view flys-artifacts/doc/datacage.txt @ 5606:0d8564196d73

Break printing to rework the parametrization of the print job There is now only one print button that opens a dialog with input fields for additional attributes as specified by desktop flys. Currently the print button does not work and this commit is part of a WIP.
author Andre Heinecke <aheinecke@intevation.de>
date Tue, 09 Apr 2013 11:51:29 +0200
parents eabecbdd5ade
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This document describes how the datacage configuration works, from a user
perspective.  Some rather technical details are omitted and mechanisms
simplified.

The datacages behaviour is defined in the file conf/meta-data.xml .

The datacage serves two purposes.
It handles automatic 'recommendations', which are instructions
sent by the client to add newly created artifacts to the collection.
From a user perspective, these artifacts mainly represent curves or data
points in the resulting diagrams.
The second task is to let the user add already existing artifacts (i.e.
previous calculations) or new artifacts with access to related data.

Irrelevant of the type of elements (recommendations or user picked data) the
datacage can iterate over possible artifacts by accessing its own database.
Thus, to create a list of matching entries, database queries are used.

In meta-data.xml, database queries are defined as <dc:statement> elements,
for example
                <dc:statement>
                  SELECT id          AS prot_id,
                         description AS prot_description
                  FROM wsts WHERE kind = 1 AND river_id = ${river_id}
                </dc:statement>

As can be seen from the example, the datacage configuration file can maintain
its own stack of variables (${river_id} in above example).

The database query will usually deliver one or many results, over which is
iterated using the <dc:elements> elements.

Information from this results can be used for two goals.
It can be taken as output, in which
case the client will either request the creation of these artifacts (considering
recommendations), or shown by the client in a the 'datacage widget',
the graphical representation of data which can be added in the current
context.  The later is seen when the user clicks on the Datacage button in
a diagram.
Or information can be used to feed a second (or third...) database query.
Following above example:

                <dc:statement>
                  SELECT id          AS prot_id,
                         description AS prot_description
                  FROM wsts WHERE kind = 1 AND river_id = ${river_id}
                </dc:statement>
                <dc:elements>
                  <additional>
                    <dc:attribute name="name" value="${prot_description}"/>
                    <dc:context>
                      <dc:statement>
                        SELECT id       AS prot_column_id,
                               name     AS prot_column_name,
                               position AS prot_rel_pos
                        FROM wst_columns WHERE wst_id = ${prot_id}
                        ORDER by position
                      </dc:statement>
                      <!-- ... -->

In both cases, an <dc:elements> element makes database queries available.
Also
note how the variables are defined in the first query and reused in the second
query (${prot_it}).

Any alement not prefixed with "dc" represents a (sub-) node in the resulting
tree.  The client will display these nodes and maybe subnodes in the datacage
widget - <additional> in above example.  The elements name is translated by
the client.

While iterating the final results, <dc:attributes> have to be specified
to define how the artifact is to be created.

                      <dc:elements>
                        <column>
                          <dc:attribute name="name" value="${prot_column_name}"/>
                          <dc:attribute name="ids" value="additionals-wstv-${prot_rel_pos}-${prot_id}"/>
                          <dc:attribute name="factory" value="staticwkms"/>
                        </column>
                      </dc:elements>

The "name" attribute is what is to be displayed in the client, the "ids" are given
to the server and pass important information about the chosen data.
The "factory" is chosen according to the type of data displayed.

So far, three other elements have not yet been mentioned: <dc:comment>,
<dc:if> and the <dc:when><dc:otherwise> structure.
<dc:comment> is an element to allow comments.  Choose these over standard
<!-- --> xml comments, because they are not transferred to the client.
<dc:if> and <dc:when> allow control (rather: definition) flow within
the configuration and work in analogy to the XSL-elements <xsl:if>
and <xsl:when>.

When dealing with the behaviour specification of the datacage, multiple
interpretations for the term "context" are possible.
A <dc:context> element essentially means a database binding.  Thus each
query (<dc:statement>) needs to be nested in its own context.
Furthermore, two types of databases with own bindings exist:
The "system" (default for <dc:context>, <dc:context connection="system">)
context allows queries related to the backend database with existing
data (e.g. measurements).
The "user" context (<dc:context connection="user">) allows queries against
the database which stores information about already existing artifacts and
calculations.

Another connotation for the term "context" is the situation from which
the datacage is queried.  The standard case is a from the datacage widget.
When the user opens the datacage from the graphical client, this is done
from one of possible multiple diagrams.
When the datacage is queried, it gets as an argument the "out" of
the current artifact.  The out corresponds to the diagram type.

For example the inner block of

          <dc:if test="dc:contains($artifact-outs, 'longitudinal_section')">
              <longitudinal_section>
                <dc:call-macro name="annotations"/>
              </longitudinal_section>
          </dc:if>

will only be executed if called from the datacage within a
longitudinal_section diagram.

In the given example another concept of the datacage configuration is
encountered: Macros.

Macros help to avoid duplication of parts of the document.  As the datacage
of some diagrams should include the same type of data, the same query should
be executed in multiple situations.

Therefore a macro can be defined, like in

        <dc:macro name="basedata_4_heightmarks-wq">
          <heightmarks>
            <dc:context>
              <dc:statement>
                SELECT id          AS prot_id,
                       description AS prot_description
                FROM wsts WHERE kind = 4 AND river_id = ${river_id}
              </dc:statement>
              <dc:elements>
              <!-- ... -->
        </dc:macro>

and invoked from another location within the document, e.g. with

                <dc:call-macro name="basedata_4_heightmarks"/>
.

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