Tools for Publishing Environmental Observations on the Internet

1
Tools for Publishing Environmental Observations
on the Internet Justin Berger, Undergraduate
Researcher Jeff Horsburgh, Faculty Mentor David
Tarboton, Faculty Mentor Nancy Mesner, Faculty
Mentor David Stevens, Faculty Mentor
Cyberinfrastructure Development
Abstract
Data Visualization Tools
Telemetry and Streaming Data Management
CUAHSI Observations Data Model (ODM)
As environmental sensor technology progresses,
and as the volume of environmental data produced
by these sensors increases, scientists have begun
to realize that the organization and
representation of data are important, so much so
now that in many cases much of the time and
effort associated with scientific discovery is
spent obtaining, manipulating, and organizing
observational data.  Unfortunately, there is
currently no standard way for scientists to store
and publish environmental observations, and there
are few freely-available tools designed
specifically for this purpose.  The software
tools presented here have been designed to
automate the process of publishing environmental
observations, enabling engineers and scientists
to visualize, edit, transform, and publish the
observational data that they collect in such a
way that they become available via the Internet
to the larger scientific community for use in
scientific discovery.  These tools include
software for automating the loading of streaming
sensor data into a central observations database,
software for visualizing, summarizing, and
performing simple quality assurance/quality
control on the data, and tools for publishing the
observations data on the Internet via web
applications that interact directly with the
central observations database.
Data visualizations allow scientists to examine
relationships between variables over time and
space.
The data we are collecting are stored in an
instance of the ODM, which enables us to publish
them through the CUAHSI Hydrologic Information
System (HIS).
We have developed a plan for a communications and
data processing system to link sensors in the
field with a central observations database in
real time. Once in the database, the data are
immediately available online using web services
and applications.
Data Collection Process
Multiple time series plot of Temperature (Left Y)
and Relative Humidity (Right Y) at a single site.
Plots like this one may reveal important
relationships among variables.
Correlation plot of Temperature (y-axis) and
Relative Humidity (x-axis) at a single site.
(Only values measured at the same time were
plotted.) A trend emerges relative humidity
decreases as temperature increases.
The goal of this research is to design and
develop methods and tools that will assist in the
collection and manipulation of hydrologic data.
These methods and tools will allow researchers to
automate the collection of certain types of
hydrologic data allowing more accurate and more
frequent measurements. These tools will also
allow researchers to collaborate, view, and
compare data in an effort to assist researchers
in finding patterns and correlations in
hydrologic data.
Client Application Development
Conclusions
Data Management Applications

• We are further developing client applications
  that use the continuous monitoring data or
  present it to the public in a clear and concise
  format.
• Data Access System for Hydrologists
• WaterOneFlow Web Services
• Time Series Analyst
• Additional graphing utilities and statistical
  analysis tools.

Streaming Data Loader - Automatically stream
sensor data directly into an ODM database ODM
Tools - Query and export data series and
metadata - Plot and summarize data series - Edit,
delete, modify, adjust, interpolate, average, etc.
1. The data is collected using devices like
this turbidity sensor or the weather station
below.
2. A data logger (below) contained within the
weather station collects and stores the data
until it is sent via a wireless transmitter to a
repeater or to the server.
We are drowning in information and starving for
knowledge. Rutherford D. Roger

• How are water quantity, quality, and related
  earth system processes affected by natural and
  human induced changes to the environment?
  Addressing this broad question, which spans the
  fields of hydrology and environmental
  engineering, in a meaningful way will require
  comprehensive monitoring of water and water
  constituent processes over a network of
  watersheds spanning a range of scales and
  settings so that hypotheses can be tested and so
  that models and theoretical understanding can be
  developed.
• Current hydrological understanding is constrained
  by the kinds of measurements that have heretofore
  been available. These constraints can be
  loosened by new measurement technologies, new
  strategies for their deployment, and new methods
  for organizing, managing, publishing,
  visualizing, and analyzing data.
• This research seeks to advance hydrologic science
  through the application of advanced hydrologic
  data collection techniques and development and
  application of cyberinfrastructure in an
  environmental observatory setting.

3. Once the data is on the server, tools such
as the Streaming Data Loader (below) can transfer
it into a central database.
Little Bear River Cyberinfrastructure
Examples Little Bear River Test Bed Website
(http//water.usu.edu/littlebearriver) Little
Bear River Google Maps Server (http//water.usu.ed
u/littlebearmap) Little Bear River DASH
Application (http//his02.usu.edu/dash/)
4. Data within the database can easily be
accessed by custom designed software and web
applications.