{
  "schema_version": "0.6.0",
  "paper_id": "multiscale-navigation-large-trace-data",
  "page_url": "https://threadslab.org/research-publications/papers/multiscale-navigation-large-trace-data/",
  "title": "Multiscale Navigation in Large Trace Data",
  "title_variants": [],
  "authors": [
    "Naser Ezzati-Jivan",
    "Michel R. Dagenais"
  ],
  "author_details": [
    {
      "name": "Naser Ezzati-Jivan",
      "orcid": "https://orcid.org/0000-0003-1435-6297",
      "profile_url": "https://threadslab.org/"
    },
    {
      "name": "Michel R. Dagenais",
      "orcid": null,
      "profile_url": "https://dblp.org/pid/60/309.html"
    }
  ],
  "publication": {
    "year": 2014,
    "venue": "2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE)",
    "type": "conference paper",
    "publication_date": "2014-05",
    "online_date": null,
    "print_date": "2014-05",
    "volume": null,
    "issue": null,
    "pages": "1-7",
    "article_number": null,
    "publisher": "IEEE",
    "issn": [],
    "isbn": [],
    "crossref_type": "proceedings-article"
  },
  "publication_type": "conference paper",
  "status": "published_metadata_record",
  "canonical_source_url": "https://doi.org/10.1109/CCECE.2014.6901019",
  "source_record_id": "multiscale-navigation-in-large-trace-data-9b173f4210",
  "identifiers": {
    "doi": "10.1109/CCECE.2014.6901019"
  },
  "abstract": "The accessible abstract describes hierarchical trace-log management with an interactive zoomable timeline and semantic and physical zooming that supports coarse-layer-first navigation.",
  "abstract_source": "Public abstract mirrors and institutional metadata reviewed; author abstract not reproduced because reuse permission for the publisher version was not established.",
  "abstract_available": true,
  "scholar_eligibility": {
    "eligible": false,
    "basis": "not-eligible",
    "note": "The page is a discovery record; it does not claim Google Scholar article-host eligibility."
  },
  "description": "The accessible abstract describes hierarchical trace-log management with an interactive zoomable timeline and semantic and physical zooming that supports coarse-layer-first navigation.",
  "evidence_level": "full-text-reviewed",
  "evidence": {
    "source_basis": "full-text-reviewed",
    "coverage": "material paper sections",
    "summary_origin": "AI-assisted catalog editorial summary",
    "review_status": "catalog-reviewed; paper-author approval pending",
    "verified_on": "2026-08-26",
    "sources": [
      {
        "note": "Local PDF reviewed, including LTTng/Linux setup, abstraction layers, State History Tree, links, and download example"
      },
      {
        "note": "IEEE DOI record: https://doi.org/10.1109/CCECE.2014.6901019"
      },
      {
        "note": "IEEE Xplore record: https://ieeexplore.ieee.org/document/6901019/"
      }
    ]
  },
  "summary": {
    "core_contribution": "The paper presents multiscale trace navigation that links raw kernel events to system-call, synthetic, and fault/alert abstractions in a zoomable timeline.",
    "problem": "A single-resolution view of a large execution trace either overwhelms the analyst with low-level events or hides the evidence needed to explain a high-level operation. Analysts need overview, drill-down, and correspondence between abstraction levels.",
    "method": "The prototype uses LTTng 1.x on Linux kernel 2.6.38.6 and builds abstraction layers from raw kernel events to system calls, synthetic HTTP/file/DNS/attack events, and faults/alerts. A pattern library applies aggregation, generalization, filtering, and reduction. Events are linked through process names and time bounds, and a zoomable timeline supports physical/semantic zoom and range queries. A customized disk-backed State History Tree stores the layers separately, with hybrid on-demand/precomputed aggregation proposed for the storage/query trade-off. The example workload recursively downloads dnews.com on an Intel Core i7 2.8 GHz/6 GB system.",
    "findings": "The prototype demonstrates a single view in which a high-level file download can be expanded into DNS/HTTP events and then kernel system calls, preserving a path for causal inspection. Precomputing levels can speed visualization at the cost of storage, while on-demand abstraction saves space but adds query work. The paper does not report a broad quantitative accuracy or interaction-latency benchmark.",
    "limitations": "The abstraction hierarchy and link logic are tied to the demonstrated patterns, layers are stored separately, and direct correspondence pointers are limited. The evaluation uses a prototype and one main workload, so performance and usability at much larger traces remain open.",
    "future_work": "Integrate abstraction levels in one efficient store, add explicit event correspondence, learn or configure links from data, evaluate hybrid aggregation policies, and measure storage, query latency, and human navigation quality at scale."
  },
  "tags": [
    "trace-visualization",
    "trace-abstraction",
    "trace-analysis",
    "performance-analysis"
  ],
  "keywords": [
    "large trace data",
    "multiscale navigation",
    "zoomable timeline",
    "semantic zoom",
    "physical zoom",
    "trace visualization"
  ],
  "versions": [
    {
      "id": "published-version",
      "label": "Published version",
      "relation": "version-of-record",
      "title": "Multiscale Navigation in Large Trace Data",
      "url": "https://doi.org/10.1109/CCECE.2014.6901019",
      "pdf_url": null,
      "status": "published",
      "canonical_for_citation": true
    },
    {
      "id": "polypublie-record",
      "label": "PolyPublie record",
      "relation": "source-record",
      "title": "Multiscale Navigation in Large Trace Data",
      "url": "https://publications.polymtl.ca/12410/",
      "pdf_url": null,
      "status": "public_source_record",
      "canonical_for_citation": false
    }
  ],
  "access": {
    "status": "published_metadata_record",
    "note": "PolyPublie, DOI, DBLP, and abstract metadata verify the record. The paper PDF was not obtained; the summary is restricted to abstract-level claims.",
    "license": null
  },
  "resources": {
    "code": null,
    "data": null,
    "slides": null,
    "demo": null
  },
  "citation_guidance": {
    "when_to_cite": "Cite this paper when linking overview-to-detail navigation across abstracted and raw execution-trace levels.",
    "points": [
      "LTTng raw/system-call/synthetic/fault abstraction layers.",
      "Time-bound and process-linked correspondence between levels.",
      "The zoomable timeline and disk-backed State History Tree.",
      "The storage-versus-query-time trade-off and prototype-scale limitation."
    ],
    "canonical_version_id": "published-version"
  },
  "provenance": {
    "metadata_verified_on": "2026-08-26",
    "metadata_source": [
      "Local PDF reviewed, including LTTng/Linux setup, abstraction layers, State History Tree, links, and download example",
      "IEEE DOI record: https://doi.org/10.1109/CCECE.2014.6901019",
      "IEEE Xplore record: https://ieeexplore.ieee.org/document/6901019/"
    ],
    "summary_written_by": "AI-assisted",
    "summary_verified_by": "full-text-grounded catalog review; author approval pending",
    "linked_preprint_record": null,
    "author_order_note": null
  },
  "batch": {
    "phase": 2,
    "batch_label": "expanded forty-paper release",
    "status": "included_in_expanded_catalog",
    "selected_at": "2026-08-28"
  }
}