7. Sustaining

In a sense, an OpenDRI engagement never ends: it just transforms into a new way of managing data about risk. When OpenDRI has been successful, governments and communities will have new tools and methods to collect and curate data about their exposure to natural hazards. They will have met the goals that the partners outlined in the design phase and adapted along the way.

Sustaining a changed way of working with risk data is the work of the host nation itself. However, sustaining change is difficult. Without continuous funding, communities of practice often fall back to using familiar, older methods; thought leaders move onto the next problem; and experts find opportunities to grow their skills further in new organizations. The risk for OpenDRI is that risk data becomes stale—that they no longer reflect the realities of fast changing urban environments and the vulnerability of a society to new risks.

OpenDRI’s designers take a practical approach to this problem, acknowledging that an occasional influx of energy and resources may be necessary to keep work going. The development partners who funded and catalyzed the change can take steps to ensure the effort remains vibrant and productive.

Objectives

The first and last task of the OpenDRI management team is to create the framework into which they can inject these bursts of sustaining energy. The sustaining phase creates an architecture for continued work. This design must include a plan for ongoing training, occasional funding for small projects, and a framework for champions to grow a locally owned, long-term, sustainable open data ecosystems,

A key problem between the scaling and sustaining phases is to determine when OpenDRI has met its intended goals. This task may not be easy. The original objectives set forth in the initial Concept Note may have shifted to more advanced risk thinking. As the pilots evolved into a larger efforts across greater areas, the effort may have grabbed the attention of high-level leaders, who want to continue low-cost, high-output work. This shift is itself a success, but also may require additional capacity building.

There is a point in the maturation of risk thinking that OpenDRI must clarify its scope to be around data collection and curation, not risk assessment. When tasks around OpenDRI become more focused on the analysis of data than the management of the data, OpenDRI can cede to other efforts in DRM capacity building and risk assessment.

The goals of the Sustaining phase can include:

• Creating opportunities for training and networking that increase the interconnections between members of the network of data collectors, curators, analysts, and decision makers.
• Building trust in the accuracy and authority of the data.
• Catalyzing the development of organizations around data collection and management, often as social enterprises.
• Funding small software development projects that extend the use and utility of OpenDRI data.
• Encouraging academic institutions to include OpenDRI training materials, software, and data in their curricula.
• Funding the start-up costs for Living Labs, where individuals from across the open data ecosystem can gather to work on start-ups, continue projects, and have a neutral space to work on inter-organizational problems.

What and Why

The mix of sustaining efforts may change over time, but they will also need to be tailored to the context. The operating principles include:

1. Increase not only the size of the network around OpenDRI, but the interconnectivity and capacity of each individual in that network. From social networks to the Internet, a principle from network theory has held true: A network’s value is proportional to the square of number of its nodes. In academic speak, this statement captures an observation: as the number of relationships in a network increases, the social capital of network increases not at a linear rate, but an exponential rate. In practical terms, it means that the more connections OpenDRI creates between ministries, analysts, data collectors, data curators, and communities, the greater value that network will bring to the individuals who join it. This is a network effect that OpenDRI needs to foster. See Metcalfe’s Law.

Ongoing Training

Development of Organizations around OpenDRI Data

Software Development around OpenDRI Data

Academic Partnerships

Who

How

Outputs

Sustaining OpenDRI initiatives is a new problem. All current projects remain funded through their pilot or scaling funding plans. None have built self-sustaining revenue streams. That said, several dynamics are creating living ecosystems around open data for resilience:

Use cases: The immediate usefulness of data and data platforms to problems in the country are the most important attributes for success of OpenDRI. While there are risk models that capture more of the complexity of the modeling process (e.g., CAPRA), these tools are build for experts. Most decision makers lack the technical training to use these tools. Hence, tools like InaSAFE are an emerging method of building “risk communication tools” alongside “risk modeling tools.”

Academic Partnerships: building GIS into curricula or creating training programs in local universities has proven an effective mechanism for instilling risk thinking into the current and upcoming generation of managers and government officials. Open data becomes a platform for the work in the class and builds a common understanding among multiple communities. This is particularly important for those that feed graduates into positions in local, provincial, and national government.

Living Labs. Building a community of users around social ventures, startups, and non-profits creates an ecosystem of users and developers who need mapping data and disaster data. Via Living Labs, projects are sustained over periods of time and incubated in a place with expert advice.