The volume and quality of Safeguards data continues to increase with instrumentation and software advances.Technical issues with handling,managing,and fully using Safeguards data also continue,despite clever and energetic engineering by Safeguards systems experts. Data‘indigestion’has two challenges,the effective use of all available data for event detection and analysis,and timely accurate collection and storage of Safeguards data. Focusing on the first data challenge,I consider here solutions developed for systems with heterogeneous sources of data coupled with complex analysis demands and explore how these solutions may be applied to Safeguards data. Other scientific and engineering fields contend with similar data management issues.For example,the data demands of weather tracking and prediction,seismic monitoring,medical modeling,and multisource digital image processing and archives share similar attributes. Each manages heterogeneous sensors collecting data across wide timescales,with huge variations in data quality and quantity requirements.Moreover,each type of sensor in these networks approaches data representation,transmission and storage with unique and often proprietary implementations.Existing solutions for data“indigestion”in these fields may offer guidance for the Safeguards community. A novel feature of these solutions is the use of public standards for data representation and interoperability,developed through an open community process.These standards arise through a community process involving peer input and review.A data standard must address essential requirements for data handling,such as efficient archival,storage,transport,and processing of data.The standard must maintain event provenance,data fidelity,and chain-of- custody information.Moreover,the standard must support data protection and security,and transparently support proprietary extensions.
展开▼
