The ScintPack Laboratory Data Acquisition, Evaluation and Reporting System provides a means to acquire, visualize, evaluate and otherwise reduce to useful form, data captured from a wide variety of laboratory instruments.
Its modular design partitions the users approach to organized data collection and maintenance, into four general categories.
ASCII data records, sometimes called data frames, are captured from the data source. The individual data elements within each record are parsed using a data frame template mask. Only the data elements matching the mask are placed in the data viewer as data points on a trace.
A data source may be one of the following:Data are collected and processed in one of three ways.
The data is represented as a variable with respect to time. This form of data acquisition is most common wherever chemical or physical processes are measured or monitored over a finite time period.
Four Data Types can be processed and applied to a Time Series and are characterized as follows.
Differential processing uses the difference between two measurements or two points in time as a measure of the quantity of interest. This form of processing is useful when monitoring PressVol / Temp relationships.
Non-cumulative data where the data values directly represent the quantity of interest. Examples of Simple data would be Temperature or pH measurements.
A quantitative determination can be derived by calculating the Area under the curve.
Radiochemical data is a form of Integral but with the results expressed in CPM or DPM, the common units of radioactivity.
The data represents a pre-processed output from another data system which has already made measurements and calculated results. Counter Mode data is represented as a sample number such as a vial or test tube. It may be a fractionated sample, either manually pipetted or automatically collected via a fraction collector. In addition this form of data may be entered directly from the Keyboard.
Statistical data is stored and displayed as a frequency distribution where measured values are plotted against frequency of occurrence. Histogram Mode is used wherever a measurement is made over and over in order to gain a statistical measure of tendency or deviation. Output tables report Range, Mean and Standard Deviations for tagged regions. Typical applications include:
