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--- ch9_handbook:getting_started [2014/08/11 14:11] – bob
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 So without further adieu, let’s look at an extremely simple TMATS file.
+a. __RCC IRIG 106 Revision Level__. Identifies the RCC IRIG 106 version of TMATS used to generate the file. The format to describe a Revision Level is 106-xx, with xx as the last two digits of the year.
+<code>G\106:09;</code>
+b. Point of Contact (POC) information.
+(1) __Number of POCs__. Identifies the number of Points of contact (POC) to be given.
+<code>G\POC\N:1;</code>
+(2) __POC Name__. Identifies the name of the POC.
+<code>G\POC1-1: Wile E. Coyote;</code>
+(3) __POC Agency__. Identifies the agency the named POC is associated with.
+<code>G\POC2-1:ACME Corp;</code>
+(4) __POC Address__. Identifies the agency address.
+<code>G\POC3-1:123 Roadrunner Way;</code>
+(5) __POC Telephone__. Identifies the named POC contact number.
+<code>G\POC4-1:(555)555-5555;</code>
+Now, that wasn't so bad, was it? Well, unfortunately, this example is not very useful because it does not actually describe anything … but it’s a start.
+===== Attribute General Syntax and Semantics =====
+Before we consider a more meaningful example, let's get a general idea of what TMATS
+should look like. Each TMATS attribute consists of a unique code name and a data item. The
+code name appears first, delimited by a colon. The data item follows, delimited by a semicolon.
+Thus, an attribute appears as A:B; - where “A” is the code name and “B” is the data item.
+There are two basic types of attribute code names: single entry and multiple entry. Single
+entry attributes are those for which there is only one code name and one data item. Multiple
+entry attributes have multiple indexed code names and data items, each of which corresponds to
+an index number. These attribute types allow for lists of like items, such as measurements.
+a. __Single Entry Example__
+<code>G\OD:05-11-2009;</code>
+The code name is “G\OD” which is “Origination Date”.
+The data item is “05-11-2009” which indicates May 11, 2009.
+b. __Multiple Entry Example__
+<code>G\DSI-2:AIRCRAFT_DATA;</code>
+The code name is “G\DSI-2” which is “Data Source ID’.
+The index “2” specifies that this is the second data source ID.
+The data item is “Aircraft Data” which is the identification of this data source.
+Numeric values for data items may be either integer or decimal. Scientific notation is
+allowed only for those attributes specifically defined for its use. For alphanumeric data items,
+including keywords, either upper or lower case is allowed; TMATS is not case sensitive.
+Semicolons are not allowed in any data item, including comments. Leading, trailing, and
+embedded blanks are assumed to be intentional and must be accounted for if they appear within
+code names or data items. Carriage return (CR) and line feed (LF) may be used to improve
+readability.
+===== A “Measurement” by any Other Name… =====
+You might not believe the number of person years that have been spent discussing the
+definition of “measurement.” Other words that are related, or possibly mean the same thing
+depending on who you ask, are: measurand, sample, parameter, and derived measurement. So
+let’s look at the basic process to illustrate.
+For this example, assume some raw phenomenon exists such as temperature, pressure or
+velocity. You can also talk about discrete settings such as weight on wheels or other settings or
+values that are not necessarily physical phenomena. But let’s start with just real world things
+that we tend to measure. A sensor is placed somewhere to “measure” this phenomenon. Most
+sensors are analog devices that “measure” the phenomenon and produce a voltage output
+(actually, millivolt output). An analog to digital converter (ADC) translates this voltage into a
+set of discrete bits. Usually, these bits are the ones that are telemetered. These bits are then
+converted using some algorithm into engineering units (EU) such as degrees Fahrenheit or
+furlongs per fortnight. The EU data is what engineers like to examine. Now consider that there
+isn’t just one sample of each item, but rather a series of samples over time.
+So there are essentially four things involved here: the raw phenomenon, the voltage
+output of the sensor, the raw digitized data value, and the EU data. Well, there is something of a
+fifth thing in the sense that values of different phenomena might be used to “derive” another
+“measurement.” For example, a series of position and time samples might be used to derive
+velocity. Then the sixth thing is the full set of samples of a given phenomenon over time.
+Which of these is a measurement, sample, parameter, measurand, etc.?
+A related terminology issue is the concept of “raw” data. Sticking our neck out a little,
+we’ll say that this usually implies the non-EU digitized bits that are telemetered. But the term
+can be moved in either direction. That is, someone might refer to the “raw signal” meaning the
+voltage output of the sensor or, as used above, the “raw phenomenon.” Or, occasionally, the
+initial EU data might be considered “raw” since the ultimate analysis is usually presented in
+some form derived from these low level measurements. To add to the confusion, there are some
+people that talk about “generations” of data, implying that the initial digitized sensor output is a
+different generation from the EU or derived calculations.
+In practice, the words measurement, measurand, sample, and parameter are often used
+interchangeably. The use of the term “raw” is probably sensitive to context. However, there are
+people and systems that make subtle distinctions between these words, so one must be careful.
+This handbook will use the word “measurement” for all of these words, and the word “raw” will
+not be used in this document.
+===== A “Look and Feel” Example =====
+===== Attributes for the Look and Feel Example =====
+===== Let’s Talk About Bits =====
+==== Bit Masks ====
+==== Transfer Order ====
+==== Fragment Order and Concatenation ====