themselves to larger communities of interest. Having access to these common data management tools can drastically reduce the cost of developing your own sensor network. Additionally, contributing standards-based data management tools that you have developed to a broader community helps to build and sustain that community, which helps ensure the sustainability of your project (i.e. you won’t be going it alone), and helps to ensure that sensor network data management systems evolve in ways that align with the strategic interests of your sensor network. Next, you will need to consider how the data management solution provides data integrity guarantees for both data in motion (i.e. when being transmitted) and data at rest (i.e. when being stored). Data integrity is especially important for data that will be submitted to regulators, and for data that may be subject to evidentiary requirements of civil or criminal legal proceedings. The key question to ask in these cases is: does your data management solution allow data chain of custody and integrity to be verified by a third party? 2.9.1 Summary of Key Considerations A.What are the best practices in industry for the type of data you’re collecting? B.Do you plan to use the data from the sensor network for regulatory purposes? If so, identify the accuracy, calibration, validation, or other quality assurance/control standards or protocols required by regulatory agencies to whom you will submit the data. C.Are there data representation (i.e. serialization formats) and access (i.e. application programming interfaces; APIs) standards that you can take advantage of as part of the data management hardware/software solution you plan to use? D.Are the standards for real time streaming formats the same as the batch download formats? E.Contributing standards-based data management tools that you have developed to a broader community can help build and sustain that community and your project’s sustainability. F.How does the data management solution provide data integrity guarantees for both data in motion (i.e. when being transmitted) and data at rest (i.e. when being stored)? G.For data to be used for regulatory or legal purposes, does your data management solution allow data chain of custody and integrity to be verified by a third party? H.What features do the standards you adopt need to support to address your vision for future deployments? I.Are the data standards comprehensive enough to become a policy to ensure interoperability for future projects? J.If creating a data standard policy, is it written to allow superseding technologies to be deployed? 2.10 Data Validation Data validation is a critical step to ensure usable data for your identified use cases or applications for sensor measurements. Lower-cost sensors can be affected by a wide range of variables including power for connectivity and communication, orientation of the sensor, temperature, and installation issues such as a loose wire. A method will need to be planned for how you will validate data initially as well as
17 measure and maintain data validity over time. Data validation may need to occur seasonally as other environmental variables change.
- Fall '14