For Zach Johnson

100%

For Zach Johnson

✓ Published0🌍 Public

Last edited Mar 14, 2018

Created on Mar 14, 2018

This example transforms a raw XML extract of the Jesse Wills finding aid into structured archival units using XQuery 3.1. The code loads a source document from a GitHub gist, then uses a tumbling window to pair adjacent XML elements into `c02` records. It tokensizes `unittitle` text by semicolons and periods, classifies segments as folder containers or dates, and constructs `did` elements with normalized `unitdate` and `unittitle` values. The result is a cleaned, hierarchical data structure suitable for downstream visualization, though no rendering library is invoked here.

AI-generated description

Similar vizzes

Loading thumbnail…

Data from Jesse Wills finding aid that needs to be extracted into individual components

This visualization extracts individual letters from Jesse Wills’ XML finding aid and plots them as nodes in a network graph using d3.forceSimulation. Each node represents a single correspondence, positioned by recipient and date, with color or grouping revealing clusters of frequent correspondents. The code parses the XML’s unittitle and unitdate elements to create structured records, then draws the graph with SVG circles and links. It relies on d3’s force layout for spatial arrangement and d3.xml for data loading.

CCliffordAnderson

71% match

Loading thumbnail…

Xquery for Unit Dates

This example demonstrates a preprocessing step for visualizing dates in archival finding aids, extracting four-digit years from `<unitdate>` elements in a single EAD XML document. The XQuery script uses the XQuery 3.0 `copy` and `modify` expressions to insert a `normal` attribute containing the extracted year onto each unitdate node. It leverages a namespace declaration for the EAD standard and the `fn:doc` and `fn:replace` functions to fetch the remote XML file from GitHub and parse the date text via regular expressions. The output is the modified XML nodes, ready for downstream temporal analysis or charting.

CCliffordAnderson

69% match

Loading thumbnail…

Get finding aid

This example demonstrates how to fetch and transform an XML finding aid from a GitHub repository, isolating a specific portion of its hierarchical structure. The code defines a function that rebuilds the EAD document by extracting the header, archdesc attributes, and selected child elements while discarding others. It uses the XQuery language with a custom function `local:build-ead` to restructure the XML. The data source is a remote finding aid document loaded via `fn:doc` from a raw GitHub URL. The transformation explicitly copies the `c01` element and its preceding siblings, omitting the `c02` children, thereby illustrating selective XML reshaping for archival metadata.

CCliffordAnderson

68% match

Loading thumbnail…

XQuery to clean up data from an Excel-generated webpage & generate an EAD document

This example shows how XQuery 3.1 can clean data scraped from an Excel-generated HTML table and use it to generate an EAD (Encoded Archival Description) finding aid. The `fetch:text()` and `html:parse` functions extract rows from a legacy webpage, normalize the text content, and repackage the fields into JSON maps. A second function transforms those entries into EAD `<c02>` components, inserting metadata like titles, abstracts, and thumbnail image links from the Lantern Slide collection at Vanderbilt. Finally, the script rebuilds a complete EAD document, injecting the new `<c02>` elements into the existing archival description hierarchy, preserving the original structure while enriching it with parsed data.

CCliffordAnderson

63% match

Loading thumbnail…

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.

CCliffordAnderson

63% match

Loading thumbnail…

Gist ccc08dae693660d7aa1b8cf2708fd13d

This example demonstrates how to query and highlight text passages in the Victorian Women Writers Project TEI corpus using XQuery 3.1. It shows a progression from simple full-text searches for repeated terms to fuzzy matching via `ft:search` and `ft:extract`, and finally visualizes results by marking hits with `ft:mark` and segmenting them into tumbling windows. The code relies on BaseX’s full-text and windowing capabilities to extract and structure paragraph-level matches containing “garden” or “house.”

CCliffordAnderson

63% match

Loading thumbnail…

XQuery Working Group Challenge

This example transforms the PROIEL treebank’s Latin New Testament XML into a sequence of verse elements, each tagged with its citation and concatenated token forms. It fetches the remote XML via `fn:doc`, extracts distinct citation parts, and filters tokens by matching `@citation-part` to build structured verses. The code uses XQuery 3.1’s element constructors and `fn:data` to output text, demonstrating a direct pipeline from hierarchical treebank data to flat verse-like text.

CCliffordAnderson

62% match

Loading thumbnail…

{$title || " - "}

This example displays a list of EAD (Encoded Archival Description) titles sorted alphabetically from a collection of finalized XML files, rendered as plain paragraph elements in an XHTML page. It uses XQuery 3.1 with the `fn:collection` function to gather titles from `titleproper[@type="filing"]` nodes, and a local template function `local:template` constructs the HTML output, setting a dynamic heading level and tab title. The code demonstrates a server-side, XML-to-HTML transformation pipeline without client-side JavaScript libraries or interactive visualization components.

CCliffordAnderson

62% match