The data tracking mechanisms to inform the public about the spread of Coronavirus COVID-19 provide useful insights for the sustainability community of organizations working to mitigate the impacts of environmental and social challenges.
How can sustainability organizations use data to address urgent and critical global challenges?
The COVID-19 GIS interactive dashboard looks similar to dashboards created to address sustainability challenges, yet sustainability organizations still face operational and data management challenges that hinder data contributions to such efforts. These lessons from the COVID-19 dashboard are useful for sustainability organizations:
- Manual data tracking mechanisms are unsustainable for global issues that require coordinated solutions.
- Tackling global issues requires a data strategy.
- Multiple trusted data sources are critical in forming a more detailed picture of global challenges.
- Open data is the only way that data in the public interest can be delivered at the speed, scale, and periodicity necessary to enable effective responses to global issues.
Background on the COVID-19 GIS Dashboard (Updated February 11, 2020)
In response to the ongoing public health emergency, Johns Hopkins University developed an interactive web-based dashboard hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. The dashboard visualizes and tracks reported cases of COVID-19 in almost real-time. It was first shared publicly on January 22 and illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. Cases are reported at the province level in China, city level in the U.S., Australia and Canada, and at the country level otherwise.
The dashboard was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. Further, all the data collected and displayed is made freely available, initially as Google Sheets, now in a GitHub repository, along with the feature layers of the dashboard, which are now included in the ESRI Living Atlas.
What could sustainability organizations learn from this dashboard to advance their missions?
1. Manual data tracking mechanisms for global issues requiring coordinated solutions are unsustainable.
‘From January 22-31 the entire data collection and processing was managed manually. During this period, the number of updates were typically conducted twice a day, both morning and night (Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable, and on February 1, we adopted a semi-automated living data stream strategy.’
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For sustainability professionals, the situation described above illustrates a high-speed scenario on the limitations of data collection methods we use today to address critical social and environmental challenges. While sustainability data is increasingly collected in digital formats, it is often still manual data collection. This is because without rules for systematic collection and consistent formatting, the data is not easily accessible or retrievable on a consistent basis. Unfortunately, this makes data sharing and use difficult while undermining the value of sustainability efforts in the digital age where data sits behind evidence of impact.
2. Tackling global issues requires a data strategy.
Another lesson we can learn from the development of the COVID-19 dashboard is that starting small, where you are, is usually the only way to start creating value with data. For the dashboard, this meant starting with manual collection of available data in China where the outbreak began. For sustainability organizations like sustainability standards, a place to start could be using a few key data streams or reports (e.g. reports to supply chain actors about certified product volumes) to realize value in using sustainability data. In broader sector initiatives like LandScale, a landscape-level sustainability initiative, the starting place could be data capture and reporting over time for a few key impact indicators at the landscape level.
The next useful step when it is clear that much broader collaboration on data is needed, is developing a plan of action with data or a data strategy. We already know that we need broader collaboration using data to address sustainability challenges. Collaboration can include data sharing among organizations working on tackling the same sustainability issues or sharing of insights in the use of trusted external data sources such as the World Database on Protected Areas. Some organizations are developing data strategies to make the most effective use of their sustainability data assets. However, a broader dialogue about a sector-wide data strategy for sustainability is needed. How can we work effectively to create a broader sustainability sector data strategy to address complex challenges more efficiently?
Admittedly, the difference with the COVID-19 pandemic and sustainability challenges is that defining the challenge and solutions (e.g. mitigating the spread of COVID-19) can be more complex for sustainability issues. Nevertheless, a good start lies in defining data products or services to describe and illustrate key challenges like deforestation, species loss, and forced labor so that charting a collective effort towards solutions is possible.
Defining data use goals or objectives (data for what?) by first exploring data products and services offered to stakeholders is an important first step in data governance. This step helps to set the direction and scale of data-related efforts so that organizations can understand their data, including how it flows and to whom. It is the first step in creating value with data on a consistent basis (e.g. more informed decision-making and high-quality impacts evidence reports).
3. Multiple trusted data sources are critical in forming a more detailed picture of global challenges.
‘Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide COVID-19 cumulative case totals in near real-time at the province level in China and country level otherwise.
Every 15 minutes, the cumulative case counts are updated from DXY for all provinces in China and affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau and Taiwan), we found DXY cumulative case counts to frequently lag other sources; we therefore manually update these case numbers throughout the day when new cases are identified.
To identify new cases, we monitor various twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers using regional and local health departments, namely the China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, European CDC (ECDC), the World Health Organization (WHO), as well as city and state level health authorities. For city level case reports in the U.S., Australia, and Canada, which we began reporting on February 1, we rely on the US CDC, Government of Canada, Australia Government Department of Health and various state or territory health authorities. All manual updates (outside mainland China) are coordinated by a team at JHU.’
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See the data sources for the COVID-19 GIS Dashboard.
Coordinated global data initiatives rely on a range of information sources. In the case of the COVID-19 virus, Johns Hopkins University relies on a range of official public health sources to report on the spread of the virus. Naturally, they go to national government sources collecting the most authoritative data on the health of their populations.
Trusted sources may be more numerous and nuanced in the case of sustainability challenges, which is why collaboration across organizations is also useful so we can share which data sources are commonly used for decision-making. Knowing which data sources various organizations use has an added benefit. These sources can then become a foundation for broader collaborations on data such as for data dashboards. For sustainability challenges, what are the set of trusted sources of global data on deforestation, species loss, child labor, and other major sustainability issues?
A good example of data collaboration among trusted sources is the ISEAL Certification Atlas which brings together geospatial data from sustainability standards across a range of sectors. Initiatives such as Data Collaboratives are also emerging to build data collaborations.
Besides knowing about shared data sources, it is also important to be aware of how these sources are maintained and licensed for use by your organization for decision-making. Data licensing and data policy are important elements of data governance. Basing management decisions on external data sources requires careful vetting to ensure decisions are based on high-quality data that is regularly updated using good data management practices. How could sustainability organizations work together to identify key data sources and use them in a coordinated way?
4. Open data is the only way that data in the public interest can be delivered at the speed, scale, and periodicity necessary to enable effective responses to global issues.
‘Further, all the data collected and displayed is made freely available, initially as Google Sheets, now in a GitHub repository, along with the feature layers of the dashboard, which are now included in the ESRI Living Atlas.’
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What if the COVID-19 dashboard team had to negotiate data-sharing contracts with each national government before they could access and publish data on new cases of COVID-19? It is easy to make the case for global public health data to be open and available for the benefit of improving the health and longevity of people. But what about sustainability data needed to address issues critical for the sustainability of our environment and life on earth? More data could be made available to the public from sustainability standards and other sustainability organizations to speed sustainability solutions and collaborations.
While open data practices have not taken root among sustainability organizations, open data is the only way we can trigger meaningful, large scale ripple effects with sustainability data. It is also the only practical approach to operationalizing an agile data policy where an organization knows its data intimately, identifies its legal obligations to share it, and understands how it can create value by making its data available for use by a wide range of stakeholders. Data governance can help organizations understand their data streams and set objectives to help them craft data policies that advance their missions. Does your organization have a public-facing data policy indicating how available data and information can be shared and used? Is an open data policy being considered at your organization?
Most organizations are currently still focused on understanding their data in order to manage it responsibly, especially in light of the EU’s General Data Protection Regulation (GDPR). This new regulation puts focus on the identification of the personal data an organization holds and processes, on the development of privacy and data policies, and on adapting legal terms in data sharing and general service agreements to reflect personal data rights and uses.
While the COVID-19 dashboard informs us about a global pandemic of immediate urgency, the same principles and conditions for data collection, use and sharing impact sustainability organizations and the issues where they want to make an impact.
If this article resonated with you regarding your organization’s use of data, please share your reflections and thoughts. Some questions where I would appreciate your input:
- Would access to a vetted list of sustainability data sources be helpful for your organization’s data efforts and decision-making?
- Would you be interested in an initiative that coordinates data sources and data sharing by organizations for specific sustainability issues?