Examples are:

• Education
• Healthcare
• Energy
• Water Resources Management
• Transportation
• Information and telecommunications
• Waste and Contaminants Management
• Banking and Finance
• Emergency Services

These infrastructures are socio-technical because they cannot achieve their aims or perform their functions without human agents, technological artifacts, and effective socio-political institutions in place. That is, their performance is determined by the interactions of:

1. technical systems, including equipment or machineries, processes, operational procedures and physical arrangements
2. social systems, including human behavioral and value systems, human performance and cultures
3. socio-institutional systems, including legal, political and enforcement institutions

Modelling and engineering large-scale, critical socio-technical infrastructures

A difficult, almost intractable, challenge facing many countries is how to maintain sufficient capacity and reliability levels of critical sociotechnical infrastructures to address demand dynamics resulting from demographics, urban development patterns, economic, environmental concerns, and technological advancement over time. The challenge is particularly strenuous for developing countries where increasing costs of delivering the services coupled with low investment and technical capacity as well as social and cultural factors thwart opportunities for achieving minimum required capacity and adequate reliability thresholds for the services. Uncertainty of regulations, rapidly changing global markets, and chaos – diminishing trust in the organizations and government, refusal to pay for poor irregular services, illegal conducts, sabotage, protests and civil conflicts - further constrain the ability of developing countries to transform their critical socio-technical infrastructures into efficient and reliable operations as is necessary for continued economic growth, greater access to markets and social mobility over time.

An important characteristic of the problem rarely addressed by planners, analysts, and decision-makers is interdependence. The factors identified above area interdependent as are the infrastructures. Thus, transforming critical socio-technical infrastructures into efficient and reliable operations cannot be easily planned and requires more than increasing development aid and/or increasing public and private capital. Disruptions (deliberate or accidental) or interventions in one of them affect the whole, but the relationships and interactions that make up the complex network that they collectively form cannot be known in advance. Nor can it be easily predicted how injections of capital, regulatory changes, and chaos affect productivity, efficiency, dependability in development aid, and instability over time. Therefore, our ability to model and analyze the behaviour of these infrastructures, individually and collectively, is pivotal. Building the models and performing the analysis, however, is a portentous task even in countries with a lot of resources and highly advanced scientific and technological capacities like the USA:

1. each infrastructure is itself an adaptive and emergent network of heterogeneous and distributed operations
2. infrastructures are dependent and always evolving
3. the systems and their environments involve dynamics, feedback loops and imprecision
4. acquisition of timely and reliable data is difficult
5. the synergistic structure cannot be described without describing each of the individual infrastructures, and each infrastructure must be described in relation to the others.
6. the modelling process is multi-domain, usually involvinggovernment agencies, businesses, community-based groups and academia
7. modelling requires multidisciplinary collaborative research that transcend traditional approach and make complexity science integral part of the problem-solving process

Many developing countries in Latino America and Africa, for example, have fledging research infrastructures, which constraint their capacity to perform innovative and breakthrough work to support decision-making processes. Nevertheless it is critical to understand the potential consequences of infrastructure interdependencies and the dynamics and mechanisms of the networks embedded in these infrastructures. It is also necessary to understand the interactions between the dynamics of the infrastructures’ states and the capacity of the PR-VNets to increase access and greater social involvement with markets over time. Without this understanding, innovation is difficult.

The United States is not insulated from the threats facing developing countries as their economies and national securities grow more interdependence over time. At the same time, the US must improve the quality and efficiency of the education systems, reduce costs and increase access to healthcare, reduce environmental hazards, increase the reliability and efficiency of the energy systems, and develop alternative sources of energy to remain competitive, provide better security, and improve the quality of life. Hence, collaborating in the search for optimal solutions to common problems is beneficial for the USA and developing countries.

Two programmes—Databases for Development (DAforDEV) & Network for the optimization of NGOs operations (NONGOSO)—being developed at COSOLA seek to:

1. help increase research capacity in developing countries – with emphasis in the Dominican Republic - to develop modelling and analysis tools that can advance understanding of the structures and dynamics of critical sociotechnical infrastructures and their interdependencies
2. develop decision-support and research-support data systems—databases for development—to increase access to timely and reliable data and improve the modelling process.