Data-Interoperability Maturity Forecasts for 78 Organizations, 2026-2035

A calibrated dataset of 78 organizational units across government, healthcare, education, and finance, used to forecast the operational value of data-interoperability maturity. The dataset includes an Interoperability Maturity Index, operational cost index, data-exchange cycle-time measure, and sector classification, calibrated from literature. It was created by Helen Dian Fridayani and published on figshare in 2026, with replication code for scenario modeling and Monte Carlo simulations.

Use Cases

• Forecasting operational efficiency gains based on the Interoperability Maturity Index.
• Comparing sectoral impacts of data-interoperability adoption based on sector classification.
• Simulating cost and cycle-time outcomes under different adoption scenarios using the provided Monte Carlo code.
• Benchmarking organizational units against literature-calibrated value ranges for maturity and cost.

Strengths

• Dataset is calibrated to value ranges reported across five literature domains, including e-government and health information exchange.
• Includes replication code for log-linear efficiency models, scenario forecasts, and figure generation, supporting full reproducibility.
• Covers 78 organizational units across four key sectors: government, healthcare, education, and finance.

Limitations

• Dataset is literature-calibrated rather than collected from primary field observations, which may limit real-world accuracy.
• Row count for the main dataset is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred from the data dictionary after download.

Provenance

Source

Helen Dian Fridayani via figshare.

Collection Method

Constructed using a fixed pseudo-random seed and calibrated from literature.

Time Range

Forecasting horizon from 2026 to 2035.

Freshness

Last updated 2026-06-03 16:07:04; freshness should be verified.