Program and Abstracts
NetSciEd4 will be a full-day symposium, which will include:
Invited talks
Contributed talks
Poster presentations
Demonstrations and Explorations
Roundtable discussion
Posters created by NetSci High students will also be displayed at the symposium venue.
PROGRAM
9:30 Welcome
9:40 Hiroki Sayama: Tactile Representation of Complex Networks for Visually Impaired Learners and Researchers, and Beyond [Slides]
10:00 Espen Knoop, Tangible Networks: A Hands-On Approach to Network Modeling [Slides]
10:20 Robin Wilkins Pilot Study with Pre-College Students: Music and Brain Networks
10:40 Kristy Collins: Virus Tracker: Would you like to be infected with the Zombie Plague? [Slides]
11:00 Coffee Break+Poster Session+Demos
11:30 Erzso Regan Why do viruses need a choice, and how is this about networks?
11:50 Lori Sheetz: Lessons from the Network Science Center at West Point [Slides]
12:10 Peter Pollner Experimental Learning of Network Science in High Schools
12:30 Catherine Cramer NetSci High: An Evaluation [Slides]
12:50 Explorations
1:30 Lunch
3:00 Keynote: Ernesto Estrada Teaching Network Theory to Mathematics Students. The Strathclyde Experience [Slides]
3:30 Ralucca Gera, NetSci Kids [Slides]
3:50 Mariano Beguerisse Teaching Network Science to Teenagers [Slides]
4:10 János Kertész, PhD Program in Network Science at CEU, Budapest [Slides]
4:30 Coffee Break+Poster Session+Demos
5:00 Roundtable
6:00 End
ABSTRACTS
Keynote
Teaching Network Theory to Mathematics Students: The Strathclyde Experience
-Ernesto Estrada and Phil Knight, University of Strathclyde, UK
For the past three years we have taught a course in network theory to the Honours class in Mathematics and Statistics at the University of Strathclyde. Our aim has been to present the material so that the difference between network theory and the more traditional area of graph theory is emphasised but that retains a level of mathematical sophistication appropriate for Honours students. With helpful feedback from students in Strathclyde and elsewhere in the world (versions of the course have been taught in the US and in Africa) our course has evolved radically both in the way the material is presented and assessed; and hands on experimentation is a key component. We provide examples of our teaching material along with excerpts from the accompanying text, "A First Course in Network Theory" (OUP, 2015).
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Tactile Representation of Complex Networks for Visually Impaired Learners and Researchers, and Beyond
- Hiroki Sayama (1,2,3), Lindsay Yazzolino (4,5,6) and Prahalad Rao (1,2)
1 Department of Systems Science and Industrial Engineering, Binghamton University
2 Collective Dynamics of Complex Systems Research Group, Binghamton University
3 Center for Complex Network Research, Northeastern University
4 Department of System-Wide Accessibility, Massachusetts Bay Transportation Authority
5 Neuroplasticity and Development Laboratory, Johns Hopkins University
6 Brain and Cognitive Sciences, Massachusetts Institute of Technology
Studies of complex networks are increasingly relying on visualization and infographic representation of network structure, formats which at present heavily depend on a viewer's ability to perceive and interpret graphical information visually. This widespread use of visually-presented data creates a significant risk for the Network Science community to lose participation of blind and visually impaired learners and researchers, and also to mislead even those that are visually normal, since not all the key features of networks can be represented using conventional visualization methods. To overcome these challenges, we have been seeking possibilities for representing complex networks through the nonvisual sensory modalities, focusing specifically on creating tactile representations of networks using additive manufacturing (3D printing) technologies. This presentation will give a brief preliminary report of our recent efforts to test various 3D network designs and conclude with exploring future directions.
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Tangible Networks: A Hands-On Approach to Network Modelling
-Espen Knoop, Ed Barter, Alonso Espinosa, Antoni Matyjaszkiewicz, Chris McWilliams, Lewis Roberts, University of Bristol, UK
Complexity Science is, broadly speaking, concerned with modelling systems as a collection
of simple parts interacting in some complex way. We use mathematical models and computer
simulations to understand the system dynamics and the collective behaviour of the system. An
increasingly important aspect of science is public engagement; communicating research to the
general public. However, it is often di.cult to do this without referring to mathematical models
and computer simulations.
Tangible Networks (TN) is a public engagement project stemming from the Bristol Centre
for Complexity Sciences (BCCS) to help communicate ideas from Complexity Science to the
general public. We want to make the communication of complexity science more hands-on,
more physical and interactive by replacing the virtual network with physical units connected
together with cables to form a network. Each TN unit has a microcontroller running the model,
and can flash in di.fferent colours. The user can directly infuence the behaviour of the network
by changing the way the units are connected and by changing parameters.
Both continuous-time and discrete-time models can be implemented on TN. We have im-
plemented models of opinion formation, synchronisation of chaotic oscillators (Rossler) and
excitable neurons (FitzHugh-Nagumo), as well as demonstrations of hamiltonian paths and con-
ditional probabilities.
TN has been demonstrated at a number of events including science festivals, summer schools
and university open days, and reception has been overwhelmingly positive. TN has also been
used as a demonstration in an undergraduate course on control of complex networks.
We are currently working with teachers to develop more structured classroom activities with
TN, so that it could be used as a standalone kit by teachers in schools.
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Network Science, Neuroimaging and The Effects of Music on the Brain: A NetSci Education Project for Training Undergraduate and Pre-College Students in Network Science Techniques Through Exploring the Effects of Music on the Brain
- Robin W. Wilkins (1,2,3), Michelle Lovett (4), David Teachout (3), Chelsea Joyce (5), Yoon Lee (5), and Robert A. Kraft (2,6)
1 Network Neuroimaging Lab for Complex Systems, Joint School for Nanoscience and Nanoengineering University of North Carolina-Greensboro, NC USA
2 Gateway MRI Center Joint School for Nanoscience and Nanoengineering University of North Carolina – Greensboro, NC USA
3 School of Music, Theater and Dance University of North Carolina-Greensboro NC USA
4 Southwest High School Guilford County Public Schools Greensboro, North Carolina USA
5 Department of Biological Sciences University of North Carolina-Greensboro, NC USA
6 Department of Biomedical Engineering, Wake Forest University Baptist Medical Center, Winston-Salem NC USA
This NetSci education broader participation (BP) pilot project builds on a successful BP case study pilot that provides hands-on technical training in network science techniques to university undergraduate and pre-college students. Harnessing a student’s natural interest in music to foster early training in network science, this interdisciplinary project introduces the techniques, tools and methods of a complex systems approach to working with large data sets. By providing students presently trained and skilled in music with both the network science knowledge and the hands-on technical training necessary to working with large data, this project aims to develop young minds prepared to pursue interdisciplinary network science research.
Participating students receive an introduction to network science techniques and methods, as well as a complex systems approach to working with large brain imaging data sets, and an overview of brain anatomy. Students learn about fMRI data acquisition and processing (including a Siemens 3 T scanner, matlab, FSL and Conn Tool Box), and a free session in fMRI statistics taught by neuroscientist Martin Lindquist, Ph.D., Johns Hopkins University, via Coursera. Students then put these techniques into practice by working with large data sets (i.e., neuroimaging fMRI and DTI data). Each student performs computational work using UNIX command line scripting and designs a network neuroscience research hypothesis to study the effects of music or intensive musical training on the brain. Students who are 18 years of age are permitted to participate in an fMRI experiment. In addition, all students have the opportunity to experience their own fMRI scan, shadow the acquisition of fMRI data and learn how to process fMRI data for network analysis. Pre-college students may use this experience for a required senior project or research paper.
Upon completion, students write a 10-15 page scientific research paper and present a 12-minute presentation describing their project before an audience of administrative adjudicators, teachers and parents at their annual school research night. Undergraduate students may continue their collaborative training with the network neuroimaging lab director through both regular independent study credits and training sessions held at the lab. Students are invited to submit their projects to the annual satellite session of the International Conference on Network Science Education and are encouraged to apply their knowledge of a network science approach to other content areas along their university academic path. The broader aim of this project is to provide a technically sound opportunity that broadens participation and generates highly skilled young interdisciplinary researchers who are informed and technically prepared to be able to pursue 21st century scientific and engineering-based academic or career endeavors.
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Virus Tracker: Would You Like to Be Infected with the Zombie Plague?
-Kristy Collins, James Stoll, Stephen Eubank, Madhav Marathe, Virginia Bioinformatics Institute at Virginia Tech
Virus Tracker is an educational game that simulates the spread of a virus and the critical role of vaccination in combating a disease outbreak. It involves a game host who: 1) controls various aspects of the outbreak; (2) maintains a record of the players’ states; (3) collects statistics on the players’ states; and (4) provides visualizations of the outbreak’s progress. Infected players can transmit the dreaded (but imaginary) Zombie Plague Virus to their contacts. Game play is deepened by the opportunity for players to vaccinate others. The virus mutates under control of the game’s host, so that regular re-vaccination is needed to maintain immunity. The amount of vaccine, its efficacy against infection, and access to the stockpile are all controlled by the host. It is possible, for example, to require players to answer questions related to public health correctly to obtain a vaccine they can distribute. Players are awarded points both for vaccinating and for infecting other players.
Players are assigned a unique identifier when they join the game. When the identifier is assigned, players may be asked to answer a short survey, for example about their demographics. The host maintains a database tracking every event in the game as well as a leader board and visualizes both the infection and vaccination transmission trees. Using their identifier, players can locate themselves in either of these trees to see, for example, how many people they have infected indirectly, or how far they are from the index case.
The game can be played using either paper IDs and bar code scanners or a smart phone app or a combination of the two. This flexibility in modes makes the game amenable to all ages and levels of technology knowledge and creates a fun, interactive opportunity to talk about infectious disease and current research. Discussions can range from the power of exponential growth and why we need to vaccinate regularly against influenza to optimal strategies for allocating limited quantities of vaccine.
This game has been played at the 2012 and 2014 USA Science and Engineering Festivals and the 2014 National Boy Scout Jamboree. Information collected in the game is used by the Network Dynamics and Simulation Science Laboratory (NDSSL) at Virginia Bioinformatics Institute at Virginia Tech in simulations to study epidemics on these virtual social networks.
This work has been funded by Virginia Bioinformatics Institute at Virginia Tech, NSF NEtSE and NIH MIDAS.
Website- https://virustracker.vbi.vt.edu
App- Available on Google Play and Apple- search for Virus Tracker
For Educators- A barcode program that can be used in classrooms- http://vtib.vbi.vt.edu
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Why Do Viruses Need a Choice, and How Is This about Networks?
-Erzsebet Regan, Harvard Medical School, US
Biological systems, from our bodies to the regulatory networks that govern cell behavior, are made of modules (and modules of modules, in a hierarchy.) A core premise of my work is that at the heart of each regulatory module is a switch: a circuit with two (or more) locally stable states, separated by energy barriers. Switches are great when cells are faced with a “decision” between mutually exclusive functional states, especially if in-between options make no sense (e.g., survival vs. cell death). We have ample evidence that regulatory systems in every organism from viruses to humans are riddled with switch-like circuits. What we do not know is how did these switches evolved?
As a first step to, our NetSciHigh 2015 project involved a closer look at the most primitive organism I know of that has a regulatory switch, namely the virus Enterobacteria phage λ virus. Upon entering a bacterium, this virus has two possible fates. Normally it hijacks bacterial transcription, translation and metabolic resources to build copies of itself, then bursts the bacterium open in search of new prey (dryly known as lysis). Occasionally, though, it can completely sidestep this and integrate its own DNA into bacterial DNA (confusingly known as lysogeny). In this case it is replicated along with the bacterial DNA, and eventually exits this lysogenyc state in favor of assembling new viruses and lysing its host. We hypothesized that when the phage is coping with an unpredictable progression of different environments, high fitness requires an ability to choose between distinct behaviors: kill or bide its time. To do this, we first build the network of regulatory interactions that make up the lysis/lysogeny switch. Second, we simulated a fluctuating bacterial environment in which viruses attempt to multiply, then tracked viral infections that flipped their lysis/lysogeny switch depending on the internal state of the bacteria they managed to infect. The students came up with a brilliant way of visualizing the time-dependent fates of different bacteria and viruses - as a network! Their work is a great foundation for an in silico experiment in which we start with a virus with no choice, and entice it to evolve one. My long-term vision is a laboratory experiment (guided by theory and simulations) in which a mutated λ phage with no gene to perform lysogeny re-evolves the switch in the lab.
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Experimental Learning of Network Science in High Schools
-Peter Pollner, Hungarian Academy of Science, Hungary
Network science provides a way of comprehension and thinking, so it would be useful to make people familiar with it as early as possible. Regular courses need some knowledge in statistics or use tools from higher mathematics that are not available for younger students, e.g. in high schools or in primary schools.
In this talk I present an online framework, that can be used for enhancing social and emotional learning in schools by evaluating questionnaires. Here, networks are excellent tools for showing a community mirror for teachers and students. During the discussions about social relations (e.g. preventing bullying), students get familiar with network thinking inconspicuously. I will present some results from a high school course as well, where basic mathematics can be used by students for working with networks. The course was organised as a subsequent seminar after a basic game theory.
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NetSci High: An Evaluation
- Catherine Cramer, Russell Faux, Hiroki Sayama, Lori Sheetz, H. Eugene Stanley, Paul Trunfio, Stephen Uzzo
Network Science for a New Generation – “NetSci High” – is a three-year project funded by the National Science Foundation, which is now coming to a close. The goals of NetSci High were, through the teaching of network science concepts and related skills, to make significant educational impacts on regional high school students and teachers; to provide a pathway to integrate science research and programming skills for high school students who would not otherwise have these opportunities; and to encourage high school teacher mentors to broaden their STEM understanding. A recent external evaluation conducted by Davis Square Research Associates, LLC produced a summative report, which includes results from surveys and focus groups over the three years of the project, as well as conclusions and recommendations for future work.
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NetSci Kids
-Ralucca Gera, Naval Postgraduate School, US
The Network Science community understands that the world we live in can be defined by networks. Why is it that we begin to think in network terms in our late teens or later? If we begin much earlier, we may develop natural intuition in the application of network theory and tools that enables a tremendous leap forward in our ability to model and understand our connected world. Network Science for Kids envisions a program to facilitate network thinking in our youngest students: Kindergarten through 8th grade. The core program precept is to generate network experiences for children in their developmental years to promote a different style of thinking—network thinking—that better suits our connected world than the thinking generated by traditional educational practices.
We may begin by encouraging students to solve puzzles and then abstracting the puzzles by identifying connections between the objects and ideas those objects represent. Early exposure to connections between the actual and abstractions in the familiar world around our children will aid them in understanding mathematical ideas through media such as hands-on activities and computer apps. For example, children as young as Kindergarten age can play the following game: Given 3-letter words denoted by a circle, find a chain of letter swapping (one letter at the time) from word “sad” to word “man.” What is the minimum number of such changes needed? The question can be answered easily, especially if the problem is viewed as a network. This is the idea behind Hamming distance between binary strings that students are exposed in discrete math in college.
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Bringing Networks to Teenagers
-Mariano Beguerisse Díaz,, Imperial College London, UK
High school students regularly use social networks and the internet, two examples of networks that are easily understood by students. Over the last few years, we have carried out outreach activities teaching teenagers network science. These outreach activities were interactive, with students first learning then basics of networks and then participating in different modules such as the environment and network, Page Rank and how Google works, Epidemics and vaccine strategies, and graph colourings and games. I will present the structure of outreach activities, lesson plans, and discuss what worked and what didn't in this outreach.
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PhD Program in Network Science at CEU, Budapest
-János Kertész, Central European University, Hungary
Network Science has reached a level of maturity, when it should enter higher education with independent PhD programs. As a first in Europe, CEU starts this year with its program, hosted by the Center for Network Science. In this talk I will briefly describe the Center, summarize the construction principles and the structure of the curriculum, and report about our experiences with the first round of recruitment of students.
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