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Annotation of /trunk/lib/WebPAC/Manual.pod

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Sat Jul 16 16:48:35 2005 UTC (18 years, 9 months ago) by dpavlin
File size: 4197 byte(s)
little cleanup and first cut into WebPAC::Normalize::XML

1 dpavlin 1 =head1 WebPAC - Search engine or data-warehouse manual
3     It's quite hard to explain conceisly what webpac is. It's a mix between
4     search engine and data warehousing application. Let's see that in detail...
6     WebPAC was originally written to search CDS/ISIS records using C<swish-e>.
7     Since then it has, however, adopted different other input formats and added
8     support for alphabetical lists (earlier described as indexes).
10     With evolution of this concept, we decided to produce following work-flow
11     of your data:
13     step
15     source file CDS/ISIS, MARC, Excel, robots, ...
16     |
17     1 | apply import normalisation rules (xml)
18     V
19     intermidiate this data is re-formatted source data converted
20 dpavlin 8 data to chunks based on tag names from config/input/*.xml
21 dpavlin 1 |
22     2 | apply output filter (TT2)
23     V
24     data search engine, HTML, OAI, RDBMS
25     |
26     3 | filter using query in REST format
27     4 | apply output filter (TT2)
28     V
29     client Web browser, SOAP
31     =head2 Normalisation and Intermidiate data
33     This is first step in working with your data.
35     You are creating mappings, one-to-one from source data records to documents
36     in webpac. You can split or merge data from input records, apply filters
37     (perl subroutines), use lookups within same source file or do simple
38     evaluations while producing output.
40 dpavlin 8 All that is controlled with C<config/input/*.xml> configuration file. You
41     will want to create fine-grained chunks of data (like separate first and
42     last name), which will later be used to produce output. You can think of
43     conversation process as application of C<config/input/*.xml> recepie on
44     every input record.
45 dpavlin 1
46     Each tag within recepie is creating one new records as long as there are
47     fields in input format (which can be repeatable) that satisfy at least one
48     field within tag.
50     Users of older webpac should note that this file doesn't contain any more
51     formatting or specification of output type and that granularity of each tag
52     has increased.
54     =head2 Output filter
56     Now that we have normalized record, we can create some output. You can create
57     html from it, data files for search engine or insert them into RDBMS.
59     The twist is that application of output filters can be recursive, allowing
60     you to query data generated in previous step. This enables to you represent
61     lists or trees from source data that have structure. This also requires to
62     produce structured data in step 2 which can be filtered and queried in steps
63     3 and 4 to produce final output.
65     You should note that you can query intermidiate data in step 4 also, not
66     just data produced in step 2.
68     Output filter use Template Toolkit 2, so you have full power of simple
69     procedural language (loops, conditions) and handy built-in functions to
70     produce output.
72     =head2 REST Query Format
74     Design decision is to use REST query format. This has benefit of simplicity
75     and ability to create unique URLs to all content within webpac. Simple query
76     format is:
78     http://webpac/search/html/personal_name/Joe%20Doe/AND/year/LT%201995
80     This REST query can be broken down to:
82     =over
84     =item http://webpac
86     Hostname on which service is running. Not required if doing lookups, just
87     for browser usage.
89     =item search
91     Name of output filtering methods. This will specify search engine.
93     =item html
95     Specified template that will be used to produce output.
97     =item perlsonal_name/Joe%20Doe...
99     URL encoded query string. It is specific to filtering method used.
101     =back
103     You can easily produce RSS feed for same query using follwing REST url:
105     http://webpac/search/rss/personal_name/Joe%20Doe/AND/year/LT%201995
107     Yes, it really is that simple. As it should be.
109     =head1 Tehnical stuff
111     Following text will be more hard-code tehnical stuff about how is webpac
112     implemented and why.
114     =head2 Search Engine
116     We are using Hyper Estraier search engine using pgestraier PostgreSQL bindings
117     for it.
119     It should be relativly easy to plugin another one if need arise.
121     =head2 Data Warehouse
123     In a nutshell, webpac has evolved to support hybrid data as input. That
124     means it has become kind of data-warehouse application. It doesn't support
125     directly roll-up and roll-down operations, but they can be emulated using
126     intermidiate data step or output step.

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