Data Model
Essential Variables
Expert-Based Approach
Goal-Based Approach
Gap Analysis
Virtual Stakeholder Table
Related Projects

Functionality and Design of the initial version of the SEE-IN KB

The SEE-IN KB is a core element of the GEOSS KB focussing on the chains and networks that connect societal goals, targets, and indicators with Essential Variables and the datasets, products and models that support the monitoring and implementation of these targets and goals. The functions of the SEE-IN KB include the identification and documentation of societal knowledge needs and the resulting observational requirements, the support of user access to existing observations and services meeting knowledge needs, and tools for gap analyses.

A core function of the SEE-IN KB is to facilitate the linkage of societal goals and targets to the EVs. The targets are connected to indicators that are report cards for the progress towards the targets and a planning tool for measures to achieve the targets. EVs need to be monitored in order to allow a quantification of the indicators.

Main Functional Areas of the SEE-IN KB

The main functional areas of the SEE-IN KB include:
  • Publish:
  • Search:
  • Analyze:
  • Network:
  • Make Decisions:
Figures to be added here.

Identifying User Needs

The best way to get to know the users and to capture and understand societal information and knowledge needs is to listen to stakeholders engaged in addressing societal tasks and challenges. An understanding how users make use of information derived from Earth observations and what type of information and knowledge they want, need and create can be developed by observed users while they access and use such observations and derived information. Therefore, the SEE-IN KB aims to become a collaborative platform where decision and policy makers can access and use Earth observations and derived information. By bringing the providers and users together on this collaborative platform, it will be possible to “learn” how decisions and policies are informed by Earth observations and derived information, how Earth observations and models are used to create practice-relevant knowledge, and where the gaps are that need to be addressed.

The design of such an collaborative platform that is of value and attractive for both users and providers and at the same time capable of learning from the activities of users and providers on this platform has to be innovative. Designing the platform is challenging. However, achieving the necessary revolution in how Earth observations are informing decision requires this innovation.