v0.3.0: Publication-ready release with blog site, paper update, and polish

Release prep:
- Version bump to 0.3.0 (pyproject.toml, cli.py)
- Rewrite README.md with current stats (475 drafts, 713 authors, 501 ideas)
- Add CONTRIBUTING.md with dev setup and code conventions

Blog site:
- Add scripts/build-site.py (markdown → HTML with clean CSS, dark mode, nav)
- Generate static site in docs/blog/ (10 pages)
- Ready for GitHub Pages deployment

Academic paper (paper/main.tex):
- Update all counts: 474→475 drafts, 557→710 authors, 1907→462 ideas, 11→12 gaps
- Add false-positive filtering methodology (113 excluded, 361 relevant)
- Add cross-org convergence analysis (132 ideas, 33% rate)
- Add GDPR compliance gap to gap table
- Add LLM-as-judge caveats to rating methodology and limitations
- Add FIPA, IEEE P3394, W3C WoT to related work with bibliography entries
- Fix safety ratio to show monthly variation (1.5:1 to 21:1)

Pipeline:
- Fetch 1 new draft (475 total), 3 new authors (713 total)
- Fix 16 ruff lint errors across test files
- All 106 tests pass

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-03-08 17:54:43 +01:00
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"""Fetch AI-related standards metadata from ISO/IEC JTC 1/SC 42.
ISO provides open data (JSON/CSV/Parquet) for metadata but full text is paywalled.
We use the open data portal to catalog SC 42 standards and supplement with
publicly available scope/abstract from the ISO Online Browsing Platform (OBP).
"""
from __future__ import annotations
import csv
import io
import re
import time as time_mod
import httpx
from rich.console import Console
from ..config import Config
from .base import SourceDocument
console = Console()
# ISO Open Data Portal — deliverables metadata
ISO_OPEN_DATA_CSV = "https://isopublicstorageprod.blob.core.windows.net/opendata/_latest/iso_deliverables_metadata/csv/iso_deliverables_metadata.csv"
# SC 42 is the AI committee under JTC 1
SC42_COMMITTEE = "ISO/IEC JTC 1/SC 42"
# Additional AI-relevant committees
AI_COMMITTEES = [
"ISO/IEC JTC 1/SC 42", # Artificial Intelligence
"ISO/IEC JTC 1/SC 27", # Information security (AI trust/privacy overlap)
]
# Known key SC 42 standards with abstracts (since open data lacks abstracts)
ISO_AI_CATALOG = [
("ISO/IEC 42001:2023", "Information technology — Artificial intelligence — Management system",
"Specifies requirements for establishing, implementing, maintaining, and continually improving an AI management system within organizations."),
("ISO/IEC 22989:2022", "Information technology — Artificial intelligence — AI concepts and terminology",
"Establishes terminology and describes concepts in the field of artificial intelligence."),
("ISO/IEC 23894:2023", "Information technology — Artificial intelligence — Guidance on risk management",
"Provides guidance on managing risk related to development and use of AI systems."),
("ISO/IEC 23053:2022", "Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)",
"Establishes a framework describing a generic AI system using ML technology."),
("ISO/IEC 38507:2022", "Information technology — Governance of IT — Governance implications of the use of AI",
"Provides guidance on the governance implications of AI for governing bodies of organizations."),
("ISO/IEC 5338:2023", "Information technology — AI system life cycle processes",
"Defines processes and their associated activities for the development and operation of AI systems."),
("ISO/IEC 5339:2024", "Information technology — AI — Guidance for AI applications",
"Provides guidance on how to apply AI within organizations, including use case analysis and risk assessment."),
("ISO/IEC 42005:2025", "Information technology — AI — AI system impact assessment",
"Provides guidance for assessing the potential positive and negative impacts of AI systems."),
("ISO/IEC TR 24028:2020", "Overview of trustworthiness in artificial intelligence",
"Provides an overview of trustworthiness in AI, including risks, challenges, and approaches."),
("ISO/IEC TR 24029-1:2021", "Assessment of the robustness of neural networks — Part 1: Overview",
"Provides background on properties of neural network robustness and methods for assessment."),
("ISO/IEC TR 24030:2021", "Artificial intelligence — Use cases",
"Provides a collection of representative use cases of AI applications across various domains."),
("ISO/IEC TS 6254:2024", "Objectives and approaches for explainability of ML models and AI systems",
"Describes objectives and approaches for explainability of machine learning models and AI systems."),
("ISO/IEC 12792:2024", "Transparency taxonomy of AI systems",
"Establishes a transparency taxonomy for AI systems to support understanding and governance."),
]
ISO_OBP_URL = "https://www.iso.org/standard/"
def _iso_id_to_name(iso_id: str) -> str:
"""Convert ISO ID to slug. E.g. 'ISO/IEC 42001:2023' -> 'iso-iec-42001-2023'."""
slug = iso_id.lower().replace("/", "-").replace(" ", "-").replace(":", "-")
return slug
class ISOFetcher:
"""Fetch AI-related standards from ISO/IEC.
Combines:
1. Open data CSV for discovering SC 42 standards
2. Curated catalog with known abstracts
3. OBP scraping for scope text of discovered standards
"""
def __init__(self, config: Config | None = None):
self.config = config or Config.load()
self.client = httpx.Client(timeout=30, follow_redirects=True)
def search(
self, keywords: list[str], since: str | None = None
) -> list[SourceDocument]:
"""Return AI-relevant ISO/IEC standards."""
seen: dict[str, SourceDocument] = {}
# Strategy 1: Curated catalog (with real abstracts)
console.print(" Loading ISO/IEC SC 42 catalog...")
for iso_id, title, abstract in ISO_AI_CATALOG:
name = _iso_id_to_name(iso_id)
seen[name] = SourceDocument(
name=name,
title=f"{iso_id}: {title}",
abstract=abstract,
source="iso",
source_id=iso_id,
source_url=f"https://www.iso.org/standard/{iso_id.split(':')[0].replace('/', '%2F').replace(' ', '%20')}.html",
time=self._extract_year(iso_id),
doc_status="published",
)
# Strategy 2: Try to download open data CSV for additional SC 42 standards
console.print(" Fetching ISO open data for SC 42 standards...")
open_data_docs = self._fetch_open_data(keywords, since)
for doc in open_data_docs:
if doc.name not in seen:
seen[doc.name] = doc
console.print(f" Found [bold green]{len(seen)}[/] ISO/IEC AI standards")
return list(seen.values())
def _extract_year(self, iso_id: str) -> str:
"""Extract year from ISO ID like 'ISO/IEC 42001:2023'."""
if ":" in iso_id:
return iso_id.split(":")[-1]
return ""
def _fetch_open_data(self, keywords: list[str], since: str | None) -> list[SourceDocument]:
"""Fetch ISO open data CSV and filter for AI standards."""
docs = []
try:
console.print(" Downloading ISO deliverables catalog (CSV)...")
resp = self.client.get(ISO_OPEN_DATA_CSV, timeout=60)
resp.raise_for_status()
reader = csv.DictReader(io.StringIO(resp.text))
ai_keywords = ["artificial intelligence", "machine learning", "neural network",
"ai system", "trustworth", "autonomous"]
for row in reader:
title = row.get("title.en", "")
committee = row.get("ownerCommittee", "")
ref = row.get("reference", "")
status = row.get("currentStage", "")
pub_date = row.get("publicationDate", "")
scope = row.get("scope.en", "")
# Filter: SC 42 committee OR AI keywords in title
is_sc42 = "SC 42" in committee
has_ai_keyword = any(kw in title.lower() for kw in ai_keywords)
if not (is_sc42 or has_ai_keyword):
continue
if since and pub_date and pub_date < since:
continue
name = _iso_id_to_name(ref)
docs.append(SourceDocument(
name=name,
title=f"{ref}: {title}",
abstract=f"ISO/IEC standard: {title}. Committee: {committee}. Status: {status}.",
source="iso",
source_id=ref,
source_url=f"https://www.iso.org/standard/{ref.split(':')[0].replace('/', '%2F').replace(' ', '%20')}.html",
time=pub_date or self._extract_year(ref),
doc_status=status.lower() if status else "published",
))
except httpx.HTTPError as e:
console.print(f"[yellow]Could not fetch ISO open data: {e}[/]")
except Exception as e:
console.print(f"[yellow]Error parsing ISO CSV: {e}[/]")
return docs
def download_text(self, doc: SourceDocument) -> str | None:
"""ISO full text is paywalled. Return abstract/scope only."""
# Try to scrape scope from ISO website
iso_id = doc.source_id.split(":")[0] # e.g. "ISO/IEC 42001"
try:
# The OBP has scope text for some standards
url = f"https://www.iso.org/standard/{iso_id.replace('/', '%2F').replace(' ', '%20')}.html"
resp = self.client.get(url)
if resp.status_code == 200:
# Extract scope/abstract from page
scope_match = re.search(
r'<div[^>]*id="item-abstract"[^>]*>(.*?)</div>',
resp.text, re.DOTALL,
)
if scope_match:
scope = re.sub(r'<[^>]+>', '', scope_match.group(1)).strip()
if len(scope) > 30:
return scope[:5000]
time_mod.sleep(0.5)
except httpx.HTTPError:
pass
return None
def close(self) -> None:
self.client.close()