Are Your Operational Decisions Based on the Right Data?Weather data. Fuel and food data. Road closure data. Social media data. These and dozens of other datasets factor into the decisions operations professionals make day. You don't need more data. You need to know if the data you see is reliable.
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Rank the "confidence factor" of the datasets you use on this new free ESRI based survey tool to know if your data meets the standard for operational use.
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Why Do Operational Decision Makers Need ORLs?
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How Did ORLs Get Created?
The ORLs (Operational Readiness Level) were developed by NASA originally. In 2016, eleven utilities and nine states within the All Hazards Consortium's SISE (Sensitive Information Sharing Environment) workgroup worked with with NASA and the ESIP (Earth Science Information Partners) Federation to customize the ORL for operational use in the energy sector for power restoration. When utilities and state governments shared information, there was confusion on the data sources and reliability. Having the ORL standard helped everyone develop a shared confidence This text is to help your site visitors with pressing questions. To edit simply click on text. |
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What's the ORL?
When organizations in industry or government use or share data, how do they know which datasets are more reliable?
How do they avoid wasting time validating each other's data before making costly decisions or mistakes? Where is the data confidence standard for everyone to use to standardize how operational decision makers and GIS professionals use data in operational environment where there is no room for mistakes? The AHC's SISE (Sensitive Information Sharing Environment) Working Group operates the SISE framework and facilitates the ongoing development of the ORL standard. The purpose of the Operational Readiness Level (ORL) standard for data sets contained within SISE (Sensitive Information Sharing Environment) is to create a standardized way to communicate the "operational readiness" of datasets in the decision making process for executives, management, and operations people who are usually not “data” or ‘technical’ people. The ORL standard simply provides a method of ranking of “data confidence factor” against a federated standard. All data will be ranked from “1” (highest) to “4” (lowest) based on a number of criteria. This standard provides a way to help data providers improve their data to a high level of operational use and help decision makers know how reliable each data set is. In many cases it is unknown where certain dataset come from and whether the “data providers or sources” are credible or not. Decision makers can use all data in the SISE but if they choose to use an ORL4 data set, they are advised to proceed at their own caution. The intent of ORLs is to:
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