- From: Gillman, Daniel - BLS <Gillman.Daniel@bls.gov>
- Date: Thu, 8 Mar 2012 17:09:21 -0500
- To: Luis Bermudez <lbermudez@opengeospatial.org>, Benedikt Kämpgen <kaempgen@fzi.de>
- CC: "public-gld-wg@w3.org" <public-gld-wg@w3.org>
Luis, In this Observation and Measurement scheme, is there a way to record equivalent units of measure? Suppose I am measuring the speed of a car using a radar gun on some road at a dangerous curve where people usually drive too fast, and the radar gun reports the speed in miles per hour. Then, suppose someone else repeats the experiment using the same radar gun, but the machine is set to report kilometers per hour instead. How do we know that all data reported in mph can be converted to data in kph, and vice-versa? The ISO/IEC 11179 standard (http://standards.iso.org/ittf/PubliclyAvailableStandards/index.html) introduced the notion of dimensionality, the name coming from the dimensional analysis that scientists use to convert units of measure. However, this takes a wider view to include units of measure that are not a part of the scientific set, and the idea doesn't depend on the faux algebra of cancelling the same units in numerator and denominator. Dimensionality depends chiefly on the set of operations, very similar to datatypes, that data in a unit of measure are allowed. Take temperatures measured in degrees Celsius. One can subtract them, take averages and similar statistics, but scalar multiplication makes no sense. For instance, twice 10C is not 20C. Therefore, data in degrees Fahrenheit are convertible to Celsius, since they share the same operations. Interestingly, under this definition, Kelvin is not an equivalent measuring system, and that is because scalar multiplication makes sense in Kelvin. Yours, Dan Dan Gillman Bureau of Labor Statistics Office of Survey Methods Research 2 Massachusetts Ave, NE Washington, DC 20212 USA Tel +1.202.691.7523 FAX +1.202.691.7426 Email Gillman.Daniel@BLS.Gov ----------------------------------------- "He has all the virtues I dislike and none of the vices I admire." - Winston Churchill ------------------------------------------ -----Original Message----- From: Luis Bermudez [mailto:lbermudez@opengeospatial.org] Sent: Thursday, March 01, 2012 11:10 AM To: Benedikt Kämpgen Cc: public-gld-wg@w3.org Subject: Observations and Measurement - draft All, Comments about Observations and Measurement related to: - Section: Publishing Statistical Data - http://www.w3.org/2011/gld/track/issues/32 - @@TODO: Are there any statements about compatibility and interoperability between O&M and Data Cube that can be made to give guidance to such organizations? Suggest to use Observations and Measurements (OM) model. An Observation is an event whose result is an estimate of the value of some property of a feature of interest, obtained using a specified procedure. An Observation has essentially the following parts: Procedure: e.g. person, sensor, observatory, model, macro. Property: e.g. temperature, color, weight. Feature of Interest: e.g. body, world, Washington DC, banana, specimen 123, Monterey Bay. Result: The actual value. Includes categories and quantities results, time series, multimedia (video, audio), one single value, a file, etc. So in the figure: "Modeling quantity, measurement, observation" we can do the following: Add Procedure, Result, Feature of Interest and Property Model Person as a type of Procedure Remove Measurement Category and Quantity are subclass of result. Phenomenon Type is same as Property Luis ------------- Luis Bermudez lbermudez@opengeospatial.org +1 (301) 760-7323 The OGC: Making Location Count... http://www.opengeospatial.org/contact On Feb 22, 2012, at 11:38 AM, Benedikt Kämpgen wrote: > Hello, > > We have further refined the Data Cube use cases and copied the content > from the wiki into an Editor's Draft for "Use Cases and Requirements > for the Data Cube Vocabulary" [1]. > > Feedback of any kind would be well appreciated. > > Best, > > Benedikt > > [1] > <http://dvcs.w3.org/hg/gld/raw-file/default/data-cube-ucr/index.html> > > > > -- > AIFB, Karlsruhe Institute of Technology (KIT) > Phone: +49 721 608-47946 > Email: benedikt.kaempgen@kit.edu > Web: http://www.aifb.kit.edu/web/Hauptseite/en > > > > >
Received on Thursday, 8 March 2012 22:09:51 UTC