For the SODA organizing committee, the primary goal was to promote open data; innovations and solutions came only second. Whereas for many other cities, their focus was on using SODA’s crowdsourcing model to solve problems. Open data was secondary. But does it have to be either/or? Is it possible to strike a better balance between the two?
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Mao Mingrui, Deputy Director of Information Center, Beijing Municipal Institute of City Planning and Design, praised SODA as a milestone in China’s open data process. He believed that SODA built a viable mechanism that drives data-providers to release “real stuff”, a mechanism that is scalable and can be used as a guide for other cities trying to create their own open data platforms. The success of the 2015 Smart Transport challenge saw an explosion of similar contests nationwide. Everybody hoped to launch a contest to pool great ideas and to create innovative solutions for transport and other problems.
But amid the fervor for big events, there were problems. Often than not the priority was given first to “application innovation”, then “open data”. There were even times that “open data” was simply missing, and people went back to the “black box”. It is not difficult to understand why. For the SODA organizing committee, the primary goal was to promote open data; innovations and solutions came only second. Whereas for many other cities, their focus was on using SODA’s crowdsourcing model to solve problems. Open data was secondary.
But does it have to be either/or? Is it possible to strike a better balance between the two?
If we think about it, it is real-life problems that bring open data and application innovation together. We need innovation because we want to solve problems. And to do that, we need data. Problems, application, and data form a complementary and mutually-enhancing triangle. For a data contest to succeed, it must be designed in such a way that the three elements are all factored in and the interests of different parties are met.
To be more specific, we should start with problems and innovate to target them. Only in this way can we create value for sponsors and data providers. In 2016, SODA made several attempts to achieve this goal. The theme of 2016 was City Safety. SODA invited three companies to talk about their needs, look at available data and raise questions. One of them was Bundstar Media, the company that operates the largest piece of LED screen on the Bund, the so-called “the Window of the Bund”. It set up a special award to look for partners for visualizing on the screen urban safety data. What’s more, to help participants better understand the problems that were raised and to solve them, SODA worked with Tongji DESIS Lab, studied design methodology and launched a data innovation design toolkit. Assisted by the toolkit, SODA held a Design SODA workshop series. Participants were asked to complete tasks to get to the bottom of these problems and to identify problems that can be best solved by innovation. They also had to very clear about what data they had and what challenges they faced.
In addition, in 2016, SODA also started to encourage data providers to put forward questions and release data accordingly. For example, SODA held a workshop on environment management inviting four municipal governmental agencies: Environmental Protection Bureau, Bureau of Meteorology, Water Bureau and Landscaping and City Appearance Bureau. Participants and government officials sat down to discuss the environment challenge the government was facing and helped government to find solution providers. After the workshop, one team had the answer to Water Bureau’s question of “how to better communicate water affairs information to the public?”. They proposed a plan to launch a data-driven Official Account on WeChat.
When innovation becomes more problem-oriented, data circulation correspondingly becomes more targeted. Nevertheless, even SODA’s crowdsourcing models are not without its limits. First, it’s not a regular data circulation mechanism. Second, it’s model is Closed Sharing, meaning data is shared in a closed environment (the contest) in the form of a limited number of licenses. We don’t know whether the SODA model would work for data providers and innovators going forward. It’s bad news for the city’s data innovation in the long run because without continuous, follow-up supply of data, there is no way for innovators to truly turn their ideas into reality. To move the data providers along the spectrum, from Closed Sharing to Open Sharing, even Open, we need to help them build a circulation mechanism that allows them to regularly release data for specific applications.
To tackle this problem, SODA is preparing to set up an interactive system named “Data Intelligence” and will gradually release Reports on Data Innovation. By focusing on specific datasets or challenges, harnessing innovative solutions emerging from competitions as well as SODA’s repertoire of data innovation programs, the system will analyze data’s application scenarios, the way it is combined and how often it is used. The aim is to help data-providers assess the potential value of the data they release, unearth new directions and thinking in data innovation, find potential partners who could add value to it and third-party data sources as well as tailor data circulation models to application scenarios.
SODA is also helping data-providers to explore ways in which they could benefit from open data. It carries out tests and sorts out data circulation details through SODA contests to establish an efficient and sustainable data circulation model. For example, SODA ran a branch challenge called “SODA+ New Finance” in partnership with the Special Committee on New Finance of Shanghai Services Federation in 2016. It is different from SODA challenges in contestants and rules. Only corporate contestants are eligible. The original “Creation+ Prototype” method has been replaced by a “Proposal+ Business Negotiation” method. This way the value chain of “Providing data to contestants—Contestants add value to it—Benefits accrue to data-providers” is more replicable in real-life situations. It’s also an opportunity to identify potential problems and modify the data circulation model. The Special Committee on New Finance finalized the data circulation model after the contest and provides long-term data support to different innovation teams through a market-based mechanism.
(Initial findings: Accidents often occur during rush hour with more accidents during morning rush than afternoon rush. Morning rush starts at 6 a.m., suggesting young people in Shanghai are quite hard-working. The number of accidents at midnight is proof of the bustling night life for people living in Shanghai.
In-depth Analysis: Examine when (month, day, hour) most accidents occur and where. For outliers, try to explain by looking at the specific situations such as pedestrian density and traffic flow.)
Free flow of data is conducive to a better understanding of problems and in turn drives innovation. In SODA competitions, most teams in the creation phase mine, analyze and visualize data samples to define the boundaries of specific problems. For instance, in the 2016 contest, Team 1403 from Wuhan University analyzed data to gain insights into when, where and under what weather conditions most traffic accidents occur. Insights gradually build up and are cross-checked. They serve as “weapons” for data-providers and stakeholders, help them better understand their operations and how data innovation resolves challenges. In turn, they will raise better questions to SODA, fueling innovation in contests.
The above in-depth analysis of SODA’s model suggests it is more cultivating an eco-system than running a challenge. Openness is at the heart of the ecosystem, which includes open data, an open innovation process and open collaboration between multiple entities in building the eco-system. Instead of promoting open data, data innovation and problem interpretation in isolation, SODA brings the three together by encouraging data release with innovative solutions, leveraging data to better understand problems and unleashing solutions based on better insights into the problem. This makes up a closed loop of resources, creating value with data in an integrated manner and establishing a healthy eco-system of data innovation.
Equipped with the above thinking, SODA will start afresh in 2017. It will reinvent itself from Shanghai Open Data Apps into Sino Open Data Apps, going beyond Shanghai to become an international data innovation brand. While creating a big data ecosystem in Shanghai, it will also serve more cities. By examining their data infrastructure, industry composition and social challenges, SODA will help them figure out how to encourage data release to combat real challenges and how to connect relevant stakeholders to build an ecosystem of data innovation.
Instead of choosing one topic every year, SODA will focus on specific challenges in four areas, i.e. future commerce, smart transport, green development and healthcare. It will sort out relevant data and link data-providers, developers and end users. By joining forces with them it will push the agenda forward and contribute to problem-solving. It will also set up SODA labs devoted to frontiers of data innovation. To remove barriers to data innovation and accelerate data sharing and use, it will launch funds to invest in the crowdsourcing of personal medical information, multi-source data fusion technology and so forth.
In addition, SODA will collaborate with industry-specific start-up competitions, incubators and industry associations. The goal is to provide expert guidance to SODA contestants so that they would understand pain point thoroughly and come up with targeted solutions. Linking experts from various industries to SODA teams creates many possibilities. They could work on certain projects together or they could bring in new people into the teams. Their ingenuity would be brought into full play as they try to address challenges in society and to build up expertise.
Solutions for public service and social governance problems face many difficulties for implementation. To tackle this, SODA will learn from international best practices, i.e. working with governments at all levels to craft innovative procurement and support models. For instance, Citymart by Sascha Haselmayer, transformed government tenders into an open challenge. The procurement fund goes directly to the winner. Another example is the Knight Prototype Fund. Usually it is difficult for developers of public-service programs to secure funding from the government and the market to test early-stage ideas. The KPF specializes in helping them to take ideas from concept to demo, securing the survival of many programs which would go on to obtain long-term investment.
SODA will also seek broader international cooperation in 2017. By connecting to the U.K., Switzerland, the U.S. and Singapore, to name just a few, it aims to introduce outstanding solutions to China from abroad and export Chinese innovations. In addition, it will conduct research and promote projects on open data, data standards and solution incubation in partnership with international organizations like the United Nations Development Program, the World Bank and the Open Data Institute to further drive data openness and unleash more innovative apps for specific business segments.
By implementing these plans, we believe SODA will further unlock the value of data and turn more data into bubbles of innovation with far-reaching implications.