Scientific Data Server User Manual
NEW: Quick Start Guide
Table of Contents
The Scientific Data Server has been developed to provide easy access to the data. This manual has been provided to help you get started accessing the data server. Access to the data server is provided currently through the web and via direct connections to Excel. Using an Internet Explorer web browser you have access to data availability information and you can choose plots and tables to view including scatter plots to explore the data. You can also download the data you are viewing in a wide variety of formats. Step-by-step instructions on accessing data via the web can be found here. Using Microsoft Excel, the data can be accessed by connecting your local Excel installation to the data on the server. This interface makes use of Pivot Tables and Charts to display the data and allows a great deal of flexibility in defining what data you are viewing. Step-by-step instructions for accessing the data via Excel 2003 Pivot Tables can be found here. Instructions for using Excel 2007 Pivot Tables can be found here. Before using the data, you might find it useful to understand a little of how we get, organize, and categorize the data on the server. The next section explains the data organization; please read it before using the data for serious science since all of the data selection interfaces are based on this organization. Information about sites, data availability, and calculations made within the database is presented in reports. Please read the section on accessing data via the web to learn how to view and use these reports.
Data Dimensions and Organization
The data is organized in the database by siteid where the site id is the name of the site. The downloaded data is placed in a dataset in the database. To allow data to be compared across sites, we break each column heading into its elements. The original format of the column label is typically <datumtype><repeat><_offset><_offset><_exdatumtype><units>. During loading of the data we break the label into the individual fields and store them with the data. An explanation of each of these fields is provided in the table below.
Field Name Explanation datumtype Primary data type of the data. Our primary datumtypes are currently listed on our datumtype table on the web. repeat Repeat occurs when multiple measurements of the same quantity are reported at the same site/time. When there is one and only one measurement, there should be no repeat number in the column heading and we assign repeat = 0. The following repeats are assigned 2, 3, 4, ... offset Any relevant z-offset. The units are assumed to be datumtype specific; most are in (m); TS and SWC are in (cm). _exdatumtype
Contains any additional “debris” characters appended to a primary datumtype. In other words, FC_corr has datumtype FC and exdatumtype _corr.
units The measurement units of the data (e.g. W/m2) dataset
Differentiates data from different sources and also different downloads of the data.
The resulting dataset, site id, datumtype, repeat, offset, exdatumtype, along with site characteristics such as latitude and longitude become the dimensions you can use to choose the data to look at in the various viewers.
Access to the database is provided through data cubes. A data cube organizes the data into dimensions and precalculates the aggregations along dimensions (e.g. daily and yearly values). Data calculations such as cumulative value, average, mean, max, and min are usually provided in the cube. Typically there will be several cubes available at any one time on the server. These cubes will usually provide access to a subset of the data. For instance, the cube named latestXXX (e.g. latestORNL) will contain the most recent data available from that source.
The dimensions of the data cubes follow a few basic conventions when they are exposed in the pivot table field list.
- Hierarchical versus Flat - It is possible to organize a dimension into a hierarchy to allow drill-down to finer scale. For example, in a time hierarchy the highest level might be years, then below it months, then below it days, and then below it hours. In our cubes a hierarchy of time will be labeled as "xxx to yyy" where the higher level is xxx and the lower level is yyy. An example hierarchical field would be "Year to Month". If instead, the field is month and does not have a hierarchy, then it will be called "yyy of xxx". So, an example might be "Month of Year".
NextSection: Data Access Through the Web
Contact: BWC Support
Credits:The research and development of the Scientific Data Server is funded by the Microsoft Corporation.