Deontic Knowledge Graphs for Privacy Compliance in Multimodal Disaster Data Sharing

Disaster response requires sharing heterogeneous artifacts, from tabular assistance records to UAS imagery, under overlapping privacy mandates. Operational systems often reduce compliance to binary access control, which is brittle in time-critical workflows. We present a novel deontic knowledge graph-based framework that integrates a Disaster Management Knowledge Graph (DKG) with a Policy Knowledge Graph (PKG) derived from IoT-Reg and FEMA/DHS privacy drivers. Our release decision function supports three outcomes: Allow, Block, and Allow-with-Transform. The latter binds obligations to transforms and verifies post-transform compliance via provenance-linked derived artifacts; blocked requests are logged as semantic privacy incidents. Evaluation on a 5.1M-triple DKG with 316K images shows exact-match decision correctness, sub-second per-decision latency, and interactive query performance across both single-graph and federated workloads.

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Publication Details

Journal
Maryland Shared Open Access Repository (USMAI Consortium)
Published
2026-01-07
DOI
https://doi.org/10.13016/m2ij9y-gdyy
Primary Topic
Advanced Graph Neural Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Deontic Knowledge Graphs for Privacy Compliance in Multimodal Disaster Data Sharing

Karuna Pande Joshi, Kelvin Uzoma Echenim
Maryland Shared Open Access Repository (USMAI Consortium)
Advanced Graph Neural Networks
article

Deontic Knowledge Graphs for Privacy Compliance in Multimodal Disaster Data Sharing

Karuna Pande Joshi, Kelvin Uzoma Echenim
article en

Abstract

Disaster response requires sharing heterogeneous artifacts, from tabular assistance records to UAS imagery, under overlapping privacy mandates. Operational systems often reduce compliance to binary access control, which is brittle in time-critical workflows. We present a novel deontic knowledge graph-based framework that integrates a Disaster Management Knowledge Graph (DKG) with a Policy Knowledge Graph (PKG) derived from IoT-Reg and FEMA/DHS privacy drivers. Our release decision function supports three outcomes: Allow, Block, and Allow-with-Transform. The latter binds obligations to transforms and verifies post-transform compliance via provenance-linked derived artifacts; blocked requests are logged as semantic privacy incidents. Evaluation on a 5.1M-triple DKG with 316K images shows exact-match decision correctness, sub-second per-decision latency, and interactive query performance across both single-graph and federated workloads.

Maryland Shared Open Access Repository (USMAI Consortium)
Climate action
Openalex Percentile: Top 68%
Advanced Graph Neural Networks
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