Lake Michigan Mass Balance
Introduction to
Lake Michigan Mass Balance Data
The main objective of the Lake Michigan Mass Balance
and Enhanced Monitoring Program is:
"...to develop a sound, scientific base of information
to guide future toxic load reduction efforts at the Federal, State, and
local levels."
Long after the study is completed, the "base of information"
will remain, and must be as diligently managed as the extensive monitoring
effort that went into creating it. The database was developed under the following guidelines:
- Develop a system having cross-program and -project utility
- Document the quality of all data populating the system
- Ensure that the resulting data base has long-term value
- Avoid duplicating effort with other data systems
Central to the data management effort is a computerized
data system to house Lake Michigan Mass Balance and other project results.
That system, the Great Lakes Environmental Monitoring Database (GLENDA),
was developed to provide data entry, storage, access and analysis capabilities
to meet the needs of mass balance modelers and other potential users of
Great Lakes data.
System Design
The database design followed a rigorous systems development process known as Information Engineering. Information
Engineering is a participatory process whereby users define requirements
and give continual feedback on system design as it proceeds. Initial user
requirements are mapped out on an entity relationship diagram
illustrating the database components and their relationships. The physical
database framework is built by following the entity relationship diagram
as a blueprint.
The Great Lakes Environmental Monitoring Database is based
on the user requirements and logical design from USEPA's STORET Modernization
project. The close association with STORET has limited the duplication
of effort common to database development projects, and ensures maximum
portability to the future central home of most environmental data.
- In an effort to reduce the data administration burden
and ensure consistency of data in this database, GLNPO developed several
key tools. Features include standard data definitions, reference tables,
standard automated data entry applications, and analytical tools are (or
will soon be) available.
Data Administration
Adapted from the 5/25/95 Draft Data Administration
Plan for the Lake Michigan Mass Budget/Mass Balance Study prepared by Tetra
Tech, Inc., under contract to EPA's Office of Water (Contract 68-C3-0303,
Work Assignment 2-42)
LMMB results will be produced by many participants and
submitted to GLNPO for archival and custody. GLNPO developed the Great
Lakes Environmental Monitoring Data Base to preserve and provide access
to the study results. To ensure that all information in the database is
consistent and compatible, GLNPO is establishing a data administration
plan.
A data administration plan defines, documents, and explains
all activities that must be performed to ensure sound management of data
base contents. In the LMMB Data Administration Plan, activities are grouped
into seven categories:
- Data Management - those activities focusing on
allowable contents of a data base
- Database Management - those activities related
to design and performance of the data base
- System Management - the collection of technical
activities including database hardware and software maintenance
- Document Management - those activities to ensure
hardcopy and electronic documentation related to the database are current,
correct, complete, and accessible
- Training and User Support - performed to provide
any necessary assistance to the "clientele" of the data base
- Public Outreach - those activities to promote
the data base and coordinate with other similar or related projects
- Authority and Accountability - to encourage adherence
to data administration practices.
The Data Administration plan is being developed to ensure
that all data administration activities are clearly defined, easy to follow,
and successfully implemented. A data administration plan instituted from
the inception of a data-generating study will avoid costly corrections
later on. The concepts in this plan may be extrapolated to manage other
Great Lakes study results.
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