Open Research Questions Pool
A curated, categorical atlas of open research questions derived from this collection's research resources and merged modules. Use it to scope theses, policy briefs, grant proposals, or practitioner pilots.
How to use this atlas
- Select a category from the sidebar; scan questions; star candidates.
- Turn a question into a testable design: define units, indicators, datasets, and method.
- Cross-link to Module 8 topics (8.1–8.7) and earlier modules for evidence and methods.
1) Measurement & Indices
- How can a harmonised digital economy index balance comparability with context sensitivity across regions?
- What weighting strategies minimise bias across infrastructure, usage, inclusion, and outcomes pillars?
- Which proxy indicators best capture “meaningful use” beyond access (affordability, skills, utility)?
- How can uncertainty and timeliness be quantified and displayed in composite indices?
- What validation protocols (ground truth, out-of-sample tests) increase trust in national rankings?
- How should ESG metrics (e.g., CADiS) integrate into macro DE dashboards without double counting?
- Can we construct satellite accounts for compute, data, and emissions aligned to SNA 2025?
- What open-data pipelines are feasible for low-capacity statistical offices?
- How to measure cross-border digital trade when prices, provenance, and data flows are opaque?
Related: 8.4 Measurement Methods · 8.2 Publication Landscape
2) Data as an Asset & Accounting
- Which valuation methods (income, cost, market) are most robust for public-sector data assets?
- How should depreciation of datasets be modelled given drift, obsolescence, and legal constraints?
- What are credible approaches to value user-generated and community data in national accounts?
- How can data trusts/cooperatives share value while maintaining privacy and governance integrity?
- What indicators capture the productivity impact of data reuse and interoperability mandates?
- How to audit the macroeconomic impact of generative AI trained on public corpora?
- What are effective crosswalks between firm-level data inventories and national statistics?
- Which incentives increase voluntary disclosure of data capital on balance sheets?
Related: 8.3 Theoretical Frameworks · 8.1 Research Orientation
3) AI Compute & Infrastructure Economics
- Which indicators best capture compute equity (e.g., GPUs per million, public compute utilisation)?
- How do workload placement and scheduling affect carbon intensity, latency, and cost?
- What market structures drive concentration in training/inference supply chains?
- How should public compute hubs be governed for fair access and research impact?
- What blend of accelerators, memory, and interconnects minimises cost per useful token?
- How to measure productivity effects of AI adoption at firm, sector, and macro levels?
- Which policies expand access to specialised compute without distorting innovation incentives?
- How resilient are AI supply chains to shocks in power, water, or critical minerals?
- What metrics quantify knowledge spillovers from shared compute to local ecosystems?
Related: 8.6 AI Infrastructure · 8.7 Frontier Research
4) Sustainability & ESG
- What is the life‑cycle footprint (GHG, water, minerals) of AI services by workload and region?
- How to quantify and mitigate rebound effects from efficiency gains in data centres and networks?
- Which siting policies align grid constraints with data centre growth fairly and efficiently?
- How to design 24/7 clean energy procurement that reflects real-time grid conditions?
- What metrics capture circularity for hardware (repairability, reuse, material recovery rates)?
- How to price and disclose embodied emissions in AI models and digital services?
- What environmental justice impacts arise from data centre clustering and how to mitigate them?
Related: 8.5 Sustainability Metrics · 8.6 AI Infrastructure
5) Inclusion & Human Capital
- How to operationalise “meaningful digital inclusion” across affordability, skills, and agency?
- Which interventions most effectively convert access into usage quality and income mobility?
- How should digital public infrastructure (ID, payments, data exchanges) be evaluated for equity?
- What metrics capture accessibility and safety for women, youth, and marginalised groups?
- How does AI augment or displace work across occupations; what reskilling models scale?
- Which financing instruments (outcome-based, blended) can scale inclusive transformation?
Related: 8.1 Research Orientation · 8.2 Publication Landscape
6) Governance & Policy
- What governance models balance innovation with accountability in AI deployments?
- How do data localisation and cross-border regimes affect growth, competition, and inclusion?
- Which antitrust tools address platform and compute concentration without stifling scale economies?
- How to design public procurement that catalyses interoperable, open digital ecosystems?
- What metrics should underpin AI risk classifications and audits in high‑risk sectors?
- How to align national strategies with global standards to reduce compliance fragmentation?
Related: 8.7 Frontier Research · 8.3 Theoretical Frameworks
7) Platforms & Agentic Internet
- What economic effects emerge as autonomous agents transact goods, services, and data?
- How to prevent collusion, manipulation, or systemic risks in agentic marketplaces?
- Which standards enable safe interoperation between agents, APIs, and payment systems?
- How do content provenance and watermarking affect misinformation dynamics?
- What business and governance models enable impact‑oriented agentic public goods?
- How should liability be allocated among model providers, deployers, and agents?
Related: 8.7 Frontier Research · 8.3 Theoretical Frameworks
8) Privacy, Security & Trust
- What is the efficacy and cost of privacy‑enhancing technologies at national‑statistics scale?
- How to balance security logging with data minimisation in critical digital infrastructure?
- Which governance patterns reduce insider risk and model exfiltration in AI stacks?
- How to measure and improve algorithmic transparency and contestability for citizens?
- What assurance frameworks certify safe AI/agent behaviour across domains?
Related: 8.7 Frontier Research · 8.4 Measurement Methods
9) Regions & Development
- Which low‑cost indicators can track digital transformation in data‑scarce environments?
- How to design compute and connectivity policies for small states and land‑locked regions?
- What models crowd‑in private investment for inclusive digital infrastructure?
- How to quantify spillovers from regional innovation hubs and tech parks?
- Which cross‑border data/compute corridors unlock regional value chains?
Related: 8.1 Research Orientation · 8.2 Publication Landscape
10) Supply Chains & Geopolitics
- Where are the chokepoints for critical minerals, components, and neon gases; how resilient are they?
- What is the risk/return profile of friend‑shoring vs reshoring for semiconductor ecosystems?
- How to model cyber‑physical risks across subsea cables, IXPs, and cloud regions?
- Which policy mixes reduce geopolitical exposure without undermining openness?
- How to measure security externalities of cloud region placement and concentration?
Related: 8.6 AI Infrastructure · 8.5 Sustainability Metrics
11) Methods & Causality
- What quasi‑experimental designs reliably identify causal effects of digital policies?
- How to combine administrative, platform, and remote‑sensing data for robust inference?
- Which evaluation methods best measure complex, multi‑actor platform interventions?
- How can participatory and mixed‑methods approaches improve construct validity?
- What open tooling lowers barriers to reproducible DE research in low‑resource settings?
Related: 8.4 Measurement Methods · 8.3 Theoretical Frameworks
12) Emerging Technologies & Architectures
- Which edge–cloud topologies optimise cost, latency, privacy, and carbon?
- How to measure economic impact of open‑weight vs closed‑weight model ecosystems?
- What benchmarks meaningfully evaluate agent performance on real‑world tasks?
- How do novel packaging and memory technologies alter compute economics?
- What are credible pathways to post‑CMOS and their policy implications?
Related: 8.6 AI Infrastructure · 8.7 Frontier Research
Turn a question into a study
- Define population, unit of analysis, and time horizon.
- Pick indicators and data sources (open, administrative, commercial).
- Choose a method (quasi‑experimental, structural, simulation, mixed).
- Pre‑register a plan; open‑source code and metadata.
- Link findings to the Module 8 roadmap (Topic 8.7) and policy levers.