Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system

Posted on April 9, 2019 By Shawn Douglas Journal articles

We know that the research process creates data, and data is increasingly valuable. But can we visualize all the nooks and crannies that data is coming from in a more technologically connected society? Take for instance the food and agriculture sectors, influencing more than 20 percent of the U.S. economy. Herd data records for the dairy industry, pedigree information for the food animal industry, and soil and machine condition data from row crop farmers are only a few examples of data sources in the sectors. But what of the security of that data? Duncan et al. take a brief look at these sectors and provide insight into the ways that cybersecurity, biosecurity, and their intersections are increasingly important. The conclude by making suggestions for "[w]orkforce development, effective communication strategies, and cooperation across sectors and industries" to better "increase support and compliance, reducing the risks and providing increased protection for the U.S. bioeconomy."

DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data

Posted on April 2, 2019 By Shawn Douglas Journal articles

In this 2018 paper published in Sensors, Perez-Castillo et al. present DAQUA-MASS, their own take on the ISO 8000-61 data quality standard but updated for the world of the internet of things and smart, connected products (SCPs), in particular sensor networks. While recognizing that data quality has been studied significantly over the decades, little work has gone into the formal policies for SCP and sensor data quality. After presenting data challenges in SCP environments, related work, their model, and their methodology, the authors conclude that their "data quality model, along with the methodology, offers a unique framework to enable designers of IoT projects—including sensor networks and practitioners in charge of exploiting IoT systems—to assure that the business processes working over these systems can manage data with adequate levels of quality."