Projects / Programmes
January 1, 2017
- December 31, 2027
| Code |
Science |
Field |
Subfield |
| 1.07.00 |
Natural sciences and mathematics |
Computer intensive methods and applications |
|
| 1.01.00 |
Natural sciences and mathematics |
Mathematics |
|
| Code |
Science |
Field |
| P170 |
Natural sciences and mathematics |
Computer science, numerical analysis, systems, control |
| Code |
Science |
Field |
| 1.01 |
Natural Sciences |
Mathematics |
Complex network, data science, graph theory, computational social science
Data for the last 5 years (citations for the last 10 years) on
April 24, 2024;
A3 for period
2018-2022
| Database |
Linked records |
Citations |
Pure citations |
Average pure citations |
| WoS |
668 |
10,835 |
9,928 |
14.86 |
| Scopus |
824 |
12,678 |
11,582 |
14.06 |
Researchers (50)
Organisations (1)
Abstract
Last two decades have witnessed a paradigm shift in our understanding of the interconnectedness of our world, owing to representing the intricate natural, social or technological systems via elegant complex networks framework. In fact, many of the booming 21st century’s research fields including neuroscience and systems biology deal with multilayer phenomena entangling different levels of complexity. This prompted Stephen Hawking to note that this will be “the century of complexity”, which indicates that network science is here to stay. Slovenian research follows this wave, thanks also to the efforts of this Research Program, which is aimed at enhancing the competitiveness of our country in this vibrant field.
We hereby propose the extension of our Research program along the lines of top-level current research topics in network science. Our work will involve two core pillars. Theoretical network science pillar will be contributing to the ongoing methodological developments, primarily design of holistic fine-grained computational models that are verifiable against real data, and construction of heuristics for NP-hard network problems such as graph alignment and k-partite matching. Core essence of our work are large-scale simulations that will be run on our High-performance computer. Within Data science and real networks pillar our work will mostly involve computational social science including economic networks, corruption models, scientometrics and migration dynamics, in addition to fields in their infancy such as culturomic, crowdsourcing or industrial symbiosis. Some attention will also be devoted to topics such as network data analysis in biomedicine. Special emphasis will be given to cross-fertilization of methodological frameworks between various directions in network science.
Drawing upon synergies between two pillars and within our research team, our efforts will contribute to upgrading of the state-of-the-art in several research directions. These are likely to include computational social science, network analysis of biomedical data and several non-mainstream directions in network science. By pursuing interdisciplinary work and organizing scientific events, we will strengthen our collaborations worldwide, which are likely to lead to new results and projects.
Since study of complex networks is a study of real world, we naturally expect our work to have a notable impact on social, economic and cultural life. Technologically relevant findings of economic interest will be emphasized, along with the results relevant for policy making. Developed computational methods will be formulated as freely available opensource software. Intense exchange of young scientists will be a key part our work, not only enhancing scientific thought in our country, but improving the circulation of ideas in and out of Slovenia. Except highly ranked scientific venues, we will pay particular attention to disseminating our results in media for the general public.
Significance for science
Network science developed by combining the knowledge from graph theory and social network analysis with recent empirical findings of universalities in real complex systems. Complex networks paradigm offers an elegant way to study natural, social or technological systems that are composed of many interacting units. While the twentieth century seems to have been the age of reductionism, we are now witnessing the increasing appreciation of the “emergent” phenomena. Stephen Hawking’s opinion that “the twenty-first century would be the century of complexity” comes precisely in this context. The number of scientific articles of Slovenian researchers containing the term “complex networks”, grew from 150 in the year 2001, to 2500 in the year 2015. This trend suggests that complex networks are likely to remain a dynamic and expanding scientific field. This Research Program is aimed at improving the competitiveness of our country in network science and bring it to the forefront of international cutting-edge research.
Our research is divided in two main pillars: Theoretical network science, and Data science and real networks. The choice of our research directions includes topics of intense ongoing work such as network modeling and simulation, optimization problems in networks, graph measures together with novel topics in their infancy, such as computational social science and network data in biomedicine. This indicates that our research plan is well timed and promising to make a significant contribution to the field. Furthermore, our choice of interdisciplinary research direction is adequate, since our research team itself includes scientific backgrounds ranging from mathematics, computer science and computational statistics to physics, biology and neuroscience. Through various local and international collaborations, our work will improve scientific communication among researchers with very diverse expertise, and thus enhance interconnections within the complex networks scientific community.
The proposed research is highly original since we build upon very recent results in a rapidly growing interdisciplinary field, which is likely to trigger new research avenues. Our idea to cross-fertilize various research topics in network science has a large potential that is at present poorly explored. The originality of our undertaking is mainly methodological in the theoretical pillar and mainly topical in the data-oriented pillar.
State-of-the-art in network science methodology includes approaches from mathematics, statistics, physics and computing/algorithms that seldom interact with one another. This leaves the gap along the interface between these fields, which is where we see our niche. On the modeling front this includes new parallelizable frameworks suited for large systems and super-computing, with models based on insights from several fields, beyond routine oversimplification. New reconstruction algorithms may spark collaborative routes between statistical physics and machine learning. Extensions of mathematical approaches will involve novel heuristics and metaheuristics, such as detection of prespecified subnetworks, beyond heavily researched community detection.
Specifically, analysis of big network data for the first time allows for a range of problems in natural and social sciences to be treated quantitatively. Migration models that build upon all involved aspects (including e.g. neuroscience results on brain reaction to strangers) will not only shed new light on this complicated problem, but motivate new collaborative avenues between natural, computer and social sciences. The same is true for financial/economic phenomena, which will eventually lead to systems economics – a discipline inspired by the success of systems biology, which uses a holistic approach integrating all faces of economic phenomena. On the biomedical front, the concept of network medicine is gaining ground as the idea to construct the human diseasome – a n
Significance for the country
Study of complex networks is automatically a study of real world - in fact, society is nothing but a network of individuals. It is therefore only natural to expect that our scientific efforts will be connected to current social and economics needs. In particular, outputs of our work might benefit several economic sectors, including high-tech industries such as biotechnology, pharmacy or communications, where the Slovenian industry has a long and successful history. Computational social science results might be of interest to policy makers and wider public, as they will grasp intricate social phenomena that help us understand our society’s dynamics.
Except on purely scientific front, our long-term results will benefit Slovenia in several other ways. By pursuing interdisciplinary work and organizing scientific events, we intend to strengthen collaborations worldwide, which at present include Oxford University, Harvard University, Imperial College London, UCL, Boston University, University of California Santa Barbara, National University of Singapore, East Chine University of Science and Tokyo University. Exchange of young scientists will be a key part our work, not only enhancing scientific thought in our country, but also improving the circulation of ideas in and out of Slovenia. This can create initiatives for new EU project and bring funding into the country. In fact, last year we organized seventh ITIS conference, annual international meeting where computational and social sciences meet. We have been active in the past as well, organizing Researchers' Night – general presentation of scientific activities through workshops, public lectures and “open doors” of laboratories. This can in turn improve Slovenia's education system through bringing new educational potential into the country.
Due to its interdisciplinarity, our work is likely to influence other scientific disciplines of Slovenian science, many of which are already highly recognized worldwide. The organization of scientific meetings and conferences will improve interconnections among Slovenian scientists, as well as their collaborations with international scientific centers. By building the reputation of Slovenia's science in the world, our research activities will help raise the level of modern scientific thought in our country.
We are successfully engaged in curating Top Publications (»TOPobjave«) section at Slovenia online portal Metina lista, where we offer a monthly summary of best scientific achievements by the Slovenian scientists, explained at the popular non-technical level. Our experience in this indicates that while Slovenian science is clearly following the cutting-edge international trends, public awareness of this is poor or often even distorted. For this reason we are decisive to put a very strong emphasis of disseminating our own and generally Slovenian research results in local and national media. This will not only enrich Slovenian scientific culture but also Slovenian language, where translating the scientific terms, particularly new ones, is imperative.
Most important scientific results
Interim report
Most important socioeconomically and culturally relevant results
Interim report
