Connecting to the Data-Intensive Future of Scientific Research

In recent years enormous amounts of digital data have become available to scientific researchers. This flood of data is transforming the way scientific research is conducted. Independent researchers are in serious need of tools that will help them managed and preserve the large volumes of data being created in their own labs. Data management will not only help researchers get or keep a handle on their data, it will also help them stay relevant and competitive in increasingly strict funding environments. This paper provides summaries of best practices and case studies of data management that relate to three common data management challenges – multitudinous sensor data, shortterm data loss, and digital images. We use a combination of open system solutions such as HydroServer Lite, an open system database for time series data, and proprietary tools such as Adobe Photoshop Lightroom. Each lab may require its own unique suite of tools, but these are becoming numerous and readily available, making it easier to archive and share data with collaborators and to discover and integrate published data sets. Keywords—data management; sensor data, best practices, HydroServer Lite; data lifecycle