XQuery Working Group - February 9, 2018

XQuery Conversion for MDID

This example demonstrates an XQuery conversion that transforms a collection of XML records into a structured CSV file, preserving field mappings for VRA and VU metadata. The code iterates over all records in a collection, extracts specific child elements and attributes, and constructs new `<record>` elements with standardized tags. It then wraps the records in a `<csv>` root element and uses the `csv:serialize` function with a map specifying `'header': true()` to generate a CSV with column headers. Finally, it writes the output to a file named "vrc.csv". The process relies on XQuery functions like `fn:collection()`, `fn:data()`, and `file:write()`, along with the `csv` module’s serialization API.

64% match

Combining Node Sequences

Two XQuery scripts demonstrate sequence operations on XML nodes. The first script, `except.xqy`, constructs a `<stopwords>` element from a word list and removes the fourth word using the `except` operator, returning a filtered sequence. The second, `operators.xqy`, defines three sequences of `<name>` elements and applies `except` to compare them, isolating differences between node sequences. Both rely on XQuery 3.1’s sequence operators (`except`, union, intersect) to combine and subtract node sets. The examples highlight how node identity and order determine sequence subtraction, with output shown as XML fragments without external libraries.

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{$doc/RecordTitle/text()}

This example extracts bibliographic records from a collection of quarterly publications and serializes them into CSV format. It queries a local XML document store containing full-text articles, capturing fields such as title, publication, volume, issue, date, pagination, and a document link. The XQuery 3.1 script uses the `csv:serialize` function to convert the generated `element csv` tree into a delimited text file, demonstrating a straightforward data-wrangling pipeline for export and downstream analysis.

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XQuery for Partitioning the Blue Mountain Project

This example demonstrates a pipeline for cleaning, partitioning, and exporting articles from the Blue Mountain Project’s TEI transcriptions into language-specific databases. It shows how XQuery 3.1 scripts transform raw periodical XML by removing facsimile and hyphenation artifacts, splitting documents into individual articles, and grouping them by `mainLang` attributes into new databases. The workflow then exports French-language texts as plain .txt files, and R code using the `tm` and `SnowballC` libraries performs text mining, including term-document matrices and stemming.

CVS to JSONL example

This example shows a practical data-transformation workflow that converts a CSV file into JSONL format, producing one JSON object per line. It fetches a remote CSV file from a GitHub gist using the `fetch:text` function, parses it into records with `csv:parse`, and iterates through each record to build key-value pairs. The code distinguishes between integer and string values using `castable as xs:integer`, then constructs JSON maps with `xml-to-json` using XQuery 3.1. The output is unindented JSONL, suitable for streaming or line-oriented processing.

XQuery Blue Mountain Project - Part III

This example shows a pipeline for transforming a single TEI XML document from the Blue Mountain Project—a digitized 1920 issue of the French journal *Action*—into clean, article-level TEI files. The first script removes facsimile elements, end-hyphenation markers, and line breaks, replacing `<lb>` elements with spaces. A second script extracts metadata and article content into a fresh TEI template, while a third builds individual TEI files for each article. The code uses XQuery 3.1 with the `fn:doc` API for document access and node operations like `copy`, `modify`, and `replace node`.

XQuery Puzzles from Week 1, Day 5, Session 4 of the Advanced Digital Editions NEH Institute at the University of Pittsburgh

This gallery example presents a set of XQuery 3.1 puzzle solutions designed to transform data formats. One function converts a textual date like "July 15, 2022" into an `xs:date` value by tokenizing the string and using a `switch` expression to map month names to numbers, while another script processes a sequence of dates with a `for` loop. A third function converts Roman numerals to integers, using `string-to-codepoints` and `codepoints-to-string` to iterate over characters and applying a conditional sum to handle subtractive notation. The code does not use any visualization libraries; the source is a gist by CliffordAnderson.

Code snippets for XQuery Working Group (Text Mining at Scale)

This example demonstrates a text-mining workflow for querying the Victorian Women Writers Project corpus stored in a BaseX database, using XQuery and XPath Full Text 1.0. It walks through creating structured records from TEI XML, saving them to a new database, and running full-text searches with scoring, stemming, and thesaurus-based matching. The code exercises functions like `db:replace`, `ft:mark`, and `ft:extract` to highlight matching text, while also showing stop-word filtering and boolean operators for queries.