Prompt for marking up TEI P5

For Arne

This example visualizes the structure of a single TEI-encoded article by extracting metadata from an XML source and rendering it as a document-tree diagram. It shows the hierarchical relationships between the article’s title, author, issue, and page-range fields, emphasizing how the original bibliographic data maps onto the TEI structure. The visualization uses an XQuery script with XPath queries to pull specific values, such as the issue and article numbers via regular-expression replacement, and the starting/ending pages from the `biblScope`. The rendering then relies on a force-directed layout (via `d3.forceSimulation`) to position nodes, with each node representing a TEI element and links showing parent–child dependencies. The data source is the gist’s embedded TEI file, and the output is a static SVG generated client-side, reflecting the parsed metadata without additional interaction.

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This is my example code from our classroom exercise

This example visualizes stage directions from a TEI-encoded text by associating each person with the stages they appear in. The XQuery code iterates through `//person` elements and collects matching `//stage` elements based on the `@who` attribute, outputting a structured XML list of directions per character. It relies on the TEI namespace and uses `fn:tokenize` to parse multiple ID references. The result is a plain XML document, not a graphical rendering, serving as a preprocessing step for potential downstream visualization.

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Here's the query we started in class today.

This example demonstrates how to extract the title and author from a TEI-encoded XML document stored in a database. It shows the direct retrieval of text content from nested XML elements, returning both pieces of metadata as a sequence. The code uses the XQuery language with the `fn:doc()` function to access the document and XPath expressions to navigate the TEI namespace. It specifically traverses the `teiHeader/fileDesc/titleStmt` structure to pull the title and author values, illustrating a fundamental pattern for querying structured text documents in an XML database environment.

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Pandoc to TEI

This example shows a command-line workflow for converting Word documents into TEI Simple XML using Pandoc, with instructions tailored for macOS Terminal. The visualization relies on the Pandoc API to transform `filename.docx` into `filename.xml` with the `-t tei` flag and `-s` for standalone output. It demonstrates the Homebrew package manager’s role in installing Pandoc via `brew install pandoc`. The code highlights the exact Terminal commands—`curl` for Homebrew installation and `pandoc` for conversion—without abstracting the process, making the data source (the Word file) and the output format (TEI) explicit.

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`.

<title>{$info[1]}

This example demonstrates a metadata transformation from TEI to MODS, converting bibliographic details from an XML source document. The code uses XQuery 3.0 with custom functions `local:gather-information` and `local:generate-mods` to extract fields like title, author, language, publication info, and abstract from the TEI file, then constructs a MODS record and stores it via `xmldb:store`. The visualization shows how structured metadata can be programmatically reshaped between standards, relying on XPath queries and namespace declarations to map data accurately.

<title>Testing XPath

This example demonstrates how an XML TEI document’s structure can be queried using XPath and represented as an interactive node-link diagram. It displays the document’s hierarchical elements—such as `teiHeader`, `text`, `body`, and `p`—as circles connected by links, with text content visible alongside node labels. The visualization uses D3.js’s `d3.hierarchy` and `d3.tree` layout to calculate positions, while `d3.zoom` enables panning and zooming. The code loads the XML via a local file and parses it with `DOMParser`, then applies XPath expressions via `document.evaluate` to extract elements and text for rendering.

For XQuery4Humanists

This example visualizes the frequency and distribution of words extracted from a TEI-encoded poem, processing the text to remove punctuation, normalize case, and tokenize it into a list. The visualization shows the resulting word list as a simple textual display, highlighting the raw output of the XQuery processing pipeline. The code uses XQuery 3.0 functions like `fn:tokenize`, `fn:lower-case`, and `fn:replace` to clean the data, pulling the source directly from a remote XML file hosted on GitHub. The rendering relies solely on the XQuery return, with no additional JavaScript or charting libraries involved.