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 16 · DO #4768 · 231_Rogers_Bx5FF18_r

Collection
David James Rogers (1918–2007) papers
Item/Folder
Meeting - Electronic Data Processing Methods Kew, 1973
Digital Object
DO #4768, page 16
Collection-level dates
1948–1977
Open PDF at page 16 ↗

Page transcription

EDP MEETING AT KEW
OCTOBER 1973

Summaries of Papers to be Presented

J.P.M. BRENAN (Royal Botanic Gardens, Kew):
EDP in Major Herbaria - the Priorities

Most herbaria have not introduced EDP methods. It is essential for their advantages and disadvantages to be carefully assessed. An attempt is made to do this with particular reference to the Kew Herbarium and its arrangement. Most herbarium arrangements permit of a more or less efficient information retrieval system to be operated by conventional means and within limits. It is doubtful whether any major herbarium can afford to computerise all its holdings, or whether the result will be worth it. Some suggestions for priorities are given based on needs at Kew. These may be summarised as follows:

1. Inventory of type material.
2. Inventories of specimens and geographical areas of outstanding conservation importance.
3. Listing of economic uses.
4. Listing of vernacular names.
5. Recording of vouchers for non-taxonomic research.
6. Limited recording of specimens in defined areas, systematic or geographical, of special research interest to Kew.
7. Listing of genera and species with their geographical ranges.
8. Comprehensive listing of genera and their position under families.

R. ROSS (British Museum, Natural History):
Relations between Herbarium Records and other Records

In considering the design of EDP records of herbarium holdings it is necessary to take account of the need for compatibility between such records and those of other types of collections, viz.:

Associated material, such as spirit specimens, pollen specimens, carpological and other bulky specimens and anatomical preparations;

Other botanical collections, including collections of living plants, collections of microscopic organisms, and palaeobotanical specimens;

In some institutions, zoological collections.

The various points that need to be borne in mind in connection with each of these will be discussed.

A. GOMEZ-POMPA and J.A. TOLEDO (National University of Mexico):
Data Processing of Herbarium Specimens for the Flora of Veracruz, Mexico

The Flora of Veracruz programme is a comprehensive study of the plant resources of this Mexican state. It involves a series of studies that go beyond the common