6. Scaling

Pilots demonstrate new possibilities. They allow partners to see firsthand how cost effective, fast, and comprehensive the OpenDRI engagement can be. Pilots can also expose challenges of the local context. In either case, there will emerge a point where the partners to OpenDRI will discuss whether to scale the initiative and where the strategic areas of expansion might be.

This chapter explores scaling two OpenDRI tactics: open government risk data and community mapping.

Objectives

Taking a pilot from one city to other areas of a country is usually done by seeding multiple pilots.

What and Why

Who

How

Outputs

Data Catalogue

After early adopters have added data to a data catalogue, the slow process of building an ecosystem of users begins. The sign for this work to start is if a champion has loaded data and a user base begins to use the data catalogue to solve immediate problems. The usage indicates that the pilot happened in a fertile environment for additional work.

In general, there are three approaches to scaling open government risk data:

• Expanding the number of data catalogues. Data catalogues no longer need to be centralized. Instead, they can form a confederation of catalogues. In this way, each ministry can own and curate its own data, and choose what data to make available to whom. The confederation of catalogues might offer other ministries very different access rights than the rights afforded to the general public.
• Increasing data sets within each data catalogue. Often the initial data sets are limited to information which is considered to be low risk and high reward for its release. Expanding the data available in each catalogue will work towards data which might have lower rewards or higher risks for its release.
• Increasing interconnections. The density of the interconnections between data will greatly affect the perceived value of the network. Each data set can be viewed as a LEGO(tm) piece. When topolography data from one ministry can be combined with meteorological forecasts and river gauge data, flood models can more accurately predict flood damage from an upcoming storm seasons.

In each case, planning how to scale requires considering several factors:

• Meeting the use cases of partners. The availability of data often exposes new use cases, many of which may have additional data needs.
• Building relationships with gatekeepers to other data sets. Data catalogues often become gravity wells for information: they pull others with data toward growing supernodes. This credibility enables the OpenDRI to locate islands of data which may be considered core to DRM, but may be held outside of government (often survey or GIS firms). Negotiating the release of these data sets has sometimes proven to be relatively easy when there is a place to host the data without cost to the gatekeepers.

Building Policies to manage linked open data

When ministries begin sharing data that has previously been closed, policy and legal question often arise. Some of these issues center on access, privacy, and standards. The OpenDRI team will need consider several questions:

• Access. Who can view the data? Do some data need to be kept private for security reasons (such as some data about nuclear power plants)?
• Privacy. What the data alone or as a mosaic reveals about others? Do the data reveal information about citizens that needs to be kept private? How can the data be released for DRM purposes in ways that protect citizen privacy?
• Standards. What is the national standard for certain data types? Do ministries use formats that are compatible with each other? What is the cost of translating data from one format to another as it now moves from ministry to ministry and outside partners? If there are problems with standards and data translation, what is the standard that the nation will follow?
• Metadata. How can users find the data they need? Metadata provides a common language to describe the data. In this way, experts in various specialties can define their vocabularies and enable others to find the data that they need.

Building Curation capacity and QA/M&E

As data scales in size and interconnection, the challenges of curating it increase. When a system is flooded with high volumes of poor quality data, it becomes far less useful than it was when it started with a few solid datasets. The Data Curator needs to become the steward of the data. He or she will not only add new data, but also removing data that has become stale, cleanse data that contains errors in accuracy or formatting. The Data Curator will need to establish and apply data typologies and hiearchies. The Data Curator’s role is to leave data better than he or she found it. The Quality Assurance capacity and M&E around OpenDRI need to be tied to the quality, findability, and usage of the data under curation. OpenDRI is developing a guide to this curation process.

Community Mapping

Research indicates that scaling community mapping efforts is generally a process of building additional pilots, then interconnecting them. This strategy roughly parallels grassroots organizing, when organizers carry the effort from one place to the next, building a larger national effort along the way.

Expanding each site

Each new pilot will generally start by cloning the previous cities, with customizations to context. Some areas of customization include architectural traditions of a particular city, natural hazards in the specific place, language, and custom.

Preparing pilots be sustainable entity

The communities that come together to collect exposure data are not meant to be a one-off. They must curate that data over time to create a viable risk management ecosystem. While the costs are low, these organizations need to sustain a small set of paid leaders around a network of volunteer surveyors. The OpenDRI team needs to consider strategies to fund and sustain these efforts. To date, all pilots are still working off pilot funding and none have developed revenue models in either the not-for-profit or for-profit spaces. Some groups might well be able to develop social ventures/social entrepreneurship models.

An important element of current work is partnerships with local universities. By integrating risk assessment into the curricula of geospatial and structural engineering courses, the OpenDRI team has been able to expose the next generation of government officials, engineers, and analysts to thinking about risk in terms of probable futures. Students have become an important source of volunteers, especially as they seek to gain experience in a new set of skills.

Data Quality Reports with Universities

As efforts scale, the dataset becomes an attractive subject for research by local academics. At the same time, the ecosystem often desires a third-party assessment of the quality of the growing data, along with recommendations about how to remedy any errors. OpenDRI team has had success contracting with local academic institutions to perform a QA study on community mapping data. One such report was done by UGM in Indonesia. It catalyzed a change to the conversation about community mapping in the client government, which subsequently expanded its use of OpenStreetMap.

Open Data Working Group

Outputs

TBD

Case: Indonesia: Mapping Jakarta for $20,000 USD

Scaling from Pedang to Indonesia