This session is intended to follow the plenary session (
http://sched.co/As6G) on Scientific Quality (which has a special focus on data uncertainty). The purpose of the session is to continue discussion initiated during the plenary session inspired by the invited panelists’ presentations from the earlier plenary session and to foster more of a collaborative interchange of technical information intended to help advance the Scientific Quality of Earth science data and to discuss effective ways to communicate uncertainty to a boarder community. This session will feature an additional invited speaker who will join the plenary speakers to facilitate this discussion to provide even more diversity of opinion and expertise on the subject matter (relative to the plenary) to facilitate active participants who wish to dive deeper into technical discussion.
By way of background, the Information Quality Cluster has formally defined information quality as a combination of the following four aspects of quality, spanning the full life cycle of data products: 1. Scientific quality defined in terms of accuracy, precision, uncertainty, validity and suitability for use (fitness for purpose); 2. Product quality that takes the following into account: the degree to which the scientific quality is assessed and documented; how accurate, complete and up-to-date the metadata and documentation are; the manner in which the data and metadata are formatted; the degree to which the associated information is published and traceable throughout the data lifecycle; 3. Stewardship quality addressing questions such as how well data are being managed, preserved, and made accessible; and 4. Service quality that deals with how easy it is for users to discover, get, understand, trust, and use a given data product along with its metadata, as well as ensuring that an archive has the requisite knowledge base and people functioning as subject matter experts available to help its data users.
The focus of this session is on scientific quality, and especially on uncertainty. In the preceding plenary session, a panel of invited speakers from a variety of Earth science disciplines will have addressed questions such as: How is uncertainty determined and characterized in the products of their research or application? What are the major side effects and limitations of common statistical techniques used to quantify and characterize uncertainty? Do advanced computing techniques such as quantum computing and neural networks offer any significant advantage over traditional techniques for quantifying and characterizing uncertainty? What is the impact of uncertainty on the quality of their data products? How is data uncertainty accounted for when multiple sources of data are spliced and woven into a single product? How do they document and convey the information about uncertainty to other scientific users? What is the best way of conveying uncertainty to (possibly skeptical) public?
This session provides for more discussion with the panelists and other practitioners in scientific data generation, Scientific Quality assessment, and management. The discussion is expected to help identify issues pertaining to understanding, capturing and conveying uncertainty and to recommend actions that the Earth science data community can readily act upon to ensure and improve the overall Scientific Quality of their datasets.
