# A Novel ICT Framework for Sustainable Development Goals
## 2 Background of the Problem and Our Contribution
### Research Design  
This section will expose the overall strategy chosen to coherently and logically integrate the different constituents of the paper. We will therefore specify the type of evidence needed to effectively address the research problem and to accurately answer the following research questions:  
* RQ1: What research questions regarding ICT for SDGs have already been conducted by combining all three disciplines: governance science, sustainability science, and data science? * RQ2: How and what ICTs have been adopted for SDGs? * RQ3: How and what artificial intelligence (AI), machine learning (ML), and other data science methods and tools have been used for SDGs? Our goal is not only to provide a systematic literature review on ICT for SDGs, but also to identify research gaps for ICT driven enhancement and implementation of SDGs. We conduct a literature review following the PRISMA framework [68] and the suggestions for systematic literature reviews by [PERSON] [69] and [PERSON] [70]. We have identified the main search terms based on our research questions, selected the most common scientific literature databases and platforms Web of Science, Scopus, Google Scholar, and Google for the search, found all relevant publications, and selected a number for critical analysis. These publications are further clustered in three groups (data module, sustainability module, and governance module) and subject to analytical discussion in the next sections. As regards the questions RQ1, RQ2, and RQ3, our findings can be summarized as follows:  
* Finding 1: The recent development of new governance theories with roots in various disciplines ranging from social sciences to natural sciences, has led to positioning governance science as an independent pillar when addressing SDGs. There is no article that takes a holistic view when addressing SDGs and includes the findings from all three disciplines: governance science, sustainability science, and data science. * Finding 2: State-of-the-art ICTs such as autonomous things, augmented analytics, AI-driven development, edge and fog computing, digital twins, digital lakes, and immersive technologies have not yet been fully developed and deployed for SDGs. Figure 2: The ICT framework for SDGs we propose here endorses six novel approaches: holistic approach aiming to integrate three disciplines—governance science, sustainability science, and data science—bonded with the concept of digital democracy; increased-awareness approach ensuring governance of SDGs on both local and global levels; data-intensive approach aiming to implement SDGs by using state-of-the-art machine learning methods at different spatial, temporal, and decision making scales; governance-enhanced approach implementing SDGs by considering various governance theories: adaptive governance, network governance, collaborative governance, accountable governance, fair governance, and trustworthy governance; two-way approach ensuring communications between government and people and effective citizen engagement in addressing SDGs; and responsible approach providing true impacts on SDGs by motivating citizens to participate in addressing SDGs and by enabling those in positions of power to endorse the framework. * Finding 3: Although AI and ML methods have been increasingly used to track progress toward certain SDGs, nevertheless, the full potential of current state-of-the-art AI/ML methods and tools have not yet been used for improving the implementation of SDGs. Taken together, the above findings suggest that this paper is actually a first attempt to conceptualize the SDGs (as an ICT-supported phenomenon) in the light of existing discussions in governance science, sustainability science, and data science. The review analysis has also been used for a \"conceptual framework analysis\" approach in order to develop an ICT framework for SDGs. A conceptual framework interlinks concepts for ensuring a comprehensive understanding of a phenomenon or phenomena [71], see also [72; 73; 74].