Session - Open Government Data: a Pillar for Sustainable Development Complex networks: a tool to help the Member States to address the SDGs

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Session - Open Government Data: a Pillar for Sustainable Development Complex networks: a tool to help the Member States to address the SDGs Roberto Bellotti Nicola Amoroso Elena Garuccio Stefano Nicotri 1

Outline Our Case Study: Public Funding: 2007-2013 Italian Program Complex Networks: a tool for data analysis Our Results ApplicaGon to SDGs Conclusions 2

Public Funding: 2007-2013 Italian Program ü Italian Program for the Convergence objective regions (less developed regions in Southern Italy) ü (Program: National Operative Program (PON) for Project in research & development) ü Goal: Evaluate the impact of public funding at regional level Total cost of the PON Projects à 2500 Million of Euros About 300 Different R&D Projects 769 distinct partners 13%# 6%# 28%# Large#Enterprise# nofpublic#research#ins/tute# N.C.# 12%# 8%# 12%# Smart#Ci/es# Cultural#Heritage#&#Ac/vi/es# Transporta/on#&#Logis/c# 19%# 12%# (a)# 13%# 7%# 2%# Small#Enterprise# Public#Research#Ins/tute# University# Micro#Enterprise# Medium#Enterprise# 21%# 7%# 12%# (b)# 16%# 12%# Environment## Energy# Nutri/on# Healthcare# N.C.# Available information: Calls and funding measures, projects, proponents and participants, funding, geographical information, etc. Data format: open data (xls, XLM, CSV) Source: : http://www.dati.puglia.it, http://opencoesione.gov.it 3

Analysis Workflow Results Structured data Model Data analysis 4

Complex Networks Many different physical, biological and social system are structured as complex networks, and their properties are now quite well understood. Complex networks are a set of nodes, connected by links, which can model many systems in social science, economics and technology. A B e.g. Nation A is linked to Nation B if A buy products from B.

Examples include Multimodal transportation networks Climate system Energy supply networks Human brain Economic markets 6

Complex Systems What can we learn from complex network analysis? The 10 most-travelled stations - along the shortest paths - of the London Underground. Find people with more influence in a social network. They have been used to predict results in political elections Marketing decisions: who is the subject that can spread information about new products, and events? 7

Public Funding: 2007-2013 Italian Program Nodes à Enterprises, Universities, research institutions. Links à Participation in the same project. 8

Result #1: community detecgon We found 15 main Communities à provides a deep understanding of how the fund allocation criteria are able to influence the economic development of a Region; discovering the existence of groups within a certain network of relationships, and highlighting such groups can be very important for the analysis of a productive system. The PON R&D network shows strongly heterogeneous communities, with hugely populated groups and very small ones. when communities grow in size, they tend to include important nodes. For example, the largest community includes the National Council Research (CNR, next slide) The community structure of the (giant component of the) PON R&D network. 15 communities are highlighted, found with the Newman-Girvan algorithm. 9

Result #2: it is a network with Hubs Scale free network à Inhomogeneous degree distribution, with many nodes having more connections than the average (hubs) Resistance to random failures, indeed the removal of a random vertex would not systematically affect the main hubs Policymakers interested in generating a solid network of relationships between productive actors on the territory PHkL 0.08 0.06 0.04 0.02 0.00 0 10 20 30 40 50 k Log-Log scale 10

Result #3: who are the hubs? Centrality of nodes à identifies the most important vertices within a graph Dominant role of public research Universities and research centers play the role of the glue i.e. they are responsible of the connectedness of the network Ex-post indicator. The fifteen largest values of each vertex centrality for the (giant component of the) PON R&D network. The highest positions are occupied by public research institutions. 11

Result #4: the network is ang- assortagve Assortativity à Low tendency to form groups of interest" or lobbies among important actors Associate strongly connected hubs to smaller and less connected enterprises/ institutions. It is an interesting result, since most social networks show assortative behavior. Anti-assortative networks are more sensitive to the removal of high-degree nodes, which is an indication for the policymaker of the importance that public research has in the productive system. 12

SDGs Goals: a different perspecgve Can we use complex network analysis to infer some important features of the SDGs? à Relations among SDGs Proposal, their Targets and Member States. 13

The Sustainable Development Goals Proposal Three main pillars of sustainable development 14

THE SUSTAINABLE DEVELOPMENT GOALS PROPOSAL Goal #1 Goal #2 End poverty in all its forms everywhere End hunger, achieve food security and improved nutrigon and promote sustainable agriculture Goal #3 Ensure healthy lives and promote well- being for all at all ages Goal #4 Ensure inclusive and equitable quality educagon and promote lifelong learning opportuniges for all Goal #5 Achieve gender equality and empower all women and girls Goal #6 Ensure availability and sustainable management of water and sanitagon for all Goal #7 Ensure access to affordable, reliable, sustainable and modern energy for all Goal #8 Promote sustained, inclusive and sustainable economic growth, full and producgve employment and decent work for all Goal #9 Goal #10 Build resilient infrastructure, promote inclusive and sustainable industrializagon and foster innovagon Reduce inequality within and among countries Goal #11 Make ciges and human sealements inclusive, safe, resilient and sustainable Goal #12 Ensure sustainable consumpgon and producgon paaerns Goal #13 Take urgent acgon to combat climate change and its impacts* Goal #14 Conserve and sustainably use the oceans, seas and marine resources for sustainable development Goal #15 Goal #16 Goal #17 Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desergficagon, and halt and reverse land degradagon and halt biodiversity loss Promote peaceful and inclusive socieges for sustainable development, provide access to jusgce for all and build effecgve, accountable and inclusive insgtugons at all levels 15 Strengthen the means of implementagon and revitalize the global partnership for sustainable development

1 3 N 2 4 5 SDG 1 The sustainable development analysis naturally involves a novel multi-graph framework. 2 1 4 3 N 5 Each layer represents a particular sustainable development goal (SDG). SDG 2 Within each layer (i.e. SDG) a node represents a member state of the United Nations, while links measure the pairwise similarity between the nations with respect to some physical, economic or social Indicators. 2 1 4 3 N 5 The multi-links (the links connecting different layers) capture the behavior of nations with respect of different SDGs. SDG 17

SDGs Goals: a new PerspecGve A global view of the relations among Member States in respect to the SDGs and their targets can be achieved. Each Member State is represented by a node The SDGs Proposal is a multilayer complex network Each layer represents one of the SDGs Links between nodes, on each layer, are defined by correlations on macroeconomic indicators from couples of Member States Important properties can be extracted from each layer, which represent a goal of our analysis (hubs, degree, etc.. ). The proposed multi-layer network framework could give important insight about how Member States can address and fulfil of SDGs target 17

Conclusions ü Complex Networks are very powerful tools to model transportation, ecological, social systems etc. ü We applied techniques of complex network analysis to open data sources representing Italian public funding programs for unprivileged Regions in Southern Italy ü We have found: ü 15 different communities among 769 distinct partners (Enterprises, Universities, ) ü The presence of Hubs à Universities and research centers play the role of the glue of the network ü The network in anti-assortativeà Low tendency to form groups of interest" or lobby among important actors ü We propose to use Complex Network in order to study in which way the Member States are pursing the SDGs Proposal and their interrelated targets. 18

Thank you for your attention. 19