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The purpose of this paper is to discuss how, despite increasing data availability from a wide range of sources unlocks unprecedented opportunities for disaster risk reduction, data interoperability remains a challenge due to a number of barriers. As a first step to enhancing data interoperability for disaster risk reduction is to identify major barriers, this paper presents a case study on data interoperability in disaster risk reduction in Europe, linking current barriers to the regional initiative of the European Science and Technology Advisory Group.

In support of Priority 2 (“Strengthening disaster risk governance to manage disaster risk”) of the Sendai Framework and SDG17 (“Partnerships for the goals”), this paper presents a case study on barriers to data interoperability in Europe based on a series of reviews, surveys and interviews with National Sendai Focal Points and stakeholders in science and research, governmental agencies, non-governmental organizations and industry.

For a number of European countries, there remains a clear imbalance between long-term disaster risk reduction and short-term preparation and the dominant role of emergency relief, response and recovery, pointing to the potential of investments in ex ante measures with better inclusion and exploitation of data.

Modern society is facing a digital revolution. As highlighted by the International Council of Science and the Committee on Data for Science and Technology, digital technology offers profound opportunities for science to discover unsuspected patterns and relationships in nature and society, on scales from the molecular to the cosmic, from local health systems to global sustainability. It has created the potential for disciplines of science to synergize into a holistic understanding of the complex challenges currently confronting humanity; the Sustainable Development Goals are a direct reflectance of this. Interdisciplinary is obtained with integration of data across relevant disciplines. However, a barrier to realization and exploitation of this potential arises from the incompatible data standards and nomenclatures used in different disciplines. Although the problem has been addressed by several initiatives, the following challenge still remains: to make online data integration a routine.

The purpose of this paper is to examine insurance regulation theories, regulatory agency structures and measures.

This study investigates significance of regulatory agency structure, key regulatory measures, political stability and cultural dimension in insurance markets of 56 developed and developing countries for 2005‐2009.

It was found that insurance consumption is lower in countries with an authority exclusively for insurance regulation but life insurance consumption is higher when the agency is part of government or when another agency is jointly responsible for insurance regulation. Market entry regulation leads to lower consumption whereas market exit regulation has the opposite effect. Solvency regulation and required use of standard forms for insurer financials lead to greater consumption of insurance. A positive impact on the nonlife market is observed for accounting regulation and regulator's intervention power.

Price control regulation may lower consumption of insurance whereas tariff rating brings about a rise in the consumption. Regulation of insurance intermediaries or corporate governance may lower insurance consumption whereas the requirement that insurers employ an actuary or actuaries gives rise to the consumption.

The author found no difference between OECD and non‐OECD countries. However, corruption‐freeness and inflation impact insurance consumption. Using OECD country data only, a negative impact was found of the single agency structure and tariff regulation in the life insurance market and a positive impact of regulation by two or more agencies in the life insurance market and of price control regulation in the nonlife insurance market. Corruption‐freeness positively affects the loss ratio in the life insurance market and the combined ratio in the nonlife insurance market.