Skip to content

Latest commit

 

History

History
290 lines (206 loc) · 9.02 KB

extract.md

File metadata and controls

290 lines (206 loc) · 9.02 KB

Extract data from MARC records

... with xmllint

First check if a XML namespace is declared in the document:

$ head loc.mrc.xml
<collection xmlns="http://www.loc.gov/MARC21/slim">
<record>
  <leader>01227cam a22002894a 4500</leader>
  <controlfield tag="001">12360325</controlfield>
  <controlfield tag="005">20070126075126.0</controlfield>
  <controlfield tag="008">010327s2001    nyua          001 0 eng  </controlfield>
  <datafield tag="906" ind1=" " ind2=" ">
    <subfield code="a">7</subfield>
    <subfield code="b">cbc</subfield>
    <subfield code="c">orignew</subfield>

If a namespace is set use the "local" XML element name in the XPATH expression:

$ xmllint --xpath '//*[local-name()="controlfield"]/@tag' loc.mrc.xml

Extract all tags and count them:

$ xmllint --xpath '//@tag' loc.mrc.xml | sort | uniq -c

Extract all IDs from MARC 001:

$ xmllint --xpath '//*[local-name()="controlfield"][@tag="001"]/text()' loc.mrc.xml

Extract all subfields from MARC 245 fields:

$ xmllint --xpath '//*[local-name()="datafield"][@tag="245"]' loc.mrc.xml

Extract subfield "a" from MARC 245 fields:

$ xmllint --xpath '//*[local-name()="datafield"][@tag="245"]/*[local-name()="subfield"][@code="a"]/' loc.mrc.xml

Extract content from subfield "a" from MARC 245 fields:

$ xmllint --xpath '//*[local-name()="datafield"][@tag="245"]/*[local-name()="subfield"][@code="a"]/text()' loc.mrc.xml

Extraxt all ISBNs:

$ xmllint --xpath '//*[local-name()="datafield"][@tag="020"]/*[local-name()="subfield"][@code="a"]/text()' loc.mrc.xml

Extract all DDC numbers:

$ xmllint --xpath '//*[local-name()="datafield"][@tag="082"]/*[local-name()="subfield"][@code="a"]/text()' loc.mrc.xml

... with Catmandu

Catmandu uses a domain specific language (DSL) called "fix" to extract, map and tranform data. Several "fixes" for library specifc data formats like MARC and PICA are available. Most common "fixes" are documented on a cheat sheet. "Fixes" can be used as command-line options or stored in a "fix" file:

$ catmandu convert MARC to CSV --fix 'marc_map(001,id); retain_field(id)' < loc.mrc
$ catmandu convert MARC to YAML --fix marc2dc.fix  < loc.mrc

marc_map

With marc_map you can extract (sub)fields from MARC records and map them to your own data model:

marc_map(001,dc_identifier)
# {"dc_identifier":"12360325"}

Extract part of field

MARC uses several "fixed-length" fields, where data elements are positionally defined. E.g. if you want to extract the language code from MARC 008 specify the positions with /35-37:

marc_map(008/35-37,dc_language)
# {"dc_language":"eng"}

Extract fields with specific indicators

If you want to extract fields with certain indicators specify them within sqare brackes [1,4]

marc_map('246[1,4]',marc_varyingFormOfTitle)
# {"marc_varyingFormOfTitle":"Games, diversions & Perl culture"}

Extract subfields

To extract certain subfields from a MARC data field use the subfield codes. By default several subfields will be joined to one string. Use option join to join them with another string. With option split you can split the subfields to a list. Use option pluck if you want to extract the subfields in a certain order.

marc_map(245ab,dc_title,join:' ')
# {"dc_title":"Perl : the complete reference /"}
marc_map(245ab,dc_title,split:1)
# {"dc_title":["Perl :","the complete reference /"]}
marc_map(245ba,dc_title,split:1,pluck:1)
# {"dc_title":["the complete reference /","Perl :"]}

Extract repeatable fields

MARC data fields could be repeatable. Use option split to create a list from all fields.

marc_map(650a,dc_subject,split:1)
# {"dc_subject":["Data mining.","Text processing (Computer science)","Perl (Computer program language)"]}

Extract repeatable subfields

MARC subfields could be repeatable within a MARC data field. Use option split:1 to create a list from all fields. To create a list for all subfields within one data field use option nested_arrays:1 which will return a "list of lists" of subfields, one list for each data field.

marc_map(655ay,marc_indexTermGenre,split:1)
# {"marc_indexTermGenre":["Portrait photographs","1910-1920.","Photographic prints","1910-1920."]}
marc_map(655ay,marc_indexTermGenre,split:1,nested_arrays:1)
# {"marc_indexTermGenre":[["Portrait photographs","1910-1920."],["Photographic prints","1910-1920."]]}

Extract subfields by value

To extract a subfield only if another subfield in the same data field has a certain value use a loop with a condition.

=856  4\$uhttp://journal.code4lib.org/$xVerlag$zkostenfrei
=856  4\$uhttp://www.bibliothek.uni-regensburg.de/ezeit/?2415107$xEZB

do marc_each()
  if marc_match(856x,EZB)
    marc_map(856u,ezb_uri)
  end
end
# {"ezb_uri":"http://www.bibliothek.uni-regensburg.de/ezeit/?2415107"}

Conditions

Use conditions marc_has, marc_has_many or marc_match to check if an record has certain fields or match certain conditions.

set_array(errors)

# Check if a 245 field is present
unless marc_has('245')
  set_field(errors.$append,"no 245 field")
end
 
# Check if there is more than one 245 field
if marc_has_many('245')
  set_field(errors.$append,"more than one 245 field?")
end
 
# Check if in 008 position 7 to 10 contains a 
# 4 digit number ('\d' means digit)
unless marc_match('008/07-10','\d{4}')
  set_field(errors.$append,"no 4-digit year in 008 position 7->10")
end

Add fields to a record

You can add fields to MARC records with marc_add.

marc_add(999,a,my,b,local,c,field)
marc_add(900,a,$.my.field)

Append values to (sub)fields

Use marc_append to append values to a (sub)field

marc_append(001,'-X')
marc_append(100a,' [author]')

Assign a value to (sub)fields

Assign a new value to a MARC field with marc_set.

marc_set(001,123456789)
marc_set(245a,'Perl - battle tested.')

Remove (sub)fields

Use marc_remove to remove (sub)fields from MARC records.

marc_remove(991)
marc_remove(9..)
marc_remove(0359)

Replace strings in (sub)fields

Use marc_replace_all to replace a string in MARC (sub)fields.

marc_replace_all(001,1,X)
marc_replace_all(245a,Perl,"Perl [programming language]")

Filter MARC records

You can filter MARC records from a dataset with reject or select.

reject marc_has_many(245)
select marc_match(245a,Perl)

Validate MARC records

You can validate MARC records and collect the error messages or filter valid records.

validate(.,MARC,error_field:errors)
select valid(.,MARC)

Dictionaries

MARC uses codes for languages and countries. You can build dictionaries based on these list and lookup names for these codes.

$ less languages.csv
eng,English
enm,English, Middle (1100-1500)
epo,Esperanto
esk,Eskimo languages
est,Estonian
...

# { "dc_language": "eng" }
lookup(dc_language,languages.csv)
lookup(dc_language,languages.csv,default:English)
lookup(dc_language,languages.csv,delete:1)
# { "dc_language": "English" }

Normalize ISBNs and ISSNs

Use issn, isbn10 or isbn13 to normalize international identifier.

# { "issn" : "1553667x" }
issn(issn)
# { "issn" : "1553-667X" }

# { "isbn" : "1565922573" }
isbn10(isbn) 
# {"isbn" : "1-56592-257-3" }
isbn13(isbn)
# { "isbn" : "978-1-56592-257-0" }

Links

Cheat sheet: http://librecat.org/assets/catmandu_cheat_sheet.pdf

MARC mapping rules: https://github.com/LibreCat/Catmandu-MARC/wiki/Mapping-rules

MARC tutorial: https://metacpan.org/pod/distribution/Catmandu-MARC/lib/Catmandu/MARC/Tutorial.pod

Example "fix" http://librecat.org/Catmandu/#example-fix-script