From OPeNDAP Documentation

1 Data Analysis with OPeNDAP

The OPeNDAP software is not only a data transport mechanism. Using OPeNDAP, you can subsample the data you are looking at. That is, you can request an entire data file, or just a small piece of it.

1.1 Selecting Data: Using Constraint Expressions

The URL such as this one:

refers to the entire dataset contained in the file. A user may, however, choose to sample the dataset simply by modifying the submitted URL. The \new{constraint expression} attached to the URL directs that the data set specified by the first part of the URL be sampled to select only the data of interest from a dataset even for programs that do not have a built-in way to accomplish such selections. This can vastly reduce the amount of data a program needs to process, and reduce the network load of transmitting that data to the client.

1.1.1 Constraint Expression Syntax

A constraint expression is appended to the target URL following a question mark, as in the following examples:[1,100,5]>15.0<15.0<15.0

A constraint expression consists of two parts: a \new{projection} ,

separated by an ampersand (\&). Either part may contain several sub-expressions. Either part may be present, or both.


<math>proj_{1},proj_{2},\ldots,proj_{n}\&sel_{1}\&sel_{2}\&\ldots\&sel_{m}</math> \end{center}

A projection is simply a comma-separated list of the variables that are to be returned to the client. If an array is to be subsampled, the projection specifies the manner in which the sampling is to be done. If the selection is omitted, all the variables in the projection list are returned. If the projection is omitted, the entire dataset is returned, subject to the evaluation of the selection expression. The projection can also include functional expressions of the form:




\noindent where the arguments are variables from the dataset, scalar values, or other functions.

A simple selection expression is a boolean expression of the form

\begin{center} "variable operator variable"


"variable operator value"





can be one of the relational operators listed in

\tableref{opd-client,tab,cons-ops} on opd-client,tab,cons-ops;

can be any variable recorded in the dataset;
can be any scalar, string, function, or list of

numbers (Lists are denoted by comma-separated items enclosed in curly braces ,for example, \{3,11,4.5\}.); and

is a function defined by the server to operate

on variables or values, and to return a boolean value (See ( opd-client,function)).

Each selection clause begins with an ampersand (\&) representing the "AND" boolean operation\footnote{The "OR" function may be

 implemented with a list.  For example, to say that "i" must
 equal 3 OR 11 you would write "i} = \{3,11\"The clause evaluates
 to true when \var{i} equals any one of the elements.}.

The \& is actually a prefix operator, not an infix

operator. That is, it must appear at the beginning of each selection clause, no matter what. This means that a constraint expression that contains no projection clause must still have an

\& in front of the first selection clause.

There is no limit on the number of selection clauses that can be combined to create a compound constraint expression. Data that produces a true (non-zero) value for the entire selection expression will be included in the data returned to the client by the server. If only a part of some data structure, such as a \class{Sequence}, satisfies the selection criteria, then only that part will be returned.

Due to the differences in data model paradigms, selection is not

implemented for the OPeNDAP array data types, such as \class{Grid} or \class{Array}. However, many OPeNDAP servers implement selection functions you can use for the same effect. You can query the server for the functions it implements with the usage service outlined in

( opd-client,function). Simple Constraint Expression Examples

Consider the data descriptor in File:Opd-client,fig,dds. The figure is an example of the Data Descriptor Structure \indc{Data Descriptor

 Structure!example} , one of the messages returned by an OPeNDAP server in response to a query about some dataset. The full syntax

description for this structure is given in ( data,ancillary). For the moment, it is only important that it is the description of a dataset containing station data including temperature, oxygen, and salinity. Each station also contains 20 oxygen data points, taken at 20 fixed depths, used for calibration of the data.

The following URL will return only the pressure and temperature pairs of this dataset. (Note that the constraint expression parser removes all spaces, tabs, and newline characters before the expression is parsed.) There is only a projection clause, without a selection, in this constraint expression\footnote{For the sake of clarity, this and

 several of the following constraint expression examples span
 multiple lines.  While the constraint expression evaluator ignores
 newline characters, program limitations of the OPeNDAP client will
 likely prevent a user from typing a newline in a constraint


Dataset {
      Int32 day;
      Int32 month;
      Int32 year;
      Float64 lat;
      Float64 lon;
      Float64 O2cal[20];
         Float64 press;
         Float64 temp;
         Float64 O2;
         Float64 salt;
      } cast;
      String comments;
   } station;
} arabian-sea;

\caption{Sample Data Descriptor} \end{figure},

Incidentally, we have assumed that the dataset was stored in the JGOFS format\footnote{Because it contains an array, the dataset

 pictured in Figure~(opd-client,fig,dds) is technically not a
 valid JGOFS dataset. We have included the array for pedagogical
 purposes, and hope that the JGOFS purists will forgive us.}  on the

remote host, in a file called explO2/cruise. For the sake of brevity, from here on we will omit the first part of the URL, to concentrate on the constraint expression alone.

If we only want to see pressure and temperature pairs below 500 meters deep, we can modify the constraint expression by adding a selection clause.


In order to retrieve all of each cast that has any temperature reading greater than 22 degrees, use the following:


Simple constraint expressions may be combined into compound expressions with logical AND (\&). To retrieve all stations west of 60 degrees West and north of the equator:

 expression!boolean functions}

As was mentioned, the logical OR can be implemented using a list of scalars. The following expression will select only stations taken north of the equator in April, May, June, or July.


If our dataset contained a field called monsoon-month, indicating the month in which monsoons happened that year, we could modify the last example search to include those months as follows:


In other words, a list can contain both values and other variables. If monsoon-month was itself a list of months, a search could be written as:


For arrays

and grids, there is a special way to select data within the projection clause. Suppose we want to see only the first five oxygen calibration points for each station. The constraint expression for this would be:


By specifying a \new{stride} value, we can also select a \new{hyperslab} of the oxygen calibration array:


This expression will return every fifth member of the 02cal array. In other words, the result will be a four-element array containing only the first, sixth, eleventh, and sixteenth members of the 02cal array. Each dimension of a multi-dimensional arrays may be subsampled in an analogous way. The return value is an array of the same number of dimensions as the sampled array, with each dimension size equal to the number of elements selected from it.

1.1.2 Operators, Special Functions, and Data Types

The data types accessible through the OPeNDAP software are listed and described in ( data,types). It is advisable to be familiar with these types before trying to construct complex constraint expressions.

The constraint expression syntax defines a number of operators for each data type. These operators are listed in \tableref{opd-client,tab,cons-ops}

Except for the <math>*</math> operation defined on the URL data

type, all the operators defined for the scalar base types are boolean operators whose result depends on the specified comparison between its arguments. Refer to ( opd-client,CE,url) for a description of the URL data type and its operator.

The \math[\~{}=]{\sim =} operator returns true when the character string on the left of the operator matches the regular expression on the right. See ( opd-client,CE,regex) for a discussion of regular expressions.

The \class{Structure}, \class{Sequence}, and \class{Grid} data types are each composed of a collection of simpler data types. The . and operators allow a user to refer to the subsidiary variables within these compound types. For example, station.year indicates the value of the year member of the station sequence.

The array operator <math>[]</math> is used to subsample the given array. See opd-client,array-op for an explanation and example of its use.

\begin{table}[htbp] \caption{Constraint Expression Operators\@.}

\begin{center} \begin{tabular}{|p{0.75in}|p{2in}|} \hline \tblhd{Class} & \tblhd{Operators}

\hline \hline \multicolumn{2}{|c|}"Simple Types\/"


\class{Byte}, \class{Int32}, \class{UInt32}, \class{Float64} & < > = != <= >=


\class{String} & = != \math[\~{=}]{\sim =}


\class{URL} & *


\multicolumn{2}{|c|}"Compound Types\/"


\class{Array} & [start:stop] [start:stride:stop]


\class{List} & length("list), nth({\em list,n}), member({\em list,elem})"


\class{Structure} & .


\class{Sequence} & .


\class{Grid} & [start:stop] [start:stride:stop] .


\end{tabular} \end{center} \end{table}

There are three special functions defined to operate on the \class{List} data type. The length() function returns the number of elements in the given list, the "nth()" function returns the list element indicated by the input index, and the "member()" function, which returns true if the given value equals any member of the list. Note that the behavior of the nth() function is undefined for indices beyond the range of the list.

1.1.3 Using Functions in a Constraint Expression

An OPeNDAP data server may define its own set of

functions that may be used in a constraint expression. For example, the data server containing the example data from File:Opd-client,fig,dds might define a sigma1() function to return the density of the water at the given temperature, salinity and pressure. A query like the following would return all the stations containing water samples whose density exceeded 1.0275"<math>g/cm^3</math>".



Functions like this one are not a standard part of the OPeNDAP architecture, and may vary from one server to another. A user may query a server for a list of such functions by sending a URL ending with ".info". For example, you can query the data server installed on the OPeNDAP home site with the following URL:

The data returned will be an HTML message, readable with a standard web browser, containing documentation of the server running on the given site, and the data named in the URL. In this case, you will learn that the specified server defines two functions that can be used in a constraint expression:

\item[geolocate(\var{variable}, \var{lat1}, \var{lat2}, \var{lon1},


Returns the elements of \var{variable} that fall

within the box created by (\var{lat1},\var{lon1}) and


time(\var{variable}, \var{start_time}, \var{stop_time}) 

Returns the elements of \var{variable} that fall within the time

interval \var{start_time} and \var{stop_time}.

1.1.4 Using URLs in a Constraint Expression

The OPeNDAP data access protocol defines a special data type to handle distributed data: \class{URL}. This is a scalar data type, much like the \class{String} type, intended to hold one OPeNDAP URL. It generally points at some remote dataset or data value. Using this data type, a constraint expression may make the data returned from one OPeNDAP data server dependent on data held at an entirely different site.

In order to accommodate this data type, OPeNDAP defines a special "dereference" . Similar to its function with pointers in C, applying this operator to a URL returns the data specified by that URL. The \class{URL} data type itself contains only a character string. It must be dereferenced to produce a reference to the data named by the URL. Examples

The following example will return all the stations containing oxygen values greater than fifteen:


Similarly, the following constraint expression will yield all the stations in the dataset whose value is greater than that of the oxygen value indicated by the URL:


Finally, suppose that the dataset itself contained a variable of type \class{URL}, and that this URL contained the address of oxygen data stored at some other site. The data descriptor for the dataset might look like the following:

Dataset {





URL O2cal;




} station;
} arabian-sea;

We can now write the previous constraint as:


URLs stored in remote datasets may also be used in the projection clause of the constraint expression. Imagine a dataset that consists only of a list of URLs for each square degree of latitude and longitude. A user could query this dataset for the actual list of URLs, or, by using the * operator, could construct a constraint expression that would return the actual data indicated by the URLs in the target dataset.

1.1.5 Pattern Matching with Constraint Expressions

There are three operators defined to compare one \class{String} data type to another. The = operator returns TRUE if its two input character strings are identical, and the != operator returns TRUE if the \class{Strings} do not match. A third operator, \math[\~{}=]{\sim =} is provided that returns TRUE if the \class{String} to the left of the operator matches the regular expression in the \class{String} on the right.

A regular expression is simply a character string containing wildcard characters that allow it to match patterns within a longer string. For example, the following constraint expression might return all the stations on the sample cruise at which a shark was sighted:


Most characters in a regular expression match themselves. That is, an "f" in a regular expression matches an "f" in the target string. There are several special characters, however, that provide more sophisticated pattern-matching capabilities.


The period matches any single character except a newline.

* + ?

These are postfix operators, which indicate to try to match the preceding regular expression repetitively (as many times as possible). Thus, o* matches any number of o's. The operators differ in that o* also matches zero o's, o+ matches only a series of one or more o's, and o? matches only zero or one o.

`[ ... ]' 

Define a "character set," which begins with [ and is terminated by ]. In the simplest case, the characters between the two brackets are what this set can match. The expression [Ss] matches either an upper or lower case s. Brackets can also contain character ranges, so [0-9] matches all the numerals. If the first character within the brackets is a caret (\^{ }), the expression will only match characters that do not appear in the brackets. For example, [\^{ 0-9]*} only matches character strings that contain no numerals.


These are special characters that match the empty string at the beginning or end of a line.


These two characters define a logical OR between the largest possible expression on either side of the operator. So, for example, the string Endeavor<math>\backslash|</math>Oceanus matches either Endeavor or Oceanus. The scope of the OR can be contained with the grouping operators, <math>\backslash</math>( and <math>\backslash</math>).

<math>\backslash</math>( <math>\backslash</math>) 

These are used to group a series of characters into an expression, or for the OR function. So, for example, <math>\backslash</math>(abc<math>\backslash</math>)* matches zero or more repetitions of the string abc2.

There are several more special characters and several other features of the characters described here, but they are beyond the scope of this guide. The OPeNDAP regular expression syntax is the same as that used in the Emacs editor. See the documentation for Emacs~\citel{emacs} for a complete description of all the pattern- matching capabilities of regular expressions. Examples

In the above example, a user might wonder whether the shark comments had been spelled with upper or lower case letters. The following constraint expression will return any station that mentions a shark in upper or lower case.


Of course, this would miss Shark and sHark and so on. The constraint could be written this way to catch all odd permutations of upper and lower case:


1.1.6 Optimizing the Query

Using the tools provided by OPeNDAP, a user can build quite elaborate and sophisticated constraint expressions that will return precisely the data he or she wishes to examine. However, as the complexity of the constraint expression increases, so does the time necessary to process that expression. There are some techniques a user may user to optimize the evaluation of a constraint that will ease the load on the server, and provide faster replies to OPeNDAP dataset queries.

The OPeNDAP constraint expression evaluator uses a "\ind{lazy

evaluation}" algorithm. This means that the sub-clauses of the selection clause are evaluated in order, and parsing halts when any sub-clause returns FALSE. Consider a constraint expression that looks like this: \indc{constraint expression!parse



If the server encounters a station with no oxygen values over 15.0, it does not bother to look at the temperature records at all. The first sub- clause evaluates FALSE, so the second clause is never even parsed.

A careful user may use this feature to his or her advantage. In the above example, the order of the clauses does not really matter; there are the same number of temperature and oxygen measurements at each station. However, consider the following expression:


For each station there is only one month value, while there are many oxygen values. Passing a constraint expression like this one will force the server to sort through all the oxygen data for each station (which could be in the thousands of points), only to throw the data away when it finds that the month requested does not match the month value stored in the station data. This would be far better done with the clauses reversed:


This expression will evaluate much more quickly because unwanted stations may be quickly discarded by the first sub-clause of the selection. The server will only examine each oxygen value in the station if it already knows that the station might be worth keeping.

This sort of optimization becomes even more important when one of the clauses contains a URL. In general, any selection sub-clause containing a URL should be left to the end of the selection. This way, the OPeNDAP server will only be forced to go to the network for data if absolutely necessary to evaluate the constraint expression. \tbd{Are

there other optimization issues besides order?}

1.2 A Word About Data Translation

Once a researcher is freed from the

confines of using only local data, he or she will soon discover that there is a wealth of data available on the Internet, and nearly all of it is stored in formats incompatible with her own. Worse, the data formats are often mutually incompatible, rendering the confusion complete. OPeNDAP provides a solution applicable to a great many such problems.

When an OPeNDAP server retrieves data from some distant machine, that data may be in any of several file formats supported by OPeNDAP. The server translates the data, however, into an intermediate format for transmission. Upon receipt of the messages containing data, the OPeNDAP client software unpacks the data into the form expected by the calling client program and returns it to that program. Because all data must be translated into the same intermediate format, OPeNDAP becomes a powerful format translator for datasets. In effect, this means that a program designed to read and display JGOFS data can look at the OPeNDAP data catalog and see everything as JGOFS datasets. A netCDF program can look at those same datasets, from that same catalog, and think they are all in netCDF format. This system of translation allows a researcher to ignore the question of formats and concentrate on the data alone.

Of course, there are some translations that cannot be done transparently, if they can be done at all. Consider a two-dimensional array of satellite sea-surface temperature measurements. Assume the data is stored in netCDF format on some machine called The data might be uniquely specified by some URL, say However, were a user to feed that URL to a JGOFS-originated OPeNDAP client designed to draw property vs. depth graphs of station data, no translation facility would be able to map the original data into a form accommodated by the client program.

The issues of data models and data translation are important ones to the data provider. These issues are discussed in detail in ( data,trans)