Seedlabs

Pre-Antibiotic Ophthalmic Outcomes Dataset (1906–1913)

A dataset of eye disease treatments and results from 1906 to 1913 for researchers studying drug resistance.

A structured, machine-readable dataset of diagnoses, treatments, and reported outcomes extracted from the complete 1906–1913 run of a leading German clinical ophthalmology journal, giving antimicrobial-resistance and outcomes researchers a baseline of how eye disease presented and resolved before antibiotics existed.

Microbial Symbiosis and ResistanceLife-sciences research data: antimicrobial-resistance baseline evidence and ophthalmic outcomes research

Concept

A curated research data product built by extracting the case reports and case series from the complete 1906–1913 run of Klinische Monatsblätter für Augenheilkunde (volumes 44–51, simultaneously numbered n.F. 1–16) into structured records: diagnosis, treatment administered, follow-up, and reported outcome, with historical German terminology mapped to modern ophthalmic and ICD codes. A clinical monthly journal of this era is composed precisely of such case material, so the extraction target is well defined. The deliverable is a citable dataset (per-volume provenance, codebook, and documentation) — not a browsing archive. The single wedge is the pre-antibiotic outcomes baseline: for the first time, health-outcomes and AMR researchers get a machine-readable record of how ocular disease was treated and what happened, in the years immediately before antibiotics and modern microsurgery. This fills the catalog's open gap of automated structured extraction from thematically complete volumes, applied to clinical outcome data rather than materials properties.

Why now

The source record demonstrates that a complete, thematically coherent run of a German clinical ophthalmology journal exists for exactly 1906–1913 (Bd. 44–51, "also called n.F., Bd. 1–16") — a bounded corpus of roughly eight annual volumes covering precisely the pre-antibiotic window. That boundedness is what makes this feasible now: it is a fixed, finite extraction target suitable for a high-accuracy pilot combining Fraktur-capable OCR with current language-model extraction, rather than an open-ended archive commitment. Claims stay modest and tied to the evidence: the dataset reports what the volumes report, with no modern outcome adjudication, and its value is as a baseline corpus for researchers studying the value of antibiotics and long-term shifts in ophthalmic disease.

Written by GLM · 8 Oct 2026

AI assessment

Backed by 1 paper88

A highly focused, feasible data product that converts a finite historical corpus into a structured baseline for AMR research, though its commercial scale is limited by the niche nature of the dataset.

Evidence strength
5/5
The idea is directly grounded in a specific, bounded set of volumes (Bd. 44-51) of a known clinical journal, making the source material concrete and verifiable.
Market pull
3/5
While the named beneficiaries (Wellcome Trust, NIH) are the correct targets, the demand for a single-journal historical dataset may be more academic than commercial.
Novelty & moat
4/5
Unlike the 'Journal-Mined Regional Epidemiology' idea which is a general feed, this is a specialized historical baseline for a specific medical era, filling a distinct gap in longitudinal outcomes data.
Feasibility
5/5
The project is highly feasible due to the finite size of the corpus and the availability of Fraktur-capable OCR and LLMs for structured extraction.
Wedge clarity
5/5
The wedge is exceptionally sharp: a pre-antibiotic outcomes baseline for ocular disease, avoiding the trap of building a general archive.
Simplicity / focus
5/5
The product is a single, well-defined dataset with a clear extraction target and a specific output format.

Scored by Gemma 4 · 8 Oct 2026. Rated against a fixed rubric (evidence, market, novelty, feasibility, wedge, simplicity), relative to the closest ideas already in the catalog. A prior estimate to compare ideas before real-world signal arrives.

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Who benefits

  • One Health Trustorganization

    Its research quantifies the declining effectiveness of antibiotics; outcomes of ocular infections from a run covering 1906–1913, before antibiotics existed, provide the natural zero-antibiotic baseline those analyses currently lack.

  • Wellcome Trustorganization

    It funds both drug-resistant-infection research and the history of medicine; a structured pre-antibiotic outcomes dataset sits exactly at that intersection and is the kind of resource it commissions.

  • National Library of Medicine (NIH)organization

    NLM digitizes and indexes historical medical journal runs; a structured outcomes layer makes such holdings usable for computational research rather than only browsing.

  • Johns Hopkins Institute of the History of Medicineorganization

    Historians of medicine need machine-readable primary sources; converting a German-language print run into structured case records turns a hard-to-use archive into analyzable evidence.

  • Deutsche Ophthalmologische Gesellschaftorganization

    The journal is a core organ of German ophthalmology; a structured, citable dataset of its 1906–1913 run serves the society's heritage mission and gives members a research asset.

Research it builds on

  1. Klinische Monatsblätter für Augenheilkunde
    Lang, Gerhard K.; Lang, Gabriele E.: · 2026 · 194 citations
    All ideas from this paper →
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