Hunt Institute for Botanical Documentation
A Research Division of Carnegie Mellon University

Hunt Institute Archives Text Discovery Platform

Search a large and growing portion of our online collections, including handwritten documents.
PROTOTYPE

This prototype uses state-of-the-art artificial intelligence, including a vision-language model (VLM) capable of reading handwritten documents as well as typed and printed text, to create searchable transcriptions of digitized materials in the Hunt Institute Archives. This makes it possible to search the textual contents of individual pages, including material that may not be described in the archival catalog.

Use Keyword search for specific words, names, dates, scientific names, or phrases. Try Semantic search (experimental) to describe a topic, question, or kind of material when you do not know the exact wording used in the documents.

About the AI-generated transcriptions

The transcriptions are generated automatically from page images and may contain errors, especially with difficult handwriting, unusual names, multiple languages, image-quality problems, or complex layouts. They are intended primarily as a discovery aid rather than authoritative transcriptions.

Each result provides the generated transcription and links to the original digitized material and associated archival description so that readings can be checked against the source. The transcription workflow uses AI models run locally by the Hunt Institute.

About Keyword and Semantic search

Keyword search is the default and matches the wording in the transcriptions. Results contain all your terms. Use quotes for an exact phrase. Substring matching is supported, so aceae can find plant-family names ending in -aceae.

Semantic search (experimental) is useful when you know what kind of material you are looking for but do not know the words used in the documents. It ranks transcribed passages by similarity of meaning, so relevant results may not contain the exact words in your query.

Semantic queries can be broad research topics, descriptions of activities or relationships, or natural-language questions. For example:

Semantic search is not a chatbot: a question is used as a search query, and the system returns archival passages that appear conceptually related to it rather than generating an answer or summary. Short descriptions and ordinary research questions generally work better than lists of disconnected keywords. Quotation marks have no special meaning in Semantic mode. Cross-language matching may work in some cases, but it should not be treated as translation.

Keyword and Semantic search are complementary. Keyword search lets you require particular wording; Semantic search can surface differently worded passages about the same subject. Depending on the research question, trying both can reveal different useful material.

Open a result: use the prominent page-and-transcription link to see the metadata, PDF, and full transcription. Keyword-search terms are highlighted in the transcription.

Archives Collections Database (ArchivesSpace): the Collection, Item/Folder, and Digital Object links open the corresponding archival records. Collection-level dates describe the collection as a whole, not necessarily the specific item or page.

If a PDF does not load: on the detail page, use the Digital Object link, click “Go to file” in ArchivesSpace, and navigate to the page number shown here.

Current limitations
  • Automated transcriptions can contain missing or incorrect text or unintended repetition. Difficult handwriting, image quality, unusual layouts, and multiple languages can reduce accuracy. Always consult the original page image when an exact reading matters.
  • Semantic search remains experimental. Its rankings are an additional discovery aid, not a complete or definitive set of relevant results, and highly ranked pages can sometimes be only broadly related.
  • This is an active prototype. Search coverage, transcriptions, functionality, and the interface may continue to change as additional archival material is processed and the system is improved.

← Back to results

Page 22 · DO #1406 · 189_Howard_r

Collection
Richard Alden Howard (1917–2003) papers
Item/Folder
Arnold Arboretum papers , 1954–1966
Digital Object
DO #1406, page 22
Collection-level dates
1954–1966
Open PDF at page 22 ↗

Page transcription

(4) The move has been of advantage to carrying on taxonomic research in Cambridge because of "the vast number of the books, pamphlets, periodicals and specimens of the Gray and Arnold . . . combined together in one building with other botanical facilities and scholarly contacts at hand or nearby." There is, however, a "marked disadvantage" to the carrying on of such research "arising from the separation of books and herbarium specimens from the living collections in Jamaica Plain, from the separation of the wild and cultivated specimen collections and from the division of the Arboretum staff resulting from the move."

(5) The work performed by persons paid from Arboretum funds in taxonomy, horticulture and other scientific fields has continued. They are performing competent scientific work. There is no evidence of either improvement or decline in the quality of work.

(6) The services of the Arnold Professor have not been shown to have been diverted from the care and management of the Arboretum.

(7) The books and specimens of the Arboretum now in the Harvard University Herbarium are under the control of the Arnold professor. Use is made of them, as before, but to a greater extent, by Harvard students and faculty and others engaged in research. Each separate library item is identified as an Arnold Arboretum item; but not in the card catalogue. A book housed at Cambridge if lost or misplaced cannot be identified from the catalogue as having been an Arboretum book. Each herbarium sheet from the Arboretum is so marked but the herbarium cases are not marked and one must examine each sheet to determine ownership.