This chapter describes how the components of your database can be managed in DataSight.  Initially, you will need to configure DataSight to suit your environmental data set.

DataSight databases are relational and manage your environmental data using a primary key.  Every primary data point in DataSight is a combination of a Level (location), datetimestamp, and variable. 

In consultation with all database users, you must;

• Define your Level 1, Level 2, and Level 3 hierarchy, with Level 3 typically being the location of the sample event.
• Define your Variables, which are the qualitative or quantitative parameters.
• Define your Metadata Variables, which are qualitative or quantitative parameters for a specific data point.

It should be noted that a timestamp is required for each data point, and date and time are stored to the second.

While the combination of location, date, time, and variable defines a unique data point in DataSight, other data can be recorded against or linked to that data point for further information. In other words, DataSight can also manage the metadata relevant to your projects, as follows:

• Information about a data point, such as minimum detection level, can be stored in Metadata Variables.
• Information about each location and its surroundings can be stored,
  • including a site description with images,
  • the physical coordinates and projections,
  • the construction details,
• DataSight can store the data collection information, specifically;
  • the personnel involved, and
  • the equipment and methods
• DataSight can be used to assign and visually identify data for quality coding or quality assurance purposes; specifically;
  • Flags,
  • Standards,
  • References can be set up prior to import of data for this purpose.

Metadata entered into DataSight can be used to answer questions such as why the primary dataset was created, where, when and how the data was created, who created the data, and was the data assessed against any standards and so on. Metadata  in DataSight enables you to understand your data in detail and will enable other DataSight users to find, use and properly understand your data. 

See also:

• Levels
• Variables
• Person
• Equipment
• Standards
• Flags
• References