This web application visualizes how successful universities or research-focused institutions collaborate. The application is based on papers (articles, reviews and conference papers) published between 2012 and 2016 in several subject areas and in “All areas”. For each subject area (and for “All areas”), those institutions (universities and research-focused institutions worldwide) were selected in the SCImago Institutions Ranking which published at least 500 papers in the publication period. We refer to these institutions as "reference institutions". For every reference institution, the collaborating institutions were identified. Collaborating institutions are those which have co-authored at least ten publications with the respective reference institution. We refer to the collaborating institutions as “network institutions”. We estimated statistical models (Bayesian multilevel logistic regressions). The statistically estimated best paper rates (from the models) which the reference institutions have achieved with its network institutions are visualized. The best paper rate gives the proportion of highly cited papers from an institution and is considered generally as a robust indicator for measuring citation impact. Co-authorship networks (based on institutional affiliations) show how successfully overall an institution (reference institution) has collaborated compared to all the other institutions, and with which other institutions (network institutions) an institution has collaborated best.
Drawing from across cultures and across scholarly disciplines, Places & Spaces: Mapping Science demonstrates the power of maps to address vital questions about the contours and content of human knowledge. An interdisciplinary and international advisory board chose each one of the works in the Places & Spaces: Mapping Science exhibit as an outstanding example of how visualization can bring patterns in scientific data into focus. The exhibit is curated by the Cyberinfrastructure for Network Science Center at Indiana University. The exhibit has been on display at over 382 venues in 28 countries on 6 continents. It showcases the work of 248 mapmakers that hail from 17 different countries
UI component for Globe Data Visualization using ThreeJS/WebGL
Highly skilled, open-minded Software Engineer focused on user-centered web development, data analytics and interactive data visualization.
Over 18 years of work experience in software/network engineering, data visualization, web UX and research in the field of Internet networking.
Specialties:
Software: JavaScript, D3.js, ReactJS, GraphQL, TypeScript, ThreeJS/WebGL, SVG, Mapbox, A-Frame/WebVR, Python, Java, R
Network: IPv4/v6, BGP, DNS, HTTP, TCP/IP, SSL, RPKI
Data Visualization
Involvement in Internet community
Interface design and User Experience
Close involvement with D3/data visualization community
https://github.com/vasturiano
https://observablehq.com/@vasturiano
https://bl.ocks.org/vasturiano
un très beau démonstrateur de navigation en 3 dimensions dans un graphe de réseau.
Une incroyable plateforme libre destinée à servir à la fois de catalogue de datasets pour tester les outils de visualisation mais également d'outil d'analyse visuelle. Du lourd..
" Le premier référentiel interactif de données et de données de réseau avec analyse visuelle en temps réel. Network repository est non seulement le premier référentiel interactif, mais aussi le plus grand référentiel de réseaux avec des milliers de dons dans plus de 30 domaines (des données biologiques aux données de réseaux sociaux). Cette vaste collection complète de données de graphes de réseaux est utile pour faire des découvertes de recherche significatives ainsi que des ensembles de données de réseaux de référence pour une grande variété d'applications et de domaines (par exemple, la science des réseaux, la bioinformatique, l'apprentissage automatique, l'exploration de données, la physique et les sciences sociales) et comprend des données de réseaux relationnels, attribués, hétérogènes, en continu, spatiaux et de séries temporelles ainsi que des données d'apprentissage automatique non relationnelles. Tous les ensembles de données graphiques sont facilement téléchargeables dans un format standard cohérent. Nous avons également construit un moteur d'analyse de graphes interactif à plusieurs niveaux qui permet aux utilisateurs de visualiser la structure des données de réseau ainsi que les statistiques de données de graphes au niveau macro et les propriétés de réseau importantes au niveau micro des nœuds et des arêtes."
The Data Visualisation Catalogue is a project developed by Severino Ribecca to create a (non-code-based) library of different information visualisation types. The website serves as a learning and inspiration resource for those working with data visualisation. Originally, this project was a way for me to develop my own knowledge of data visualisation and create a reference tool for me to use in the future for my own work. However, I felt it would also be beneficial to both designers and also anyone in a field that requires the use of data visualisation. Each visualisation method was added bit-by-bit, as I individually researched each method, to find the best way to explain how it works and what it is best suited for.
"Functional visualizations are more than innovative statistical analyses and computational algorithms. They must make sense to the user and require a visual language system that uses colour, shape, line, hierarchy and composition to communicate clearly and appropriately, much like the alphabetic and character-based languages used worldwide between humans."
Matt Woolman
Digital Information Graphics
Goal
VisualComplexity.com intends to be a unified resource space for anyone interested in the visualization of complex networks. The project's main goal is to leverage a critical understanding of different visualization methods, across a series of disciplines, as diverse as Biology, Social Networks or the World Wide Web. I truly hope this space can inspire, motivate and enlighten any person doing research on this field.
Not all projects shown here are genuine complex networks, in the sense that they aren’t necessarily at the edge of chaos, or show an irregular and systematic degree of connectivity. However, the projects that apparently skip this class were chosen for two important reasons. They either provide advancement in terms of visual depiction techniques/methods or show conceptual uniqueness and originality in the choice of a subject. Nevertheless, all projects have one trait in common: the whole is always more than the sum of its parts.
How it started
The idea for this endeavor started on my second year MFA program at Parsons School of Design. During this period I conducted extensive research on the visualization of complex networks, which culminated with my thesis project Blogviz: Mapping the dynamics of information diffusion in Blogspace. One thing I found while exploring this area was the lack of an integrated and extensive resource on this subject. This is the main reason why this project came to life.
Later on, as a teaching assistant of Information Architecture at Parsons Design+Technology program, together with Christopher Kirwan, I was able to consolidate most of this research as part of an independent study. The key chunk of projects shown here was gathered during this phase. My ultimate goal is to keep adding new projects to a still undetermined limit. VisualComplexity.com was launched in October, 2005.
Complex Networks
Complexity is a challenge by itself. Complex Networks are everywhere. It is a structural and organizational principle that reaches almost every field we can think of, from genes to power systems, from food webs to market shares. Paraphrasing Albert Barabasi, one of the leading researchers in this area, “the mystery of life begins with the intricate web of interactions, integrating the millions of molecules within each organism”. Humans, since their birth, experience the effect of networks every day, from large complex systems like transportation routes and communication networks, to less conscious interactions, common in social networks.
Scale-Free networks, one of the most common topology in either natural or human systems, is curiously enough, a very recent breakthrough. Since its discovery, in 1999, dozens of researchers worldwide have been disentangling the networks around us at an amazing rate. This awareness is helping us understand not only the world around us but also the most intricate web of interactions that shape the human body. The global effort of constructing a general theory of complexity is tremendous and may lead us, not only to a structural understanding of networks, but to major improvements in stability, robustness and security of most complex systems around the globe. Like Barabasi refers in Linked, “Once we stumble across the right vision of complexity, it will take little to bring it to fruition. When that will happen is one of the mysteries that keeps many of us going”.
About the author
A Fellow of the Royal Society of Arts, nominated by Creativity magazine as "one of the 50 most creative and influential minds of 2009", Manuel Lima is a designer, researcher, teacher, and founder of VisualComplexity.com - A visual exploration on mapping complex networks.
With over 10 years of experience designing digital products, Manuel has worked for Microsoft, Nokia, R/GA, and Kontrapunkt. He holds a BFA in Industrial Design and a MFA in Design & Technology from Parsons School of Design, New York. During the course of the MFA program, Manuel worked for Siemens Corporate Research Center, the American Museum of Moving Image and Parsons Institute for Information Mapping in research projects for the National Geo-Spatial Intelligence Agency.
Manuel is a leading voice on information visualization and has spoken in numerous conferences, schools and festivals around the world, including TED, Lift, OFFF, Eyeo, Ars Electronica, IxDA Interaction, Harvard, MIT, Royal College of Art, NYU Tisch School of the Arts, ENSAD Paris, University of Amsterdam, MediaLab Prado Madrid. He has also been featured in various magazines and newspapers, such as Wired, New York Times, Science, BusinessWeek, Creative Review, Fast Company, Forbes, Eye, Grafik magazine, SEED, Étapes, and El País. For a complete list of talks, click here.