NEON collects data at sites in terrestrial and aquatic ecosystems across 20 ecoclimatic domains using a combination automated instrument measurements, airborne remote sensing surveys and observational sampling. The success of NEON relies upon standardized and quality-controlled data collection methods and processing systems:
About NEON's science designs and standardized protocols
NEON scientists collaborate with technical working groups to develop and document science designs and protocols for 1) data collection infrastructure, including sensor installation and configuration and supporting measurements; and 2) observations and samples collected at field sites. Science designs inform data collection methods and protocols guide operations crews in the field.
Standardized protocols across all sites and effective training for field technicians using protocols reduce measurement uncertainty. NEON’s protocols are based on currently utilized sampling methods with input from experts participating in NEON design workshops and technical working groups. Protocols are tested through characterization and prototype efforts. While the general methodology described in protocols will not change significantly, slight modifications will continue to be made throughout NEON’s construction period (through September 2017). Updates to these documents will be posted as they become available.
High-quality, integrated and standardized data
In order to collect and produce high-quality data, NEON relies on integrated and standardized data collection, effective data processing and quality assurance measures:
- Integrated sensor measurements, observations and samples: NEON field operations crews manage integrated collection of data and samples at NEON field sites. Field technicians maintain and monitor instruments installed at sites.
- Audit laboratory to calibrate and validate sensors: NEON maintains its own calibration and validation facility to reduce variability of sensor calibration. Sensors are calibrated and validated each year to ensure that they are collecting consistent and accurate data.
- Quality-assurance of observations and samples: NEON quality-assures observations and samples by developing collection protocols, training field staff and introducing checks during the collection process. Examples of quality-assurance include sensors with built in calibration, field staff trainings and the use of mobile applications with designated drop-down taxonomic lists to reduce error in species identification. Specimens and samples are archived for future validation and research purposes.
Standard field sites to collect data across the country
Multidisciplinary experts collaborate to transform scientific requirements into infrastructure and system designs that collect standard data across the US in a variety of ecosystems:
- Engineers and scientists prototype, test and verify data collection equipment designs;
- Facilities and civil construction staff work with scientists to develop field site designs to minimize environmental impact and optimize data collection regarding ecological variability;
- Construction staff oversee infrastructure development, such as raised walkways and towers, while engineers compare constructed sites to designs and requirements; and
- Field deployment teams install instruments and communications systems to collect and transmit site data to headquarters for processing.
High-quality, usable data
NEON design relies on algorithms and processes to convert raw field measurements and observations into calibrated, documented and quality-controlled data products. Delivering the immense volume of diverse sensor-derived data that NEON collects in a user-friendly format requires large-scale automation and computing power. NEON scientists collaborate with cyber infrastructure staff to create data processing algorithms and frameworks that
- Process incoming data to create derived data products;
- Assess the quality and integrity of data products; and
- Deliver optimized, useable, high-value data products.
For example, NEON flags sensor-derived data that are out-of-normal range and implausible values, such as a species size measurement outside of the known range, for review. NEON also conducts random recounts, crosschecks collected data with existing data and reconciles conflicting data using documented quality-control methods.
Computing and engineering infrastructure that support big data
NEON relies on computing software and hardware to manage millions of data points, thousands of sensors and terabytes of output data. Sensors and technicians collect data from sites spread across the nation. The cyber infrastructure team coordinates the transfer of data from field sites to NEON’s central data center. Working with science and engineering staff, the team:
- Standardizes and automates data collection and processing tasks;
- Stores and processes data; and
- Develops relevant operational tools, such as mobile applications.