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Information management at the North Temperate Lakes Long-term Ecological Research site — Successful support of research in a large, diverse, and long running project

Gries, Corinna, Gahler, Mark R., Hanson, Paul C., Kratz, Timothy K., Stanley, Emily H.
Ecological informatics 2016 v.36 pp. 201-208
Internet, analytical methods, automation, data collection, databases, education, information management, lakes, landscapes, leadership, quality control, research support, students
Information management has been an integral part of the research process at the North Temperate Lakes Long-term Ecological Research (NTL LTER) program for over 30years. A combination of factors has made the information management system (IMS) at NTL very successful. Significant resources have been invested in the IMS from the beginning, the Information Manager has been part of the leadership team at NTL and later in various roles at the LTER network level; the NTL IMS was a very early adopter of database systems, standardized metadata, and a data delivery system based on those metadata. This approach has made data easily accessible to NTL researchers and the broader scientific community. Data management workflows have become increasingly more automated with adoption of modern technologies as they became available, making the system efficient enough to handle core data as well as all one-time research data generated within NTL and several related projects. More than three decades of core data from eleven lakes are reused extensively as critical background information and as the limnological go-to site for many synthesis projects within and beyond LTER.The NTL IMS continues to implement new technologies for improving data management efficiency, discovery, access, integration, and synthesis. Accordingly, the functionality of the original online data access system programmed in Java and JavaServer Pages (JSP) was ported to the modern content management system, Drupal and integrated into LTER's Drupal Ecological Information Management System (DEIMS). NTL has invested in sensor technology for studying lake conditions over the long term, which necessitated a sophisticated management system tailored to high frequency data streams. Several technologies have been used at different times for automation of management, quality control and archiving of these high volume data. Near real time lake conditions can be accessed on the NTL website and smart phone Apps.Easy access to long-term and sensor data in the NTL IMS has led NTL researchers to develop new analytical methods and the publication of several R statistical packages. Recent graduate students are now employed as data scientists helping define a new career path inspired by the availability of data.The NTL project has amassed one of the world's most comprehensive long-term datasets on lakes and their surrounding landscapes. The NTL IMS facilitates the use of these data by multiple groups for research, education, and communication of science to the public.