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An Eye Tracking Study on camelCase and under_score Identifier Styles

Programmers sit around and discuss many things about the methods and practices of writing code. One ageless discussion is how to name things. There are a few studies that review naming conventions and most of them just focus on doing it consistently across a language, group or organization.

This study, now a few years old doesn’t really come to any overwhelming conclusion that would persuade me to abandon underscores (or dashes) for CamelCase but is worth noting.

From the Abstract:

An empirical study to determine if identifier-naming conventions (i.e., camelCase and under_score) affect code comprehension is presented. An eye tracker is used to capture quantitative data from human subjects during an experiment. The intent of this study is to replicate a previous study published at ICPC 2009 (Binkley et al.) that used a timed response test method to acquire data. The use of eye-tracking equipment gives additional insight and overcomes some limitations of traditional data gathering techniques. Similarities and differences between the two studies are discussed. One main difference is that subjects were trained mainly in the underscore style and were all programmers. While results indicate no difference in accuracy between the two styles, subjects recognize identifiers in the underscore style more quickly.

via IEEE Xplore Abstract – An Eye Tracking Study on camelCase and under_score Identifier Styles.

Also available via the author’s web site.

Posted in dev, research.


Interesting statistics about the iTunes Store Terms and Conditions

The iTunes Store terms and conditions has about 17,637 words or about 26 generously large Web browser screen fulls. It has about 1744 unique words, 779 sentences, a lexical density of 16 percent and a readability score of 12.7 (which means it requires a greater than high school reading level, but not a law school graduate reading level).

Here’s a word cloud of the text from the fine people at Wordle:

Posted in tech.


GoogleBot vs iTunes Preview

Maybe Michael Bay should direct this next battle of the robot titans: Googlebot vs the Apple iTunes Web Servers – Dark of the Web?

It seems that as of today, the Apple iTunes Preview Web servers are not playing well with the googlebot. Take a look at the top three SERP descriptions for Angry Birds, one of the most popular iOS apps.

Google Search Engine Results Page for Angry Birds with useless description metadata

Maybe the Apple Webmasters need to get a plucky action hero to improve snippets with a meta description makeover.

Posted in games, search.


"What is" Instant Search with Google and Bing

It seems there are some rather large differences in what I get when Bing and Google do their instant search term suggestions for something as vague as “what is”:

what is bing instant search suggestions what is google instant search suggestions

These results may also imply something about how much data has been gathered and is used for my personalized versions of both searches too. However, I don’t remember searching for any of these as either a "what is" search or for any of the other search terms.

Parliament? Gout? Gluten? The Illuminati? Strange indeed, but perhaps the makings of a great mystery-thriller novel!

Posted in search.


Information Seeking on the Web

[Original Journal Article]

Chun Wei Choo, Brian Detlor and Don Turnbull

Keywords

world wide web, information seeking, information retrieval, browsing, web browser, searching, finding, behavioral model, user behavior, log analysis, quantitative, qualitative

Cite As

Chun Wei Choo, Brian Detlor and Don Turnbull (2000) Information Seeking on the Web: An Integrated Model of Browsing and Searching. First Monday, volume 5, number 2 (February 2000).

Abstract

This paper presents findings from a study of how knowledge workers use the Web to seek external information as part of their daily work. Thirty-four users from seven companies took part in the study. Participants were mainly IT specialists, managers, and research/marketing/consulting staff working in organizations that included a large utility company, a major bank, and a consulting firm. Participants answered a detailed questionnaire and were interviewed individually in order to understand their information needs and information seeking preferences. A custom-developed WebTracker software application was installed on each of their work place PCs, and participants’ Web-use activities were then recorded continuously during two-week periods. The WebTracker recorded how participants used the browser to seek information on the Web: it logged menu choices, button bar selections, and keystroke actions, allowing browsing and searching sequences to be reconstructed. In a second round of personal interviews, participants recalled critical incidents of using information from the Web.

Data from the two interviews and the WebTracker logs constituted the database for analysis. Sixty-one significant episodes of information seeking were identified. A model was developed to describe the common repertoires of information seeking that were observed. On one axis of the model, episodes were plotted according to the four scanning modes identified by Aguilar (1967), Weick and Daft (1983): undirected viewing, conditioned viewing, informal search, and formal search. Each mode is characterized by its own information needs and information seeking strategies. On the other axis of the model, episodes were plotted according to the occurrence of one or more of the six categories of information seeking behaviors identified by Ellis (1989, 1990): starting, chaining, browsing, differentiating, monitoring, and extracting. The study suggests that a behavioral framework that relates motivations (Aguilar) and moves (Ellis) may be helpful in analyzing patterns of Web-based information seeking.

Excerpt

Towards a Behavioral Model of Information Seeking on the Web

Aguilar’s modes of scanning and Ellis’ seeking behaviors may be combined and extended in a new behavioral model of information seeking on the Web. The figure below identifies four main modes of information seeking on the Web: undirected viewing, conditioned viewing, informal search, and formal search. For each mode, the figure indicates which information seeking activities or moves are likely to occur frequently, as suggested by theory.

Figure 3: Behavioral Modes and Moves of Information Seeking on the Web

Starting Chaining Browsing Differentiating Monitoring Extracting
Undirected Viewing Identifying, selecting, starting pages and sites Following links on initial pages
Conditioned Viewing Browsing entry pages, headings, site maps Bookmarking, printing, copying;
Going directly to known site
Revisiting ‘favorite’ or bookmarked sites for new information
Informal Search Bookmarking, printing, copying;
Going directly to known site
Revisiting ‘favorite’ or bookmarked sites for new information Using (local) search engines to extract information
Formal Search Revisiting ‘favorite’ or bookmarked sites for new information Using search engines to extract information

Undirected Viewing

In the undirected viewing mode on the Web, we expect to see many instances of starting and chaining. Starting occurs when viewers begin their Web use on pre-selected default home pages, or when they visit a favorite page or site to begin their viewing (such as news, newspaper, or magazine sites). Chaining occurs when viewers notice items of interest (often by chance), and then follow hypertext links to more information on those items. Forward chaining of the sort just described is the most typical during undirected viewing. Backward chaining is also possible, since search engines can be used to locate other Web pages that point to the site that the user is currently at.

Conditioned Viewing

In the conditioned viewing mode on the Web, we expect browsing, differentiating, and monitoring to be common. Differentiating occurs as viewers select Web sites or pages that they expect to provide relevant information. Sites may be differentiated based on prior personal visits, or recommendations by others (such as word-of-mouth or published reviews). Differentiated sites are often bookmarked. When visiting differentiated sites, viewers browse the content by looking through tables of contents, site maps, or list of items and categories. Viewers may also monitor highly differentiated sites by returning regularly to browse, or by keeping abreast of new content (through, for example subscribing to newsletters that report new material on the site).

Informal Search

During informal search on the Web, we expect differentiating, extracting, and monitoring to be typical. Again, informal search is likely to be attempted at a small number of Web sites that have been differentiated by the individual, based on the individual’s knowledge about these sites’ information relevance, quality, affiliation, dependability, and so on. Extracting is relatively “informal” in the sense that searching would be localized to looking for information within the selected site(s). Extracting is also likely to make use of the basic, ‘simple’ search features or commands of the local search engine, in order to get at the most important or most recent information, without attempting to be comprehensive. Monitoring becomes more proactive if the individual sets up push channels or software agents that automatically find and deliver information based on keywords or subject headings.

Formal Search

During formal search on the Web, we expect primarily extracting operations, with some complementary monitoring activity. Formal search makes use of search engines that cover the Web relatively comprehensively, and that provide a powerful set of search features that can focus retrieval. Because the individual wishes not to miss any important information, there is a willingness to spend more time in the search, to learn and use complex search features, and to evaluate the sources that are found in terms of quality or accuracy. Formal search may be two-staged: multi-site searching that identifies significant sources is then followed by within-site searching. Within-site searching may involve fairly intensive foraging. Extracting may be supported by monitoring activity, again through services such as Web site alerts, push channels/agents, and e-mail announcements, in order to keep up with late-breaking information.

References in this publication

  • Francis J. Aguilar, 1967. Scanning the Business Environment. New York: Macmillan.
  • Francis J. Aguilar, 1988. General Managers in Action. New York: Oxford University Press.
  • L.D. Catledge and J. E. Pitkow, 1995. “Characterizing Browsing Strategies in the World Wide Web”. World Wide Web Conference.
  • Shan-Ju Chang and Ronald E. Rice, 1993. “Browsing: A Multidimensional Framework,” In: Martha E. Williams (editor). Annual Review of Information Science and Technology. Medford, N.J.: Learned Information.
  • Chun Wei Choo, 1998. Information Management for the Intelligent Organization: The Art of Scanning the Environment. Second edition. Medford, N.J.: Information Today.
  • Chun Wei Choo, Brian Detlor, and Don Turnbull, 1998. “A Behavioral Model of Information Seeking on the Web: Preliminary Results of a Study of How Managers and IT Specialists Use the Web,” In: Proceedingsof 61st ASIS Annual Meeting held in Pittsburgh, Pa., edited by Cecilia M. Preston, volume 35, pp. 290-302. Medford, N.J.: Information Today.
  • Richard L. Daft and Karl E. Weick, 1984. “Toward a Model of Organizations as Interpretation Systems,” Academy of Management Review,volume 9, number 2, pp. 284-295.
  • David Ellis and Merete Haugan, 1997. “Modelling the Information Seeking Patterns of Engineers and Research Scientists in an Industrial Environment,” Journal of Documentation,volume 53, number 4, pp. 384-403.
  • David Ellis, D. Cox, and K. Hall, 1993. “A Comparison of the Information Seeking Patterns of Researchers in the Physical and Social Sciences,” Journal of Documentation,volume 49, number 4, pp. 356-369.
  • David Ellis, 1989. “A Behavioural Model for Information Retrieval System Design,” Journal of Information Science, volume 15, numbers 4/5, pp. 237-247.
  • John C. Flanagan, 1954. “The Critical Incident Technique,” Psychological Bulletin, volume 51, number 4, pp. 327-358.
  • Bernardo A. Huberman, Peter L. Pirolli, James E. Pitkow, and Rajan M. Lukose, 1998. “Strong Regularities in World Wide Web Surfing,” Science,volume 280, number 5360, pp. 94-97.
  • Gary M. Marchionini, 1995. Information Seeking in Electronic Environments.Cambridge, Eng.: Cambridge University Press.
  • Linda Tauscher and Saul Greenberg, 1997. “How People Revisit Web Pages: Empirical Findings and Implications for the Design of History Systems,” International Journal of Human-Computer Studies, volume 47, pp. 97-137.
  • Linda Tauscher and Saul Greenberg, 1997. “Revisitation Patterns in World Wide Web Navigation,” In: Proceedingsof CHI 97 Human Factors in Computing Systems held in Atlanta, Georgia, edited by Steven Pemberton, pp. 399-406.
  • Karl E. Weick and Richard L. Daft, 1983. “The Effectiveness of Interpretation Systems,” In: Organizational Effectiveness: A Comparison of Multiple Models,edited by Kim S. Cameron and David A. Whetten, pp. 71-93. New York: Academic Press.
  • T. D. Wilson, 1997. “Information Behaviour: An Interdisciplinary Perspective,” Information Processing & Management, volume 33, number 4, pp. 551-572.

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PIKII – A Personal Information and Knowledge Infrastructure Integrator

[PDF]

K. Andrew Edmonds, James Blustein and Don Turnbull

Keywords

information management, personal information management, pim, hypertext, wiki, personalization, information organization, blogging, computer-supported cooperative work

Cite As

K. Andrew Edmonds, James Blustein and Don Turnbull (2006). A Personal Information and Knowledge Infrastructure Integrator. Journal of Digital Information, 5(1).

Abstract

The Next Big Thing is being grown organically, cultivated by software developers and pruned by personal Weblog publishers. The rising Weblogging space of the Internet is looking more like traditional hypertext than the Web of the 1990s. The ways in which Weblogging has evolved beyond the previous limitations of the Web as hypertext, and the ways Weblogging is evolving towards common-use hypertext destined to play a critical role in everyday life, will be explored. We have a vision of a universal information management system built on extending the traditional hypertext framework. In our utopian future, everyone will use tools descended from today’s blogs to structure, search and share personal information, as well as to participate in shared discussion. We begin by expressing a vision of common-use hypertext for information management and interpersonal communication.

This vision is grounded in the rapid evolution of Weblogs and known issues in information systems and hypertext. The practical implications of who will use these systems, and how, is expanded as usage scenarios for Weblogs now and in the future. After recapping the current issues facing the Weblogging community, we look to the long-range implementation issues with optimism. Our system is forward-looking yet realistic. The activities the system will support are extrapolated from recent developments in the online community, and most of the sketches of implementation are based on current approaches. It is of more than passing interest that the features we extrapolate were all described by Nelson as early hypertext ideals. Of particular interest is that the features are now being implemented because of perceived immediate need by communities of interest.

Excerpt

Looking Ahead
An enriched personal history of interaction with any networked information, organized by time, location or activity will add much-needed context to ubiquitous computing and its potential for always-on history collection. This history will be available in the universal information manager for user controlled contributions to a spectrum of distributed access, from private to public and dynamic to archival. Already the practice of moblogging (i.e. the use of digital camera-equipped cell phones to take and share photographs taken anywhere [8]) is expanding the abilities of personal information collections. Moreover, this expansion of digital information collection leads to a multimedia-rich world of individual history, shareable with family, friends and others as permitted. Flexible recombinations of media will allow the easy assemblage of interlinked hypermedia scrapbooks in the PIKII: to catalog the interactions of subsets of people, places and activities enabled by automatically created metadata at the time of media creation, through subsequent interaction and by explicit tagging.

Systems that generate and use implicit tagging and information classification are also key elements of the PIKII. Just as Google uses popularity and relevance measures to sort and rank Web information, authoring tools will enable the use of information annotation in appropriate metadata dimensions to add information about a link or node of information. Such link type information might be, at its simplest, an affective score or a value along a more sophisticated dimension such as typing the rhetorical relationship. This information, when combined with personal history, information content, the interaction with a peer’s data (expressed in any number of ways from a blog post, shared access to personal information or popularity measures), will be key factors that help make information searching more personally relevant.
Beyond singular units of information, the PIKII will provide interfaces for mapping discussions distributed across the Internet and could be the catalyst for widescale adoption of link types in more traditional discussion systems. Affective components of link types may dominate the social aspects of Weblog communication due to simplicity in authoring and dynamic typing through the explicit and implicit methods previously noted. While transclusion and annotation have formed the basis for widespread adoption of hypertext for Weblog communication, the proposed link and node type additions, as well as more general metadata improvements, will facilitate the intertwingling of information, but with an intelligence to help manage attention and provenance

In many ways, this article aligns with a subset of the goals of the semantic Web space (Berners-Lee et al. 2001), which also promises utility for metadata-enriched information about everyday events. In an ideal world, service providers and vendors, software tools and agencies would offer information in standardized, metadata-enriched, machine readable formats suitable for semantic Web intentions. Many chores might be automated, as in the arrangement of health care for example.
Expanding from the semantic Web, a system of successful micropayment schemes may arise, whether they be karmic and barter schemes or involve actual funds transfer that may drive the received value of both preparing and accessing this semantically-enriched information. Information exchanges with knowledgeable experts and the distribution of favors through a Friend-of-a-Friend network may prove to be more valuable and more popular than micropayments. As we have seen, a key to the widespread adoption of Web information to date is the ability to connect openly with individuals and groups who share common interests, a trend that should continue.

This combination of personal, aggregate and networked contextualizing of information nodes and their linking methods has wide-ranging potential for many dimensions of personal knowledge management efforts. The critical need for personal information management and publishing is to bring the fluency that Weblogging software has created for publishing to the process of connecting and integrating information, leading to a storehouse of personal knowledge.

Conclusion
We have a vision of a universal information management system built on a hypertext framework. In our utopian future, everyone will use tools descended from today’s blogs to structure, search and share personal information as well as to participate in shared discussion. Just as Nelson (1990) envisioned a network where everything is deeply intertwingled, we propose that not only everything, but everyone can belong to several, possibly overlapping and discordant, intertwingled communities of interest. These communities will form dense networks of information linkage, allowing many types of structured and unstructured content to continually expand and weave even more interconnected webs of relationships.
People are motivated to communicate many aspects of their lives to many different audiences. The rapid growth of Weblogging has affirmed the appeal of hypertext and validated the notion of individuals as content producers. The availability of personal hypertext systems, with support for granular control over sharing nodes, will increase this adoption for both Weblog authors and readers.
The growth in the amount of digitally captured and hypertextualized information in the coming years will be even more astounding than the growth of the Web over the past ten years. There are significant technical challenges to overcome, but the standards-based organic growth of Weblogs and the Internet shows methods by which these challenges might be overcome. Rejecting the Web as not-hypertext is missing the point. The Web is an incubator for a continuously evolving system of content, user interests and supporting technologies.

References in this publication

  • Allen, T. J. (1977) “Information needs and uses”. In Annual Review of Information Science and Technology, Vol. 4, pp. 3 – 29
  • Anderson, Corin R. and Horvitz, Eric (2002) “Web Montage: A Dynamic Personalized Start Page”. Eleventh International World Wide Web Conference, Honolulu, HI, May  http://www2002.org/CDROM/refereed/468/
  • Berners-Lee, Tim, Hendler, James and Lassila, Ora (2001) “The Semantic Web”. Scientific American, 284(5):34 – 43, May http://www.scientificamerican.com/article.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21&catID=2
  • Berners-Lee, Tim (1999) Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web (HarperCollins)
  • Bernstein, Mark (2003) IPodlings, 18 November http://markbernstein.org/Nov0301.html#note_35207
  • Blustein, James and Staveley, Mark (2001) “Methods of Generating and Evaluating Hypertext”.  In Annual Review of Information Science and Technology, Vol. 35, chapter 6, edited by Martha E. Williams (American Society for Information Science and Technology)
  • Brin, S. and Page, L. (1998) “The anatomy of a large-scale hypertextual web search engine”. Proceedings of the 7th International WWW Conference, pp. 107 – 117  http://www7.scu.edu.au/programme/fullpapers/1921/com1921.htm
  • Brockman, Katherine (2003) “America Online Members Capture The Spirit of America – In Pictures”. AOL/TimeWarner press announcement, 1 July http://media.aoltimewarner.com/media/press_view.cfm?release_num=55253250
  • Bush, Vannevar (1945) “As We May Think”. The Atlantic Monthly, 176(1):101-108, July http://www.theatlantic.com/unbound/flashbks/computer/bushf.htm
  • Chi, Ed H., Pirolli, Peter and Pitkow, James (2000) “The scent of a site: a system for analyzing and predicting information scent, usage, and usability of a Web site”. In Proceedings of the  SIGCHI Conference on Human Factors in Computing Systems, The Hague, The Netherlands, pp. 161 – 168  http://citeseer.nj.nec.com/chi00scent.html
  • Claypool, Mark, Brown, David, Le, Phong and Waseda, Makoto (2001) “Inferring User Interest”. IEEE Internet Computing, November/December http://www.cs.wpi.edu/%7Eclaypool/papers/iui/
  • Conklin, Jeff and Begeman, M. L. (1998) “gIBIS: A hypertext tool for exploratory policy discussion”. ACM Transactions on Office Information Systems, 6(4):303-331, October
  • Decrem, Bart (2003) “Mozilla.org Announces Launch of the Mozilla Foundation to Lead Open-Source Browser Efforts”. Mozilla.org, 15 July http://www.mozilla.org/press/mozilla-foundation.html
  • Engelbart, Douglas C. (1962) “Augmenting Human Intellect: A Conceptual Framework”. Summary Report AFOSR-3223 under Contract AF 49(638)-1024, SRI Project 3578 for Air Force Office of Scientific Research, Stanford Research Institute, Menlo Park, CA, October http://www.bootstrap.org/augdocs/friedewald030402/augmentinghumanintellect/ahi62index.html
  • Franzen, Kristofer and Karlgren, Jussi (2000) “Verbosity and Interface Design” SICS Technical Report T2000:04 (presented at AAAI Spring Symposium 1997) http://citeseer.nj.nec.com/313985.html
  • Furner, Jonathan, Ellis, David and Willett, Peter (1999) “Inter-linker consistency in the manual construction of hypertext documents”. ACM Computing Surveys, 31(4es) http://polaris.gseis.ucla.edu/jfurner/csurv00.pdf
  • Gilmore, Dan (2003) “Google Buys Pyra: Blogging Goes Big-Time”. SiliconValley.com, February 15 http://weblog.siliconvalley.com/column/dangillmor/archives/000802.shtml
  • Good, Nathaniel, Shafer, Ben, Konstan, Joe, Borchers, A., Sarwar, B., Herlocker, Jon and Riedl, John (1999) “Combining Collaborative Filtering with Personal Agents for Better Recommendations”. In Proceedings of the 1999 Conference of the American Association of Artificial Intelligence ( AAAI-99), pp. 439-446 http://citeseer.nj.nec.com/good99combining.html
  • Grossman, Wendy (1987) net.wars (NYU Press)
  • Kleinberg, J. (1998) “Authoritative sources in a hyperlinked environment”. Proceedings of the Ninth ACM-SIAM Symposium on Discrete Algorithms. Also appears as IBM Research Report RJ 10076, May 1997 http://citeseer.nj.nec.com/87928.html
  • Kuhlman, Ashby (2002) When is a link an endorsement? September 6 http://www.ashbykuhlman.net/blog/2002/09/06/0546
  • Losee, Robert M. and Paris, Lee Anne H. (1999) “Measuring Search-Engine Quality and Query Difficulty: Ranking with Target and Freestyle”. Journal of the American Society for Information Science and Technology, 50(10):882-889 http://www.ils.unc.edu/%7Elosee/par/paril.html
  • Nelson, Theodor Holm (1990) Literary Machines, edition 90.1 (The Distributors, 702 South Michigan, South Bend, IN 46601-3122)
  • Nielsen, Jakob (2001) “Search: Visible and Simple”. Alertbox, 13 May 2001 http://www.useit.com/alertbox/20010513.html
  • Pausch, R. and Detmer, J. (1990) “Node Popularity as a Hypertext Browsing Aid”. Electronic Publishing: Origination, Dissemination and Design, 3(4):227 – 234, November http://cajun.cs.nott.ac.uk/compsci/epo/papers/volume3/issue4/ep035rp.pdf
  • Phelps, Thomas A. and Wilensky, R. (2001) “The Multivalent Browser: A Platform for New Ideas”. Proceedings of Document Engineering, Atlanta, GA, November
  • Pitkow, James, Schütze, Hinrich, Cass, Todd, Cooley, Rob, Turnbull, Don, Edmonds, Andy, Adar, Eytan and Breuel, Thomas (2002) “Personalized Search”. Communications of the ACM, 45(9), September
  • Pratik, Dave, Karadkar, Unmil P., Furuta, Richard, Francisco-Revilla, Luis, Shipman, Frank and Dash, Suvendu (2003) “Navigation, Path-centric browsing, Navigation metaphors, Directed paths, Walden’s Paths, Path Engine”. In Proceedings of the Fourteenth ACM Conference on Hypertext and Hypermedia, Nottingham, UK, August
  • Pu, Hsiao-Tieh, Chuang, Shui-Lung and Yang, Chyan (2002) “Subject Categorization of Query Terms for Exploring Web Users’ Search Interests”. Journal of the American Society for Information Science and Technology, 53(8):617-630
  • Rheingold, Howard (2002) The Virtual Community: Homesteading on the Electronic Frontier, revised edition (MIT Press) http://www.well.com/user/hlr/vcbook/
  • schraefel, m.c. and Zhu, Yuxiang (2001) “Interaction Design for Web-Based, Within-Page Collection Marking and Management”. In Proceedings of the Twelfth ACM Conference on Hypertext and Hypermedia, Arhus, Denmark, August
  • Selfe, Cynthia and Boese, Christine (2003) The Clemson Laptop Program: Insiders’ Perspectives http://www.nutball.com/laptopresearch/
  • Sullivan, Danny (2003a) “Nielsen NetRatings Search Engine Ratings”. Search Engine Watch, 23 February http://www.searchenginewatch.com/reports/article.php/2156451
  • Sullivan, Danny (2003b) “comScore Media Metrix Search Engine Ratings”. Search Engine Watch, 16 August http://www.searchenginewatch.com/reports/article.php/2156431
  • Tague-Sutcliffe, Jean (1995) Measuring Information: An Information Services Perspective (Academic Press)
  • Tauscher, Linda and Greenberg, Saul (1997) “How people revisit web pages: empirical findings and implications for the design of history systems”. International Journal of Human Computer Studies, 47(1):97-138 http://ijhcs.open.ac.uk/tauscher/tauscher-01.html
  • Trigg, Randall H. and Weisner, Mark (1986) “TEXTNET: A network-based approach to text handling”. ACM Transactions on Office Information Systems, 4(1):1-23, January
  • Trott, Mena and Trott, Ben (2002) Feature: TrackBack, 10 June http://www.movabletype.org/trackback/archives/2002_06.html
  • Walker, Jill (2002) “Links and power: the political economy of linking on the Web”. In Proceedings of the Thirteenth ACM Conference on Hypertext and Hypermedia (ACM Press), pp. 72 – 73
  • Walker, Jill (2003) “Definition of weblog”. To appear in Routledge Encyclopedia of Narrative Theory, 28 June 2003 version http://huminf.uib.no/%7Ejill/archives/blog_theorising/final_version_of_weblog_definition.html
  • Wexelblat, Alan and Maes, Pattie (1997) “Using History to Assist Information Browsing”. In  RIAO’97: Computer-Assisted Information Retrieval on the Internet, Montreal
  • Winer, Dave (2003) RSS 2.0 Specification http://blogs.law.harvard.edu/tech/rss

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Information Architecture

[PDF]

Andrew Dillon and Don Turnbull

Keywords

information architecture, web design, world-wide web, interaction design, user experience, information design

Cite As

Andrew Dillon & Don Turnbull (2006). Information Architecture. Encyclopedia of Library and Information Science, 2006 Edition. Taylor & Francis.

Introduction

Information architecture has become one of the latest areas of excitement within the library and information science (LIS) community, largely resulting from the recognition it garners from those outside of the field for the methods and practices of information design and management long seen as core to information science.

The term, information architecture (IA), was coined by Richard Wurman in 1975 to describe the need to transform data into meaningful information for people to use, a not entirely original idea, but cer- tainly a first-time conjunction of the terms into the now common IA label. Building on concepts in archi- tecture, information design, typography, and graphic design, Wurman’s vision of a new field lay dormant for the most part until the emergence of the World Wide Web in the 1990s, when interest in information organization and structures became widespread. The term came into vogue among the broad web design community as a result of the need to find a way of communicating shared interests in the underlying organization of digitally accessed information.

Excerpt

Research Issues in IA

Pure research in IA is rare, the field borrowing more from outside as needed than tackling research ques- tions directly. However, as the process of IA has become structured and recognized, dedicated research for IA is beginning to take form, driven largely by practitioners seeking answers to design questions.
The major theme in IA research is the study of navigation and how people find what they are looking for in an information space. From concerns with labeling and menu structures to the development of models of navigation behavior there are now significant research publications dealing with topics of direct relevance to IA.[10,11] True, most of this work is still borrowed from outside, but this is subject to change as more academic researchers become involved in the field.

There is also significant work that extends examina- tions of navigation into areas such as the perception of information shape or the emergence of web genres and their exploitation for design.[7,12] This research aims to uncover the interaction between various structural forms of information space and the user, employing a socio-cognitive based analytical approach to explain- ing and predicting use.

Another central theme for IA research is search behavior and the underlying design of efficient search mechanisms. Again, this research not only draws on the history of such work for information retrieval but also contains new contributions dealing with faceted metadata and image databases.[13–15]

Indeed, it is difficult to bound work exclusively as the province of IA because concerns with organization of information and user search and navigation of information spaces have such a long history. It is likely that for the foreseeable future, IA will remain a net borrower of intellectual research from other disciplines until such time as dedicated venues for IA research publications emerge. That said, the need to understand how best to design and implement IAs will remain an important driver of research work.

References in this publication

  1. Rosenfield, L.; Peter, M. Information Architec- ture for the World Wide Web: Designing Large- Scale Web Sites; O’Reilly & Associates, Inc.: Sebastopol, CA, 2002.
  2. Wurman, R.S., Bradford, P., Eds.; Information Architects; Graphis Press: Zurich, Switzerland, 1996.
  3. Dillon, A. Information architecture in JASIST? J. Am. Soc. Inf. Sci. Technol. 2002, 53 (10), 821– 823.
  4. Weibel, S.L. The Dublin Core: a simple content description model for electronic resources. Bull. Am. Soc. Inf. Sci. Technol. 1997, 24 (1).
  5. Beckett, D.; McBride, B., Eds.; RDF=XML Syntax Specification (Revised): W3C Recommendation 10 February 2004. World Wide Web Consortium, Cambridge, MA., http://www.w3. org/TR=2004/REC-rdf-syntax-grammar-20040210/ (accessed Mar 29 2005).
  6. Instone, K. Fun with faceted browsing. American Society of Information Science and Technology Information Architecture Summit, Austin, TX, Feb 28, 2004.
  7. Dillon, A. Spatial semantics: how users derive shape from information spaces. J. Am. Soc. Inf. Sci. 2000, 51 (6), 521–528.
  8. Nielsen, J. Designing Web Usability; New Riders: Indianapolis, 2000.
  9. Helander, M.; Landauer, T.; Prabhu, P.V. Hand- book of Human Computer Interaction; North- Holland: Amsterdam, 1997.
  10. Jacko, J.A.; Slavendy, G. Hierarchical menu design: breadth, depth and task complexity. Percept. Motor Skills 1996, 82, 1187–1201.
  11. Pirolli, P.L.; Fu, W. SNIF-ACT: a model of infor- mation foraging on the World Wide Web. 9th International Conference on User Modeling, Johnstown, PA, Jun 22–26, 2003.
  12. Kwasnik, B.; Crowston, K. A framework for creating a faceted classification for genres. Hawaii International Conference on Systems Science (HICSS 04), Los Alamitos, CA, Jan 2004.
  13. Bates, M.J. The design of browsing and berry- picking techniques for the on-line search interface. Online Rev. 1989, 13, 407–424.
  14. Yee, K.; Swearingen, K.; Li, K.; Hearst, M. Faceted metadata for image search and browsing. Proceedings of CHI’03, Annual Conference of the ACM SIGCHI, New York, Apr 2003; ACM Press: New York, 401–408.
  15. Wildemuth, B.; Marchionini, G.; Yang, M.; Geisler, G.; Wilkens, T.; Hughes, A.; Gruss, R. How fast is too fast? Evaluating fast forward surrogates for digital video. ACM/IEEE Joint Conference on Digital Libraries, Los Alamitos, CA, Jun 2003; 221–230. I
  16. Berners-Lee, T. The World-Wide Web. Commun. ACM 1994, 37 (8), 76–82.
  17. Lyman, P.; Kahle, B. Archiving digital cultural artifacts: organizing an agenda for action. D- Lib Mag. 1998, 4 (7); http://www.dlib.org=dlib/july98/07lyman.html (Apr 5, 2005).
  18. Berners-Lee, T.; Hendler, J.; Lassila, O. The Semantic Web. Sci. Am. 2001, 284 (5), 34–43.

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I often mention something I have heard in a podcast and am asked what podcasts I listen to. Here is a list of my favorite podcasts, with a few comments.

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Methodologies for Understanding Web Use with Logging in Context

Methodologies for Understanding Web Use with Logging in Context

[PDF]

Don Turnbull

Abstract

This paper describes possible approaches of data collection and analysis methods that can be used to understand Web use via logging. First, a method devised by Choo, Detlor, & Turnbull (1998, 1999 & 2000) that can be used to offer a comprehensive, empirical foundation for understanding Web logs in context by gaining insight into Web use from three diverse sources: an initial survey questionnaire, usage logs gathered with a custom-developed Web tracking application and follow-up interviews with study participants. Second, a method of validating different types of Web use logs is proposed that involves client browser trace logs, intranet server and firewall or proxy logs. Third and finally, a system is proposed to collected and analyze Web use via proxy logs that classify Web pages by content.

Excerpt

It is often thought that in some configurations, client browsing application local caching settings may influence server-based logging accuracy. If it is not efficient to modify each study participant’s browser settings (or that temporarily modifying participants browser settings for the study period affects true Web use) a method of factoring in what may be lost due to local cache may be applied. … By tuning intranet server logging settings and collecting and analyzing these logs, some initial measurement of the differences that client browser caching makes in accurate firewall logs can be made. Comparisons to access on the organizations intranet Web server logs such as total page requests per page, time to load, use of REST or AJAX interaction and consistent user identification can be made to the more raw logging from the firewall logs collected

Update

What’s novel about this paper is the introduction of using different datasets to validate or triangulate the veracity and accuracy of log data. Often, logs are collected and processed without context to explain subtle interaction patterns, especially in relation to user behavior. By coordinating a set of quantitative resources, often with accompanying qualitative data, a much richer view of Web use is achieved. This is worth remembering when relying on Web Analytics tools to form a picture of a Web site’s use or set of Web user interactions: you need to go beyond the basic statistical measures (often far beyond what typical log analysis software provides, certainly by their default reports) and design new analysis techniques to gain understanding.

Keywords

browser history, firewall logs, intranet server logs, web use, survey, questionnaire, client application, webtracker, interview, methodology, logs, server logs, proxy, firewall, analytics, content classification, client trace, transaction log analysis, www

Cite As

Turnbull, D. (2006). Methodologies for Understanding Web Use with Logging in Context. Paper presented at the The 15th International World Wide Web Conference, Edinburgh, Scotland.

References in this publication

  • Auster, E., & Choo, C. W. (1993). Environmental scanning by CEOs in two Canadian industries. Journal of the American Society for Information Science, 44(4), 194-203.
  • Catledge, L. D., & Pitkow, J. E. (1995). Characterizing Browsing Strategies in the World-Wide Web. Computer Networks and ISDN Systems, 27, 1065-1073.
  • Choo, C.W., Detlor, B. & Turnbull, D. (1998). A Behavioral Model of Information Seeking on the Web — Preliminary Results of a Study of How Managers and IT Specialists Use the Web. Proceedings of the 61st Annual Meeting of the American Society of Information Science, 290-302.
  • Choo, C.W., Detlor, B. & Turnbull, D. (1999). Information Seeking on the Web – An Integrated Model of Browsing and Searching. Proceedings of the 62nd Annual Meeting of the American Society of Information Science, Washington, D.C.
  • Choo, C.W., Detlor, B. & Turnbull, D. (2000). Web Work: Information Seeking and Knowledge Work on the World Wide Web. Dordrecht, The Netherlands, Kluwer Academic Publishers.
  • Cuhna, C.R., Bestavros, A. & Crovella, M.E. (1995). Characteristics of WWW Client-Based Traces. Technical Report #1995-010. Boston University, Boston MA.
  • Flanagan, J. C. (1954). The critical incident technique. Psychological Bulletin 51(4), 327-358.
  • Jansen, B. J., Spink, A. & Saracevic, T. (2000) Real life, real users, and real needs: a study and analysis of user queries on the Web. Information Processing & Management, Volume 36, Issue 2, pp 207-227.
  • Jansen, B. J. (2005) Evaluating Success in Search Systems. Proceedings of the 66th Annual Meeting of the American Society for Information Science & Technology. Charlotte, North Carolina. 28 October – 2 November.
  • Kehoe, C., Pitkow, J. & Rogers, J. (1998). GVU’s Ninth WWW User Survey Report. http://www.gvu.gatech.edu/user_surveys/survey-1998-04.
  • Pitkow, J. and Recker, M. (1994). Results from the first World-Wide Web survey. Special issue of Journal of Computer Networks and ISDN systems, 27, 2.
  • Pitkow, J. (1997, April 7-11). In Search of Reliable Usage Data on the WWW. Sixth International World Wide Web Conference Proceedings, Santa Clara, CA.
  • Rousskov, A. & Soloviev, V. (1999) A performance study of the Squid proxy on HTTP/1.0. World Wide Web., 2, 1-2, pp 47 – 67.

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Rating, Voting & Ranking: Designing for Collaboration & Consensus

Rating, Voting & Ranking: Designing for Collaboration & Consensus

[PDF]

Don Turnbull

Abstract

The OpenChoice system, currently in development, is an open source, open access community rating and filtering service that would improve upon the utility of currently available Web content filters. The goal of OpenChoice is to encourage community involvement in making filtering classification more accurate and to increase awareness in the current approaches to content filtering. The design challenge for OpenChoice is to find the best interfaces for encouraging easy participation amongst a community of users, be it for voting, rating or discussing Web page content. This work in progress reviews some initial designs while reviewing best practices and designs from popular Web portals and community sites.

Excerpt

…Tim O’Reilly proposed the phrase “architecture of participation” to describe participatory Web sites and applications that encourage user-driven content, open source contribution models and simple access via APIs. So why are so many of these sites and applications under-designed at the interface and interaction level, not to mention having vaguely architected overall structure? Many of these sites are relying on the (initial) enthusiasm of users or their compelling features to keep and encourage participation. However more attractive and functional interfaces with clear labels, (usability) tested interfaces, finely crafted workflows and consistent interaction models would both keep early adopters involved and allow for easy bootstrapping for late-comers. When designing participatory, community-oriented sites, designers shouldn’t have to re-invent everything from scratch.

…popular community sites feature common interface elements and functionality:

  • Overall voting and rank status easy to read
  • Dynamically updated interaction
  • Thumbnail, abstract or actual content of item on same page as voting interface
  • Rating information for community at large for the item
  • Suggestions or lists for additional items to rate
  • Textual description of (proposed) item category with link to category
  • Links to related and relevant discussions about item (or item category)
  • Standard interface objects (where appropriate) to leverage existing Web interaction (e.g. purple & blue links colors, tabbed navigation metaphor, drop-down lists)
  • Show history of ratings or queue of items to vote on
  • Aggregate main page or display element that shows overall community ratings (to encourage virtuous competition for most ratings)
  • Task flow for voting or rating clear with additional interactions not required (e.g. following links)

…In addition to dynamic voting status, there is some consideration of simplifying the voting to include “allow” vs. “block” ratings only. Design issues such as the colors of the buttons may also overly influence certain votes.

Basic Voting Interface and Voting History
As part of each user’s own customized portal page, a history of recent votes is prototyped to give users the ability to remember their past votes and see the status of pending items in consideration.

Keywords

information interfaces: Graphical User Interfaces, user interfaces, reputation systems, social computing

Cite As

Turnbull, D. (2007). Rating, Voting & Ranking: Designing for Collaboration & Consensus. Paper presented at the Association of Computing Machinery Computer Human Interface Conference (SIGCHI), San Jose, CA.

References in this publication

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  • Galway, D. (2008) Real-life Rating Algorithm [PDF].

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Building Web Reputation Systems by Randy Farmer and Bryce Glass at Building Web Reputation Systems: The Blog.

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