# A Novel ICT Framework for Sustainable Development Goals
## 5 The ICT Framework Description
### Data Module  
This module aims:  
* To collect, prepare, analyze (compute and transform), visualize, manage and preserve data from three sources: statistical, sensor, and social data at three levels of granularity: spatial, temporal, and decision making;
* To integrate linked open data, sensor network data, and data from social networks and blogs, resulting in a context-aware realization of the SDGs;
* To collect the Agenda 2030 indicators;
* To collect data relevant to SDGs (including social data) to be used for computing other indicators as well as proxy indicators and for analyzing citizens' behavior regarding SDGs;
* To provide data for the Sustainability module relevant for computing integrated (composite) indicators and for modeling social-ecological systems; and
* To provide data for the Governance module.  
Data will be collected from different sources arranged in three groups [181]: (1) Statistical data (data from national and EU statistical agencies, data from other governmental and non-governmental agencies, various open-data available in periodical reports or in continuous mode), (2) Sensor data (data from sensors owned by governmental agencies as well as from sensors owned by various vendors, and data from citizens' sensors such as wearable sensors, mobile smart-phones, in-vehicle sensors, etc.),  
Figure 4: Three building blocks of the ICT framework: data module, sustainability module, and governance module. Data module aims to collect, prepare, analyze (compute and transform), visualize, manage and preserve data from three sources: statistical, sensor, and social data at three levels of granularity: spatial, temporal, and decision making. Sustainability module aims to map SDGs at local level, to ensure inclusion of stakeholders, to provide priority ranking of SDGs, to implement SDGs at local level, and to share and manage knowledge. Governance module aims to provide adaptive, network, collaborative, fair, and trustworthy governance.  
and (3) Social data (data from social networks, blogs, and data from newspapers or news aggregating portals). Levels of granularity include spatial (e.g., local, region, state, national, international), temporal (e.g., daily, monthly, annual), and decision making (e.g., individual, group, institution). This module analyses data and provides input data for the other two modules. By adopting machine learning algorithms, it also incorporates several advanced behavior science concepts in order to improve the motivation for participating on the platform. Social data will be used for providing context-sensitive models of decision-making processes for understanding characteristics of citizens' environmental behavior, which could be reflected in addressing SDGs [182]. Data also generates various indicators (including also proxy indicators): social and ecological performance measures. A proxy indicator provides an indirect measure that approximates or is related to a quantity in the absence of a direct measure. Therefore, proxy indicators are derived from real-time processes and could be implemented to provide social and ecological performance measures in greater detail [181].