilities being added in GENI, we propose using an approach adopted in other metadata schemata such as the FGDC schema which has long been used in spatial data where keywords are defined based on an external source such as a controlled vocabulary. This allows terms to be precisely defined, but avoids continual updates to the underlying schema. |
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| | 83 | * Nesting of MDODs, but not a strict hierarchy. An experiment may use measurement data created by an operator or aggregate provider, or may incorporate measurements from multiple runs done over time. Allowing MDODs to nest or reference other existing MDODs results in a more flexible and lighter weight structure. |
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| | 85 | At GEC14 we presented a poster that outlined this structure and a proposed lifecycle for the MDOD as reflected in the following diagram: |
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