Geneva, 19- 20January 2016
PTC-2016/Doc. 4.1(1)/5
4.1Inter-Commission issues
4.1(1)Decisions of the Seventeenth World Meteorological Congress (Cg-17) in matters related to inter-commission issues
Emerging data challenges for WMO Stakeholders
Resolution 65 (Cg-17) decides to undertake a review of the challenges and risks, opportunities and benefits related to big data, crowd-sourced data, social media as well as emerging and future data sources, and their potential impact on Members, as the basis for production of a guidance document for Members, and requests the Commission for Basic Systems, in coordination with other technical commissions, in particular the Commission for Hydrology, to undertake the review;
Resolution 7 (EC-67) decides to establish an Executive Council Task Team on Data Policy and Emerging Issues and that the Task Team shall include representation by the Commission for Climatology, the Commission for Basic Systems, the Commission for Hydrology, the Commission for Agricultural Meteorology, the Commission for Atmospheric Sciences and the Commission for Aeronautical Meteorology – nominated by the presidents of these Commissions – among its members.
Presidents of technical commissions are invited to contribute elements for a terms of reference and work plan for implementing the review.
Background
The abridged report of Cg-17 pp. 205-206 lays out three emerging areas, presenting various challenges, risks and opportunities in areas related to big data, crowd-sourcing and social media.
Big data is defined in two ways: 1) Big "scientific" data are formally collected, structured data. Examples include NWP and climate model-related data, radar and satellite data. These have associated information about the data (metadata) that is relevant to the application area, such as quality information or a description of how the data were derived. Key challenges with this type of data include storing, processing in a short time, moving the information, and in delivering to users only the components relevant to them. 2) Big "opportunity" data are informally collected and unstructured. Examples include messages on social media and measurements obtained from instruments that are deployed for non-meteorological purposes (such as sensors in mobile telephones). There is often only poor knowledge about the technical and environmental characteristics of these data, or a weak link between the data and the meteorological information that might be derived. Here the challenges are in extracting relevant and useful information from the data; the meteorological information will often only be derived using aggregation and statistical approaches which may be driven by marketing or other non-meteorological purposes.
“Crowd-sourcing’ is the process of obtaining data, services, ideas, or content by soliciting or capturing contributions from a large group of people, and especially from an online community. While crowd-sourcing will not replace high quality observations, especially for climate and where traceability and accountability is important, it is potentially an innovative way to collect large amounts of data and non-conventional observations such as impact reports, particularly during significant events.
“Social media” allows people to create, share or exchange information in virtual communities and networks. Social media provide a wealth of environmental observations and information that could be used for supplementing meteorological forecasts and warnings. Challenges may arise with regarding how NMHS data processing systems can accept and process these novel types of data. Mobile phones and other devices will provide an ever-growing source and volume of real-time digital data.
Issues for potential consideration during the review, drawn mainly from the Cg-17 report, include:
- Identification of non-traditional data sources and the emerging opportunities to access and utilize these data and to manage the complexity of processing, use, distribution and security as well as laws concerning privacy and propriety
- Identification of appropriate ways through which the meteorological and hydrological community can benefit from enhancements in the access, exchange and use of data beyond what can be achieved by existing methods
- Assessment of the implications of the data sources identified for the practices, policies and capabilities within individual meteorological institutions in relation to the lifecycle management of data, to ensure that Members are able to manage their observations and data efficiently and effectively, to extract the value from the data in support of their services, and to integrate observations and data from diverse platforms and from external sources, ref. the WMO Integrated Global Observing System (WIGOS) and the WMO Information System (WIS)
- Identification of potential partnerships e.g. with the private sector such as the airline industry or big data/social media companies, that could benefit WMO and its Members through potential complementarities.