spreadsheets were used for data organization, manipulation, and editing. As the
collected data became more numerous and unwieldy for use in spreadsheets, we
purchased AQUARIUS Workstation [31] in 2011 for time series aggregation,
manipulation, and preprocessing. After each monitoring event, data downloaded
from the data loggers onto data shuttles are imported into HOBOware and
converted to CSV files, which are then imported into Aquarius. Within Aquarius,
the data are appended to previous datasets. Aquarius has tools to join datasets, trim
outliers (i.e., in the case of instrument failure), convert units and do other calculations, resample the data at different time intervals (e.g., hourly, daily, monthly), and
conduct descriptive statistics, in addition to other functions. As the datasets at
James Cave currently contain an excess of several million data points, using a
software package that can integrate and process the data has eased data management considerably.
5.3 Data Storage
The use of multiple data storage options and sharing data allows for maximum
availability and collaborative efforts. For the James Cave project, both raw and
processed data are stored on hard drives at Virginia Tech, on a cloud server, and on
a project management system at Virginia Tech to allow for exchange between
researchers. The stored datasets are public domain and can be accessed by
contacting the corresponding author of this chapter.
6 Results and Discussion
This section outlines the datasets that have been collected at James Cave as an
example of a comprehensive and integrated cave monitoring program. The section
also presents selected results from the James Cave project thus far and includes
recommendations for establishing and maintaining a long-term cave monitoring
project.
6.1 James Cave Datasets
At James Cave, the following data are collected at 10-min intervals (2007–current
(2014)):
• Precipitation at the surface
• Air temperature and relative humidity at the surface
• Drip rate at three drip sites (Fig. 9)
Instrumenting Caves to Collect Hydrologic and Geochemical Data: Case Study. . .
223
collected data became more numerous and unwieldy for use in spreadsheets, we
purchased AQUARIUS Workstation [31] in 2011 for time series aggregation,
manipulation, and preprocessing. After each monitoring event, data downloaded
from the data loggers onto data shuttles are imported into HOBOware and
converted to CSV files, which are then imported into Aquarius. Within Aquarius,
the data are appended to previous datasets. Aquarius has tools to join datasets, trim
outliers (i.e., in the case of instrument failure), convert units and do other calculations, resample the data at different time intervals (e.g., hourly, daily, monthly), and
conduct descriptive statistics, in addition to other functions. As the datasets at
James Cave currently contain an excess of several million data points, using a
software package that can integrate and process the data has eased data management considerably.
5.3 Data Storage
The use of multiple data storage options and sharing data allows for maximum
availability and collaborative efforts. For the James Cave project, both raw and
processed data are stored on hard drives at Virginia Tech, on a cloud server, and on
a project management system at Virginia Tech to allow for exchange between
researchers. The stored datasets are public domain and can be accessed by
contacting the corresponding author of this chapter.
6 Results and Discussion
This section outlines the datasets that have been collected at James Cave as an
example of a comprehensive and integrated cave monitoring program. The section
also presents selected results from the James Cave project thus far and includes
recommendations for establishing and maintaining a long-term cave monitoring
project.
6.1 James Cave Datasets
At James Cave, the following data are collected at 10-min intervals (2007–current
(2014)):
• Precipitation at the surface
• Air temperature and relative humidity at the surface
• Drip rate at three drip sites (Fig. 9)
Instrumenting Caves to Collect Hydrologic and Geochemical Data: Case Study. . .
223