{
  "id": "https://waingram.github.io/projects.json",
  "type": "project_collection",
  "last_updated": "2026-06-17",
  "owner": "https://waingram.github.io/#waingram",
  "projects": [
    {
      "id": "https://waingram.github.io/#project-goal-conditioned-evaluation",
      "name": "Goal-Conditioned Evaluation in Scholarly Collections",
      "status": "completed",
      "completed": 2026,
      "role": "Researcher",
      "project_type": "dissertation research",
      "research_layer": "Knowledge Understanding",
      "description": "Developed a framework for evaluating research contributions relative to explicit goals, using SDG alignment as a testbed. The work treated large language models as explicit evaluative functions whose judgments can be distilled into retrieval and classification systems.",
      "topics": [
        "goal-conditioned evaluation",
        "scientific contribution modeling",
        "large language models",
        "information retrieval",
        "Sustainable Development Goals",
        "scholarly collections"
      ]
    },
    {
      "id": "https://waingram.github.io/#project-harnessing-etds",
      "name": "Harnessing ETDs: Pioneering AI-Driven Innovations in Library Service",
      "status": "active",
      "period": "2024-2027",
      "role": "Principal Investigator",
      "funding": "https://waingram.github.io/#grant-lg-256638-ols-24",
      "research_layer": "Knowledge Access",
      "description": "Integrates retrieval-augmented models with curated ETD corpora to investigate semantic retrieval, contextual classification, evidence-constrained generation, and hybrid sparse/dense ranking for institutional research analysis.",
      "topics": [
        "retrieval-augmented models",
        "ETD corpora",
        "semantic retrieval",
        "contextual classification",
        "evidence-constrained generation",
        "hybrid sparse/dense ranking"
      ]
    },
    {
      "id": "https://waingram.github.io/#project-opening-books",
      "name": "Opening Books and the National Corpus of Graduate Research",
      "status": "completed",
      "period": "2019-2023",
      "role": "Principal Investigator",
      "funding": "https://waingram.github.io/#grant-lg-37-19-0078-19",
      "research_layer": "Knowledge Access",
      "description": "Developed methods for computational access to book-length documents using Electronic Theses and Dissertations, including document structure extraction, classification, summarization, and metadata enrichment.",
      "topics": [
        "Electronic Theses and Dissertations",
        "document structure extraction",
        "classification",
        "summarization",
        "metadata enrichment",
        "computational access"
      ]
    },
    {
      "id": "https://waingram.github.io/#project-oads-preservation",
      "name": "Preserving Open Access Datasets and Software for Sustainable Computational Reproducibility",
      "status": "active",
      "period": "2024-2027",
      "role": "Senior Personnel",
      "funding": "https://waingram.github.io/#grant-lg-256694-ols-24",
      "research_layer": "Knowledge Use",
      "description": "Studies preservation of open access datasets and software used to reproduce research results reported in scholarly works.",
      "topics": [
        "open access datasets",
        "research software",
        "computational reproducibility",
        "open science",
        "scholarly documents"
      ]
    },
    {
      "id": "https://waingram.github.io/#project-etd-accessibility",
      "name": "Enhancing Accessibility of Electronic Theses and Dissertations",
      "status": "active",
      "period": "2024-2026",
      "role": "Co-Principal Investigator",
      "funding": "https://waingram.github.io/#grant-lg-256693-ols-24",
      "research_layer": "Knowledge Access",
      "description": "Planning project for improving accessibility of Electronic Theses and Dissertations for blind and low-vision library users.",
      "topics": [
        "Electronic Theses and Dissertations",
        "accessibility",
        "blind and low-vision users",
        "document structure",
        "library services"
      ]
    },
    {
      "id": "https://waingram.github.io/#project-government-records",
      "name": "Ensuring Scholarly Access to Government Records and Archives",
      "status": "completed",
      "period": "2020-2021",
      "role": "Project Lead",
      "funding": "https://waingram.github.io/#grant-1910-07229",
      "research_layer": "Knowledge Access",
      "description": "Convened experts to examine machine-learning techniques for enhancing public access to government records.",
      "topics": [
        "government records",
        "archives",
        "machine learning",
        "public access",
        "digital collections"
      ]
    }
  ]
}