I501: Introduction to Informatics

Fall 2017

Instructor: Luis M. Rocha, Center for Complex Networks and Systems, School of Informatics, Computing, and Engineering and Cognitive Science Program, Indiana University

Associate Instructor: Thomas Parmer

Class Location and Time:Wednesdays, 11:15AM - 1:45PM, Room: Informatics East, 901 E. 10th St., Room 122

Course Description

Description:The course deals with the foundations of Informatics as an interdisciplinary field. We will study concepts such as Information, Technology, Knowledge, Modeling, as well as their impact on science and society. The course will also attempt to define and understand what computational and systems thinking can bring to science and society. The course is required for the PhD in Informatics as well as the NSF-NRT Interdisciplinary Training Program in Complex Networks and Systems at Indiana University.

Aims: The course is designed to present and discuss the history, methodology and impact of informatics; students are introduced to various approaches to informatics via the appropriate literature. Finally, students are expected to develop a understanding of what constitutes research in the field, via a familiarization with relevant funding opportunities.

Syllabus

Lecture Outline

How did we get here?

Cybernetics & the Information Turn
Organized Complexity, Information, and Semiotics
Systems theory

Computing Models of the World

Reverse Engineering and Modeling the World as a System
The Blackbox

Information and Uncertainty

From semiotics to Shannon
Information Theory

Informatics Today

Complexity
Networks
Collective Intelligence: The cyborg species?

Science and Society

Proposal Development
Scientific Publication and Peer Review

Course Evaluation

Participation: 15%.

based upon attendance and participation in class discussion. We expect that students will approach the course as they should a professional job and attend every class.

Paper Presentation and Handout: 15%.

Presentation of research paper plus leading of discussion

Black box Assignments: 40%

There will be 2 blackbox assignments during the semester.

GRFP Research proposal: 30%

Assignments and Proposal

Black Box Assignment 1:
- Due: October 11th, 2017
The Black Box and the Numerical Version. Study the behavior of the system. Propose a model of what it does. Due on October 11th, 2017 . Upload your group's findings to the Black Box Assignment 1 folder in the assignments section in Canvas.
Black Box Assignment 2:
- Due: November 17th, 2017
Upload your group's findings to the Black Box Assignment 2 folder in the assignments section in Canvas. The Black Box and its Numerical Version. Study the behavior of the system. Focus on uncovering quadrants using data collection and induction. Propose a formal model or algorithm of what each quadrant is doing. Analyze, using deduction, the behavior of this algorithm. Due on November 15th , 2017. Upload your findings to the Black Box Assignment 2 folder in the assignments section in Canvas.
GRFP Research proposal:
- Due: December 15th, 2017

Lecture Notes

1. The Nature of Information
2. Formalizing and Modeling the World (pdf document)

Lecture Slides

Lecture 1 - How did we get here? Introduction and Syllabus
Lecture 2 - From Bones to Computers
Logan Paul's presentation of Weaver's paper, and the handout.
Zackary Dunivin's Handout of Simon's paper.
Lecture 3 - Computers and Cybernetics
Nicholas Plank's presentation of Freeth's paper, and the handout.
Clara Boothby's presentation of Wasserman, Zeng, & Amaral, and the handout.
Lecture 4 - Information and uncertainty
Sirag Erkol's presentation of Barabasi and Albert's paper, and the handout.
Patrick Kaminski's presentation of Hofman, Sharma, & Watts, and the handout.
Andrew Leeth's presentation of Jonas & Kording, and the handout.
Rosemary Steup's presentation of Frimer et al, and the handout.
Jayati Dev's presentation of Adamic et al, and the handout.
Lecture 5 - Modeling the World
Giampaolo Russo's presentation of Ciampaglia et al, and the handout.
Lecture 6 - From Modeling to General Principles of Organization
Vincent Wong's presentation of Schmälzle et al, and the handout.
Cassie Kresnye's presentation of Gauvrit et al, and the handout.
Vincent Malic's presentation of Piantadosi et al's paper, and the handout.
Lecture 7 - Organized Complexity and Systems Theory
Stephen Sher's presentation of Markov's paper, and the handout.
Kaicheng Yang's presentation of Loreto et al's paper.The handout
Lecture 8 - The Black Box I
Lecture 9 - Dealing With Black Boxes: General Systems Problem Solving (or how to count oranges) (by Ian Wood)
Lecture 10 - Science and Society (by Johan Bollen)
Lucas Kemp-Cook's presentation of Popper's paper.The handout
Filip Miscevic's presentation of Kuhn's paper.The handout
Lecture 11 - Interdisciplinarity, Informatics, and Two-dimensional Science
Swapna Joshi's presentation of Rubenstein et al's paper.The handout
Lecture 12 Part I - Grant Writing Tips (by Shannon K. Larson)
Lecture 12 Part II - GFRP Proposal Guidelines (by Rion Correia)
Stephen Simms's presentation of Clark's chapters.The handout

Readings available in the OnCourse Class Folder)

Mandatory articles

week	papers
week 1	Borges, Jorge Luis. [1941]. The Library of Babel. Borges, Jorge Luis. [1941]. The Garden of Forking Paths .
week 2	Heims, S.G. [1991]. The Cybernetics Group. MIT Press. Chapters: 1,2 Weaver, W. [1948]. "Science and Complexity". American Scientist, 36(4): 536-44. Simon, H.A. [1962]. "The Architecture of Complexity". Proceedings of the American Philosophical Society, 106: pp. 467-482.
week 3	Freeth, Tony. 2014. “Eclipse Prediction on the Ancient Greek Astronomical Calculating Machine Known as the Antikythera Mechanism.” PloS One 9 (7): e103275. Gleick, J. [2011]. The Information: A History, a Theory, a Flood. Random House. Chapter 8. Wasserman, M., X.H.T. Zeng, and L.A.N. Amaral [2015]. “Cross-evaluation of metrics to estimate the significance of creative works”. PNAS 112 (5) 1281-1286
week 4	Barabasi and Albert (1999) Emergence of Scaling in Random Networks, Science 296 (5439) Hofman, Jake M., Amit Sharma, and Duncan J. Watts. "Prediction and explanation in social systems." Science 355.6324 (2017): 486-488. Prokopenko, Mikhail, Fabio Boschetti, and Alex J. Ryan. [2009]. "An information-theoretic primer on complexity, self-organization, and emergence. ". Complexity 15(1): 11-28
week 5	Young, T. (2017). Cease and desist. Nature, 541(7637), 430–430. https://doi.org/10.1038/541430a Lazebnik, Y [2002]. "Can a biologist fix a radio?--Or, what I learned while studying apoptosis". Cancer Cell, 2(3):179-182. Jonas, E., and Kording, K. P., (2017). Could a Neuroscientist Understand a Microprocessor? PLOS Computational Biology, 13(1), e1005268. Adamic, Lada A., Thomas M. Lento, Eytan Adar, and Pauline C. Ng. "Information evolution in social networks." In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, pp. 473-482. ACM, 2016. Jeremy A. Frimer, Karl Aquino, Jochen E. Gebauer, Luke (Lei) Zhu, and Harrison Oakes [2015] "A decline in prosocial language helps explain public disapproval of the US Congress" PNAS 2015 112 (21) 6591-6594; doi:10.1073/pnas.1500355112
week 6	G.L. Ciampaglia, P. Shiralkar, L.M. Rocha, J. Bollen, F. Menczer, A. Flammini [2015]. “Computational fact checking from knowledge networks.” PLoS One. 10(6): e0128193. doi:10.1371/journal.pone.0128193.
week 7	Gauvrit, N., Zenil, H., Soler-Toscano, F., Delahaye, J.-P., Brugger, P., Schuknecht, B., … Brugger, P. (2017). Human behavioral complexity peaks at age 25. PLOS Computational Biology, 13(4), e1005408. Klir, G.J. [2001]. Facets of systems Science. Springer. Chapters: 1,2,3 Piantadosi, S. T.,et al (2011). Word lengths are optimized for efficient communication. PNAS, 108(9), 3526–3529. Schmälzle, R., Brook O’Donnell, M., Garcia, J. O., Cascio, C. N., Bayer, J., Bassett, D. S., … Falk, E. B. (2017). Brain connectivity dynamics during social interaction reflect social network structure. Proceedings of the National Academy of Sciences, 114(20), 5153–5158.
week 8	Loreto, Vittorio, et al. "Dynamics on expanding spaces: modeling the emergence of novelties." Creativity and Universality in Language. Springer International Publishing, 2016. 59-83. Markov, Igor L. 2014. “Limits on Fundamental Limits to Computation.” Nature 512 (7513) (August 13): 147–154. doi:10.1038/nature13570.
week 10	Klir, G.J. and D. Elias [2003]. Architecture of Systems Problem Solving. Springer. Chapters: 1,2, 3.1, 3.2, 3.10, 4.1, 4.2
week 11	Kuhn, Thomas S. (1970). Logic of discovery or Psychology of Research. Popper, Karl (1963). Science: Conjecture and refutations.
week 12	Clark, A. [2003]. Natural-Born Cyborgs: Minds, technologies and the Future of Human Intelligence. Oxford University Press. Chapters 2 and 6 Coutinho, A. [2003]. "On doing science: a speech by Professor Antonio Coutinho". Economia, 4(1): 7-18, jan./jun. 2003. Knapp B, Bardenet R, Bernabeu MO, Bordas R, Bruna M, et al. (2015) Ten Simple Rules for a Successful Cross-Disciplinary Collaboration. PLoS Comput Biol11(4): e1004214. doi: 10.1371/journal.pcbi.1004214 Rubenstein, M., A. Cornejo, and R. Nagpal. 2014. “Programmable Self-Assembly in a Thousand-Robot Swarm.” Science 345 (6198) (August 14): 795–799. Schwartz, M.A. [2008]. "The importance of stupidity in scientific research". Journal of Cell Science, 121: 1771.
week 13	Agar, J. E. "The curious history of curiosity-driven research." Notes and Records: The Royal Society Journal of the History of Science (2018). Sandve, Geir Kjetil, Anton Nekrutenko, James Taylor, and Eivind Hovig. [2013]. "Ten Simple Rules for Reproducible Computational Research." PLoS Computational Biology 9 (10): 4. Weinberger CJ, Evans JA, Allesina S (2015) Ten Simple (Empirical) Rules for Writing Science. PLoS Comput Biol 11(4): e1004205. doi: 10.1371/journal.pcbi.1004205 Zhang, W. [2014]. "Ten Simple Rules for Writing Research Papers." PLoS Computational Biology 10 (1): e1003453.

Optional


Heims, S.G. [1991]. The Cybernetics Group. MIT Press. Chapters: 11, and 12.
McCulloch, W. and W. Pitts [1943], "A Logical Calculus of Ideas Immanent in Nervous Activity". Bulletin of Mathematical Biophysics 5:115-133.
Aleksander, I. [2002]. Understanding Information Bit by Bitî. In: It must be beautiful : great equations of modern science. G. Farmelo (Ed.), Granta, London.
Klir, G.J. [2001]. Facets of systems Science. Springer. Chapters: 8 and 11
Klir, G.J. and D. Elias [2003]. Architecture of Systems Problem Solving. Springer. Chapters: 3 and 4

For Presentations (Choose One)

Ackermann, K., Angus, S. D., and Raschky, P. A. (2017). The Internet as Quantitative Social Science Platform: Insights from a Trillion Observations. arXiv:1701.05632
Adamic, Lada A., Thomas M. Lento, Eytan Adar, and Pauline C. Ng. "Information evolution in social networks." In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, pp. 473-482. ACM, 2016.
Barabasi and Albert (1999) Emergence of Scaling in Random Networks, Science 296 (5439)
Eytan Bakshy, Solomon Messing, and Lada A. Adamic [2015] "Exposure to ideologically diverse news and opinion on Facebook." Science 5 June 2015: 348 (6239), 1130-1132.
Luís M. A. Bettencourt at al (2007) - Growth, innovation, scaling, and the pace of life in cities, PNAS, vol. 104 no. 17 7301-7306 + Shalizi, C.R. [2011]. "Scaling and Hierarchy in Urban Economies.", arxiv.org.
Bollen J, Crandall D, Junk D, Ding Y, Borner K. [2014] “From funding agencies to scientific agency: Collective allocation of science funding as an alternative to peer review”. EMBO Rep. DOI: 10.1002/embr.201338068
C. Cattuto, V. Loreto, L. Pietronero [2007] "Semiotic dynamics and collaborative tagging", PNAS 104(17), 1461
Clark, A. [2003]. Natural-Born Cyborgs: Minds, technologies and the Future of Human Intelligence. Oxford University Press. Chapters 2 and 6
R.B. Correia, L. Li, L.M. Rocha [2016]. "Monitoring potential drug interactions and reactions via network analysis of Instagram user timeliness". Pacific Symposium on Biocomputing. 21:492-503.
Eiben. A. and Jim Smith [2015]. "From evolutionary computation to the evolution of things." Nature 521, 476–482. doi:10.1038/nature14544
Erez, Zohar, et al. "Communication between viruses guides lysis–lysogeny decisions." Nature 541.7638 (2017): 488-493.
Dunn, M. C., Bourne, P. E., AAlberg, I., Appleton, G., Axton, M., and Baak, A. (2017). Building the biomedical data science workforce. PLOS Biology, 15(7), e2003082.
Freeth, Tony. 2014. “Eclipse Prediction on the Ancient Greek Astronomical Calculating Machine Known as the Antikythera Mechanism.” PloS One 9 (7) (January): e103275. doi:10.1371/journal.pone.0103275.
Jeremy A. Frimer, Karl Aquino, Jochen E. Gebauer, Luke (Lei) Zhu, and Harrison Oakes [2015] "A decline in prosocial language helps explain public disapproval of the US Congress" PNAS 2015 112 (21) 6591-6594; doi:10.1073/pnas.1500355112
A. Gates and L.M. Rocha. [2016] "Control of complex networks requires both structure and dynamics." Scientific Reports 6, 24456. doi: 10.1038/srep24456.
Gauvrit, N., Zenil, H., Soler-Toscano, F., Delahaye, J.-P., Brugger, P., Schuknecht, B., … Brugger, P. (2017). Human behavioral complexity peaks at age 25. PLOS Computational Biology, 13(4), e1005408.
Helbing, Dirk, Dirk Brockmann, Thomas Chadefaux, Karsten Donnay, Ulf Blanke, Olivia Woolley-Meza, Mehdi Moussaid et al. "Saving human lives: what complexity science and information systems can contribute." Journal of statistical physics 158, no. 3 (2015): 735-781.
Heylighen, Francis. 2015. “Stigmergy as a Universal Coordination Mechanism: Components, Varieties and Applications.” In Human Stigmergy: Theoretical Developments and New Applications (Studies in Applied Philosophy, Epistemology and Rational Ethics), edited by Ted; Lewis and Leslie Marsh, In Press.
Hofman, Jake M., Amit Sharma, and Duncan J. Watts. "Prediction and explanation in social systems." Science 355.6324 (2017): 486-488.
Hughes (2009) Quantification of artistic style through sparse coding analysis in the drawings of Pieter Bruegel the Elder. PNAS 107(4):1279–1283
Jonas, E., and Kording, K. P., (2017). Could a Neuroscientist Understand a Microprocessor? PLOS Computational Biology, 13(1), e1005268.
Thomas S. Kuhn (1970). Logic of discovery or Psychology of Research.
Kull, Deacon, Pattee, Kauffman[2012] . Approaches to biosemiotics. In Gatherings in Biosemiotics. Eds. S Rattasepp and T. Bennett. University of Tartu Press.
Yann LeCun, Yoshua Bengio and Geoffrey Hinton [2015]. "Deep learning" Nature 521, 436–444 (28 May 2015) doi:10.1038/nature14539
Danielle Li and Leila Agha [2015]. "Big names or big ideas: Do peer-review panels select the best science proposals?" Science 24 April 2015: 348 (6233), 434-438.
Loreto, Vittorio, et al. "Dynamics on expanding spaces: modeling the emergence of novelties." Creativity and Universality in Language. Springer International Publishing, 2016. 59-83.
Mann, R. P., and Helbing, D. (2017). Optimal incentives for collective intelligence. Proceedings of the National Academy of Sciences of the United States of America, 201618722.
Markov, Igor L. 2014. “Limits on Fundamental Limits to Computation.” Nature 512 (7513) (August 13): 147–154. doi:10.1038/nature13570.
Piantadosi, S. T.,et al (2011). Word lengths are optimized for efficient communication. PNAS, 108(9), 3526–3529.
Karl Popper (1963). Science: Conjecture and refutations.
Radicchi, F. (2008) Universality of citation distributions: Toward an objective measure of scientific impact. PNAS 105(45): 17268–17272.
Rubenstein, M., A. Cornejo, and R. Nagpal. 2014. “Programmable Self-Assembly in a Thousand-Robot Swarm.” Science 345 (6198) (August 14): 795–799.
Suderman, R., Bachman, J. A., Smith, A., Sorger, P. K., Deeds, E. J. (2017). Fundamental trade-offs between information flow in single cells and cellular populations. Proceedings of the National Academy of Sciences of the United States of America, 201615660.
Suzuki, R. et al (2006) Information entropy of humpback whale songs, J. Acoust. Soc. Am, 199(3), March
Scheffer (2009) Early-warning signals for critical transitions. Nature 461, 53-59 - doi:10.1038/nature08227
Schmälzle, R., Brook O’Donnell, M., Garcia, J. O., Cascio, C. N., Bayer, J., Bassett, D. S., … Falk, E. B. (2017). Brain connectivity dynamics during social interaction reflect social network structure. Proceedings of the National Academy of Sciences, 114(20), 5153–5158.
Wasserman, M., X.H.T. Zeng, and L.A.N. Amaral [2015]. “Cross-evaluation of metrics to estimate the significance of creative works”. PNAS 112 (5) 1281-1286, doi:10.1073/pnas.1412198112
I.B Wood, P.L. Varela, J. Bollen, L.M. Rocha, J. Gonçalves-Sá [2017]. Human Sexual Cycles are Driven by Culture and Match Collective Moods. arXiv:1707.03959.

Last Modified: December 17, 2017