import json
import pandas as pd
from pathlib import Path
base = Path(“/mnt/data”)
sectors = {
“Defense & Security”: {
“services”: {“NaaS”,”AaaS”,”RegaaS”,”IDaaS”,”ValaaS”,”OaaS”,”TaaS”,”RaaS”,”ProvAaaS”,”VaaS”,”InteropaaS”,”ACaaS”,”DaaS”,”AnaaS”,”VizaaS”},
“standards”: {“STIX/TAXII”,”RDF/JSON-LD”,”W3C VC”},
“anchors”: {“Sequences”,”Strains”,”Specimens”,”Digital Credentials”},
},
“Manufacturing & Supply Chain”: {
“services”: {“IDaaS”,”OaaS”,”TaaS”,”ProvAaaS”,”InteropaaS”,”ACaaS”,”VaaS”,”DaaS”,”AnaaS”,”VizaaS”},
“standards”: {“GS1 EPCIS”,”RDF/JSON-LD”,”W3C VC”},
“anchors”: {“Batch Certificates”,”Cultures/Sequences”},
},
“Supply Chain”: {
“services”: {“IDaaS”,”OaaS”,”TaaS”,”ProvAaaS”,”InteropaaS”,”ACaaS”,”VaaS”,”DaaS”,”AnaaS”,”VizaaS”},
“standards”: {“GS1 EPCIS”,”RDF/JSON-LD”,”W3C VC”},
“anchors”: {“Batch Certificates”,”Cultures/Sequences”},
},
“Smart Cities & Infrastructure”: {
“services”: {“NaaS”,”IDaaS”,”OaaS”,”TaaS”,”ProvAaaS”,”InteropaaS”,”ACaaS”,”DaaS”,”AnaaS”,”VizaaS”},
“standards”: {“OGC”,”RDF”,”JSON-LD”,”W3C VC”},
“anchors”: {“Digital Certificates”,”Relevés/Specimens”},
},
“Energy Systems”: {
“services”: {“IDaaS”,”OaaS”,”TaaS”,”ProvAaaS”,”VaaS”,”InteropaaS”,”ACaaS”,”DaaS”,”AnaaS”,”VizaaS”},
“standards”: {“RDF/OWL”,”CFIHOS”,”OPC UA”,”ISO 15926″,”W3C VC”},
“anchors”: {“Digital Credentials”,”Material Samples”},
},
“Climate & Geoscience”: {
“services”: {“OaaS”,”TaaS”,”RaaS”,”ProvAaaS”,”InteropaaS”,”DaaS”,”AnaaS”,”VizaaS”},
“standards”: {“OGC”,”NetCDF”,”RDF”,”JSON-LD”},
“anchors”: {“Type Relevé”,”Specimens”,”Isotope Anchors”},
},
}
def build_overlay(group_name, sector_names):
nodes = []
edges = []
for s in sector_names:
meta = sectors[s]
nodes.append({
“sector”: s,
“services”: sorted(meta[“services”]),
“standards”: sorted(meta[“standards”]),
“anchors”: sorted(meta[“anchors”]),
})
for i in range(len(sector_names)):
for j in range(i+1, len(sector_names)):
a = sectors[sector_names[i]]
b = sectors[sector_names[j]]
shared_services = sorted(a[“services”].intersection(b[“services”]))
shared_standards = sorted(a[“standards”].intersection(b[“standards”]))
shared_anchors = sorted(a[“anchors”].intersection(b[“anchors”]))
edges.append({
“group”: group_name,
“source”: sector_names[i],
“target”: sector_names[j],
“shared_services”: shared_services,
“shared_services_count”: len(shared_services),
“shared_standards”: shared_standards,
“shared_standards_count”: len(shared_standards),
“shared_anchors”: shared_anchors,
“shared_anchors_count”: len(shared_anchors),
“overlap_score”: len(shared_services) + 0.5len(shared_standards) + 0.5len(shared_anchors),
})
return nodes, edges
overlay_specs = {
“Defense–Manufacturing–SupplyChain”: [“Defense & Security”,”Manufacturing & Supply Chain”,”Supply Chain”],
“SmartCities–Energy–Climate”: [“Smart Cities & Infrastructure”,”Energy Systems”,”Climate & Geoscience”],
}
manifest = {“name”: “UCLS Overlays”,”version”: “1.0”,”generated”: True,”groups”: {}}
all_edges, all_nodes = [], []
for group, members in overlay_specs.items():
nodes, edges = build_overlay(group, members)
all_nodes += [{“group”: group, **n} for n in nodes]
all_edges += edges
manifest[“groups”][group] = {“members”: members, “edge_count”: len(edges)}
def write_group_files(group, members):
nodes = [n for n in all_nodes if n[“group”] == group]
edges = [e for e in all_edges if e[“group”] == group]
df_e = pd.DataFrame(edges)
df_n = pd.DataFrame(nodes)
e_csv = base / f”overlay_{group}edges.csv” e_json = base / f”overlay{group}edges.json” n_csv = base / f”overlay{group}nodes.csv” n_json = base / f”overlay{group}_nodes.json”
df_e.to_csv(e_csv, index=False)
df_n.to_csv(n_csv, index=False)
e_json.write_text(json.dumps(edges, indent=2))
n_json.write_text(json.dumps(nodes, indent=2))
return dict(edge_csv=str(e_csv), edge_json=str(e_json), node_csv=str(n_csv), node_json=str(n_json))
file_index = {group: write_group_files(group, members) for group, members in overlay_specs.items()}
Combined
edges_df = pd.DataFrame(all_edges)
nodes_df = pd.DataFrame(all_nodes)
edges_df.to_csv(base / “overlays_all_edges.csv”, index=False)
nodes_df.to_csv(base / “overlays_all_nodes.csv”, index=False)
(base / “overlays_manifest.json”).write_text(json.dumps({**manifest, “files”: file_index}, indent=2))
Append markdown links
md_path = base / “ucls_directory_wordpress.md”
append_md = []
append_md.append(“\n\n—\n\n## Inter-Sector Overlays (UCLS)\n”)
append_md.append(“> Auto-generated overlay graphs showing shared services, standards, and anchors.\n\n”)
for group, files in file_index.items():
append_md.append(f”### {group.replace(‘–’,’ — ‘)}\n”)
append_md.append(f”- Edges (CSV): {Path(files[‘edge_csv’]).as_posix()}\n”)
append_md.append(f”- Edges (JSON): {Path(files[‘edge_json’]).as_posix()}\n”)
append_md.append(f”- Nodes (CSV): {Path(files[‘node_csv’]).as_posix()}\n”)
append_md.append(f”- Nodes (JSON): {Path(files[‘node_json’]).as_posix()}\n\n”)
append_md.append(
“### Combined\n”
f”- All Overlays — Edges (CSV): {(base/’overlays_all_edges.csv’).as_posix()}\n”
f”- All Overlays — Nodes (CSV): {(base/’overlays_all_nodes.csv’).as_posix()}\n”
f”- Manifest (JSON): {(base/’overlays_manifest.json’).as_posix()}\n”
)
if md_path.exists():
with md_path.open(“a”) as f:
f.write(“”.join(append_md))
action = “appended to existing WordPress MD”
else:
md_path.write_text(“# UCLS Inter-Sector Overlays\n” + “”.join(append_md))
action = “created new overlay MD”
{
“action”: action,
“wordpress_md”: md_path.as_posix(),
“groups”: file_index,
“combined”: {
“edges_csv”: (base/”overlays_all_edges.csv”).as_posix(),
“nodes_csv”: (base/”overlays_all_nodes.csv”).as_posix(),
“manifest_json”: (base/”overlays_manifest.json”).as_posix()
}
}
Key terms in plain language
Open a term for a concise explanation of language used on this page.
Cybersecurity
The practices and controls used to protect identities, devices, networks, applications, and data from unauthorized access, disruption, or manipulation.
Zero Trust
A security model that does not automatically trust a user or device because of its location. Access is continuously verified and limited to what is necessary.
SASE
Secure Access Service Edge combines networking and security capabilities in a cloud-delivered architecture so users and locations can receive consistent policy wherever they connect.
Identity and Access Management (IAM)
The systems and policies that determine who a user is, what resources they may access, and how that access is authenticated and reviewed.
Multi-Factor Authentication (MFA)
A login control requiring more than one form of verification, such as a password plus an authenticator app, security key, or biometric factor.
MDR / XDR
Security services and tools that monitor activity, investigate suspicious behavior, and help contain threats. MDR is managed detection and response; XDR correlates signals across multiple security layers.