Theory ::::::::::::::::::: Bibliography::::::::::::::::::::::Glossary::::::::::::::::::::::::White book

by Núria Vergés Bosch & Alexandra Haché

> Bibliography

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Ackoff, R. L. (1989). ‘From Data to Wisdom’, Journal of Applied Systems Analysis, 16, 3-9.
 
Batagelj, V. & Mrvar, A. (2004). Pajek – Analysis and Visualization of Large Networks, 77-104 in Graph Drawing Software eds. Jünger, M. & Mutzel, P., Berlin: Springer-Verlag.
 
Becker, H.S. (2000). What Should Sociology Look Like in the (Near) Future? Contemporary Sociology, 29(2), 333-336.
 
Beniger, J. R.  & Robyn, D.L. (1978). Quantitative graphics in statistics: A brief history. The American Statistician, 32(1),1-9.
 
Brandes, U., Raab J. &Wagner, D. (2001). Exploratory Network Visualization: Simultaneous Display of Actor Status and Connections, Journal of Social Structure, 2 (4)
 
Brandes, U., Kenis, P., & Wagner, D. (2003). Communicating Centrality in Policy Network Drawings. IEEE Transactions on Visualization and Computer Graphics, 9(2), 241-253.
 
Brandes, U., Kenis, P., Raab J., Schneider, V. &Wagner, D. (1999). Explorations into the Visualization of Policy Networks, Journal of Theoretical Politics, 11(1), 75-106.
 
Brandes, U. & Wagner, D. (2004): visone - Analysis and Visualization of Social Networks: 321-340 in Graph Drawing Software eds. Jünger, M. & Mutzel, P., Berlin: Springer-Verlag.
 
Brandes, U. & Erlebach, T. (Eds.) (2005). Network Analysis: Methodological Foundations. Lecture Notes in Computer Science Tutorial, vol. 3418, Berlin: Springer-Verlag.
 
Burt, R. (1991). Structure Reference Manual, Version 4.2. New York: Columbia University Press.

Börner, Katy, Chen, Chaomei, and Boyack, Kevin. (2003). Visualizing Knowledge Domains. In Blaise Cronin (Ed.), Annual Review of Information Science & Technology, Volume 37, Medford, NJ: Information Today, Inc./American Society for Information Science and Technology, chapter 5, pp. 179-255. 

Checkland, P.; Scholes, J. (1990). Soft Systems Methodology in Action. Chichester, Wiley.

Collin Ware, “Information Visualization: Perception for Design”, Morgan Kaufmann, San Francisco, USA, 2000.
 
Crosby, A. W. (1997). The Measure of Reality: Quantification and Western Society, 1250-1600. Cambridge: Cambridge University Press.

David L. Kao, Kwan-Liu Ma, “The Life Cycle of a Visualization Case Study”, IEEE Computer Graphics and Applications, Vol. 20, No. 5, 2000, pp. 29-31.

Dervin, B. (1999). Chaos, order, and Sense-Making: A proposed theory for information design. In R. Jacobson (Ed.), Information design (pp. 35-57). Cambridge, MA: MIT Press. Reeditado en: B. Dervin & L. Foreman-Wernet (junto a E. Lauterbach) (Eds.). (2003).

Ed H. Chi, John T. Riedl, “An Operator Interaction Framework for Visualization Systems”, Proceedings of the IEEE Symposium on Information Visualization (InfoVis’98), North Carolina, 1998, pp. 63-70.

Ed H. Chi, “A Taxonomy of Visualization Techniques Using Data State Reference Model”, Proceedings of the IEEE Symposium on Information Visualization (InfoVis’00), Salt Lake City, Utah, 2000, pp. 69-75.
 
Freeman L. C. (2000) Visualizing Social Networks, Journal of Social Structure 1 (1),
 
Freeman L. C. (2005). Graphic techniques for exploring social network data in Models and Methods in Social Network Analysis, eds. P. J. Carrington, J.Scott & S. Wasserman. Cambridge: Cambridge University Press.
 
Gahegan, M. & Brodaric, B. 2002. Computational and Visual Support for Geographical Knowledge Construction : Filling in the Gaps between Exploration and Explanation, Symposium on Geospatial Theory, Processing and Applications, Ottowa 2002

Horn, R. (1999a) "Information Design: The Emergence of a New Profession." in Jacobson, Robert (Ed.), Information Design, Cambridge MA, MIT Press

Horn, R. (1999b). The Argumentation Mapping Project.
 
Klovdahl, A. S. (1981). A note on images of networks. Social Networks. 3, 197-214.

MacEachren, A. M.; Kraak, M. J. (2001). Research challenges in geovisualization. Cartography and Geographic Information Systems, 28, (1), pp. 3-12.

Mei C. Chuah, Steven F. Roth, “On the Semantics of Interactive Visualizations”, Proceedings of the IEEE Symposium on Information Visualization (InfoVis’96), San Francisco, California, 1996, 29-36.

Michael J. Potel (ed), Ben Delaney, “VizSim Technology Helps Find Oil Faster”, IEEE Computer Graphics and Applications, Vol. 19, No. 2, 1999, pp. 10-16.

Nardi, B.; O'Day, V. (1999) Information ecologies. MIT Press, Cambridge, Mass.

Nooy, W. de, Mrvar, A. & Batagelj, V. (2004). Exploratory Social Network Analysis with Pajek. Cambridge/New York: Cambridge University Press

Northway, M. L. (1940). A Method for Depicting Social Relationships Obtained by Sociometric Testing, Sociometry, 3 (2), 144-150.

Pang Alex , Hans-Georg Pagendarm, “Visualization for Everyone”, IEEE Computer Graphics and Applications, Vol. 18, No. 4, 1998, pp. 47-48.

Raab, J. (2002a). Steuerung von Privatisierung. Eine Analyse der Steuerungsstrukturen der Privatisierung der ostdeutschen Werft- und Stahlindustrie 1990-1994. Wiesbaden: Westdeutscher Verlag.
 
Raab, J. (2002b). Where Do Policy Networks Come From?, Journal of Public Administration Research and Theory, 12 (4), 581-622.

Rasmussen, J. P., A.M.; Goodstein, L.P. (1994). Cognitive systems engineering. Chichester, Wiley.

Sense-Making Methodology reader: Selected writings of Brenda Dervin (pp. 325-340). Cresskill, NJ: Hampton Press.
Spence, R. (2000). Information visualization. Harlow, England: Addison-Wesley.

Shiffrin, Richard M. and Börner, Katy (Eds). (2004) Mapping Knowledge Domains PNAS 101 (Suppl. 1)  

Stuart K. Card, Jock Mackinlay, “The Structure of the Information Design Space”, Proceedings of the IEEE Symposium on Information Visualization (InfoVis’97), Phoenix, Arizona, 1997, pp. 92-99.

Stuart K. Card, Jock Mackinlay, Ben Shneiderman, “Readings in Information Visualization: Using Vision to Think”, Morgan Kaufmann, San Francisco, USA, 1999.

Sutcliffe, A. (1997) Task-related information analysis. International Journal of Human-Computer Studies 47, 223-57.
 
Tufte, E. R. (1983). The Visual Display of Quantitative Information. Graphics Press, Cheshire, Connecticut.
 
Tufte, E. R. (1997). Visual Explanations. Images and Quantities, Evidence and Narrative. Cheshire/Connecticut: Graphics Press
 
Tukey, J. (1972). Some Graphic and Seigraphic Displays: 293-316 in Statistical Papers in Honor of George W. Snedecor, ed. T. A. Bancroft. Ames: Iowa State University Press.
 
Wassermann, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press.

Wise, J.A. et al (1995). Visualizing the non-visual: spatial analysis and interaction with information from text documents. Proceedings of the 1995 IEEE Symposium on Information Visualization.
 
Whyte, W. F. (1943). Street Corner Society, Chicago: University of Chicago Press.

William Schroeder, Lisa Avila, William Hoffman, “Visualizing with VTK: A Tutorial”, IEEE Computer Graphics and Applications, Vol. 20, No. 5, 2000, pp. 20-27.

William Schroeder, Ken Martin, Bill Lorensen, “The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics”, Prentice Hall, 2nd edition, 1997.

William Schroeder, K. Martin, Lisa S. Avila, C. Charles Law, “The Visualization Toolkit User's Guide, Version 4.0”, Kitware, version 4.0, 2001.

Will Schroeder and Ken Marti,. Overview of Visualization,. In The Visualization Handbook, C. D. Hansen and C. R. Johnson, editors. Elsevier, 2004.

> Glossary

Algorithm: In mathematics and computer science, an algorithm is a procedure (a finite set of well-defined instructions) for accomplishing some task which, given an initial state, will terminate in a defined end-state. Informally, the concept of an algorithm is often illustrated by the example of a recipe, although many algorithms are much more complex; algorithms often have steps that repeat (iterate) or require decisions (such as logic or comparison). In most higher level programs, algortihms act in complex patterns, each using smaller and smaller sub-methods which are built up to the program as a whole. In most languages are isomorphic to functions or methods. source: wikipedia

API: Application Programming Interface. The specification of how a programmer writing an application accesses the behavior and state of classes and objects. source: sun developer network

APPLET: An applet is a program written in the Java programming language that can be included in an HTML page, much in the same way an image is included in a page. When you use a Java technology-enabled browser to view a page that contains an applet, the applet's code is transferred to your system and executed by the browser's Java Virtual Machine (JVM). source: sun developer network

Copyleft:describes a group of licenses applied to works such as software, documents, music, and art. Whereas copyright law is seen by the original proponents of copyleft as a way to restrict the right to make and redistribute copies of a particular work, a copyleft license uses copyright law in order to ensure that every person who receives a copy or derived version of a work can use, modify, and also redistribute both the work, and derived versions of the work. Thus, in a non-legal sense, copyleft is the opposite of copyright.source: wikipedia

Distribution: A software distribution is an installer of a specific software (or a collection of multiple, even an entire operating system) , already compiled and configured. It is generally the closest thing to a turnkey form of a usually GPL or open source source code for a software. It usually takes the form of either rpm, deb, tgz, msi, exe etc. installer and is downloadable from the Internet source: wikipedia .

FOAF: is a phrase used to refer to someone that one does not know well — literally, a friend of a friend. In some social sciences, the phrase is used as a half-joking shorthand for the fact that much of the information on which people act comes from distant sources (as in "It happened to a friend of a friend of mine") and cannot be confirmed. It is probably best known from urban legend studies. The term was popularized by Jan Harold Brunvand, the best-known writer of that field. It was apparently first published by Rodney Dale in his 1978 book The Tumour in the Whale - WH Allen ISBN 0426187105 - in which he discussed the "FOAFtale". The rise of social networking services has led to increased use of this term.source: wikipedia

Folksonomy: "a neologism combining "folk" and "taxonomy", refers to collaborative efforts to organize information on the Internet. More colloquially, this refers to a group of people cooperating spontaneously to organize information into categories. In contrast to formal classification methods, this phenomenon typically only arises in non-hierarchical communities, such as public websites. Instead of using a centralized form of classification, users are encouraged to assign freely chosen keywords, typically referred to as "tags", to pieces of information or data, a process known as "tagging". Examples of web services that use tagging include those designed to allow users to publish and share photographs, personal libraries, bookmarks, social software and most blog software, permitting authors to assign tags to each entry. source: wikipedia

GIS/GPS: These data can be of any kind: sales figures, revenues, population census, real estate, illness rates, etc. The fundamental issue that distinguishes it from other information systems is that of making the relationship between these data and the geographical coordinates of the Earth surface. They are mainly used in demography, town planning, natural resources management, business, marketing, logistics and distribution. source: infovis

Graphs: We can say that a graph is a set of nodes with links between them called edges or arcs. In a simple graph there’s only one arc between two nodes. If there’s more than one arc we call it a multigraph. If arcs can be followed in only one specific direction but not in the other we call it a directed graph or digraph and arcs become edges. If arcs begin and end in the same node making a loop, the resulting graph is called a pseudograph. Despite a graph seeming a very elementary structure, there are many features of graphs whose study has lead to a complete mathematical theory. (For more information you can take a look at the graph glossary by Chris Caldwell or the introduction to graph theory of the wikipedia). There are many ways to represent a graph. There are even complete congresses devoted to discussing how to do it; for example the International Symposium on Graph Drawing source: infovis

Hubs: A common connection point for devices in a network. Hubs are commonly used to connect segments of a LAN. A hub contains multiple ports. When a packet arrives at one port, it is copied to the other ports so that all segments of the LAN can see all packets. A passive hub serves simply as a conduit for the data, enabling it to go from one device (or segment) to another. So-called intelligent hubs include additional features that enables an administrator to monitor the traffic passing through the hub and to configure each port in the hub. Intelligent hubs are also called manageable hubs. A third type of hub, called a switching hub, actually reads the destination address of each packet and then forwards the packet to the correct port. source: webopedia

Information Arquitecture: The study of the organisation of information in order for the user to find their navigational way to the knowledge and understanding of information. According to Richard Saul Wurman an Information Architect is:
1.the individual who organises the patterns inherent in data, making the complex clear.
2.a person who creates the structure or map of information which allows others to find their personal paths to knowledge.
3.the emerging 21st century professional occupation addressing the needs of the age focused upon clarity, human understanding and the science of the organisation of information.
Information architecture has many things in common with Information Design. For this reason sometimes the two terms are confused. We consider it as part of Information Visualisation. source: infovis

Nodes: (1) In networks, a processing location. A node can be a computer or some other device, such as a printer. Every node has a unique network address, sometimes called a Data Link Control (DLC) address or Media Access Control (MAC) address.
(2) In tree structures, a point where two or more lines meet. source: webopedia

Opensource: describes general practices in production and development which promote access to the end product's sources. It is regarded by some as a philosophy and by others a pragmatic methodology. Developers and producers had used many different phrases and jargon words before open source became widely adopted, as the early Internet years provided a rapid convergence of socially diverse production models. With the revolutionary increase in interactive communities and their direct involvement with the Internet, open-source software became the most prominent face of open source. Even though the Internet started in 1969 with open standards like RFCs, it wasn't until 1998 that open source became a label applied to software to denote the same collaborative effort which began the Internet. The open source model allows for the concurrent use of different agendas and approaches in production, and it contrasts with more isolated models.source: wikipedia
Perl: Practical Extraction and Report Language (a backronym, see below) is an interpreted procedural programming language designed by Larry Wall. Perl borrows features from C, shell scripting (sh), awk, sed, Lisp, and (to a lesser extent) many other programming languages.source: wikipedia

Plugin: A plugin (or plug-in) is a computer program that can, or must, interact with another program to provide a certain, usually very specific, function. Typical examples are plugins to display specific graphic formats (e.g., SVG if the program doesn't support this format natively), to play multimedia files, to encrypt/decrypt email (e.g., PGP), or to filter images in graphic programs. The main program (a web browser or an email client, for example) provides a way for plugins to register themselves with the program, and a protocol by which data is exchanged with plugins. source: wikipedia
Psychogeography:Psychogeography was originally developed by the Lettrist International, as a hypergraphics in their system of unitary urbanism. The term has since been used by many others, leading to many variations in the practice which have included the following forms: Debordian; Literary; Generative or Algorithmic; and Quantum. Various factions claim to be or accuse each other of being: academic; occultist; avant-garde; proletarian; or revolutionary and pure psychogeographics.
During the 1980s and 90s while situationist theory became popular in academic circles, avant-garde, neoist and revolutionary groups emerged, developing the praxis in various ways. Psychogeography has since also become a standard device used in art and literature.Source: wikipedia

RSS: web feed formats, specified in XML and used for Web syndication. RSS is used by (among other things) news websites, weblogs and podcasting. The abbreviation is variously used to refer to the following standards:
Rich Site Summary (RSS 0.91)
RDF Site Summary (RSS 0.9 and 1.0)
Really Simple Syndication (RSS 2.0)
Web feeds provide web content or summaries of web content together with links to the full versions of the content, and other metadata. RSS in particular, delivers this information as an XML file called an RSS feed, webfeed, RSS stream, or RSS channel. In addition to facilitating syndication, web feeds allow a website's frequent readers to track updates on the site using an aggregator. Source: wikipedia

Semantic web:The Semantic Web is a web of data. There is lots of data we all use every day, and its not part of the web. I can see my bank statements on the web, and my photographs, and I can see my appointments in a calendar. But can I see my photos in a calendar to see what I was doing when I took them? Can I see bank statement lines in a calendar?
Why not? Because we don't have a web of data. Because data is controlled by applications, and each application keeps it to itself. The Semantic Web is about two things. It is about common formats for interchange of data, where on the original Web we only had interchange of documents. Also it is about language for recording how the data relates to real world objects. That allows a person, or a machine, to start off in one database, and then move through an unending set of databases which are connected not by wires but by being about the same thing. source: w3.org

Semantic zoom: Zoom of a graphic object that doesn't adhere to the pure scaling of its geometry but instead, searches at every level of detail a representation that maximises the understanding of its meaning. For example, at a certain zoom level, the object can be a dot, at another one it could be represented as a labeled box and still at another as a small rectangle with little characters representing text. More zooming could give us the whole document. source: infovis

Social networks: Social network analysis is focused on uncovering the patterning of people's interaction. It is about the kind of patterning that Roger Brown described when he wrote: "Social structure becomes actually visible in an anthill; the movements and contacts one sees are not random but patterned. We should also be able to see structure in the life of an American community if we had a sufficiently remote vantage point, a point from which persons would appear to be small moving dots. . . . We should see that these dots do not randomly approach one another, that some are usually together, some meet often, some never. . . . If one could get far enough away from it human life would become pure pattern."source: International Network for Social Network Analisis

TagCloud: TagCloud is an automated Folksonomy tool. Essentially, TagCloud? searches any number of RSS feeds you specify, extracts keywords from the content and lists them according to prevalence within the RSS feeds. Clicking on the tag's link will display a list of all the article abstracts associated with that keyword. source: tagcloud.com

Usability: Ability of a system to be used easily or efficiently. Usability is different than utility (ability of something to satisfy a need). The word usability arises in relation with the Human-Computer? interface studies. The interface of a program or of a web site can be useful because it performs the whole range of operations specified, but can be of low usability, for example, due to a high complexity that makes it difficult to be used efficiently for non-trained people. source: infovis

Visualization: Process of knowledge internalization by the perception of information. Although information is visualized mainly in a visual way, in this context Information Visualisation has to be understood in a more general way; as perception or internalization i.e. understanding. In principle this includes whatever media could be used to get the understanding, be it graphics, written text, sound, animations, etc. Information Visualisation relies basically on:
Human beings receive the bulk of information in a visual way due to the fact that this is the sense with more bandwidth, i.e. the one that yields more quantity of information. The symbolic capability of the human brain.
InfoVis? includes explicitly the following topics (among others):Information Design or Architecture Scientific Visualisation Graphic representations in general . Formation in the mind of the image of an abstract concept. Visualisation derives, in this context, from the graphic representation of variables associated to the concept that one wants to follow. For instance, a plot of the fever vs. time allows us to visualize the evolution of the illness. Fever (temperature) and time are the variables. Illness is the concept. source: infovis

> White book

You can download below all the repports that have been developepd through the project. They reflect the several steps and tasks that we did develop to be able to make those tools.