Folksonomies-cooperative classification and communication through shared metadata, Computer Mediated Communication

Examples are discussed to show the differences among discriminant analysis, logistic regression, and multiple regression. Chapter 6, “Multivariate Analysis of Variance,” presents advantages of multivariate analysis of variance (MANOVA) over univariate analysis of variance (ANOVA), discusses assumptions of MANOVA, and assesses validations of MANOVA assumptions and model estimation. The authors also discuss post hoc tests of MANOVA and multivariate analysis of covariance. Chapter 7, “Conjoint Analysis,” explains what conjoint analysis does and how it is different from other multivariate techniques. Guidelines of selecting attributes, models, and methods of data collection are presented. Chapter 8, “Cluster Analysis,” studies objectives, roles, and limitations of cluster analysis. Two basic concepts: similarity and distance are discussed. The authors also discuss details of five most popular hierarchical algorithms (singlelinkage, complete-linkage, average-linkage, centroid method, Ward’s method) and three nonhierarchical algorithms (the sequential threshold method, the parallel threshold method, and the optimizing procedure). Profiles of clusters and guidelines for cluster validation are studied as well. Chapter 9, “Multidimensional Scaling and Correspondence Analysis,” introduces two interdependence techniques to display the relationships in the data. The book describes clearly and intuitively the differences between the two techniques and how these two techniques are performed. Chapters 10–12 cover topics in SEM. Chapter 10, “Structural Equation Modeling: An Introduction,” introduces SEM and related concepts such as exogenous, endogenous constructs, and so on, points out the differences between SEM and other multivariate techniques, overviews the decision process of SEM. Chapter 11, “Confirmatory Factor Analysis,” explains the differences between exploratory and confirmatory factor analysis, discusses how to construct, validate, and assess the goodness of fit of a measurement model in SEM by confirmatory factor analysis. Chapter 12, “Testing a Structural Model,” presents some methods of SEM in examining the relationships between latent constructs. The book is an excellent book for people in management and marketing. For the Technometrics audience, this book does not have much flavor of physical, chemical, and engineering sciences. For example, partial least squares, a very popular method in Chemometrics, is discussed but not as detailed as other techniques in the book. Furthermore, due to the amount of materials covered in the book, it might be inappropriate for someone who is new to multivariate analysis.

The Grammar of Graphics

Mexico City : México

Katholieke Universiteit Leuven, Belgium Erik DuvalErik.Duval@cs.kuleuven.ac.beStrategic FuturistAutodesk Wayne Hodginswayne.hodgins@autodesk.comAssociate Professor, The Information SchoolUniversity of Washington Stuart Suttonsasutton@u.washington.eduExecutive DirectorDublin Core Metadata Initiative Stuart L. WeibelWeibel@oclc.org

Metadata Principles and Practicalities

The weighted list, known popularly as a `tag cloud', has appeared on many popular folksonomy-based web-sites. Flickr, Delicious, Technorati and many others have all featured a tag cloud at some point in their history. However, it is unclear whether the tag cloud is actually useful as an aid to finding information. We conducted an experiment, giving participants the option of using a tag cloud or a traditional search interface to answer various questions. We found that where the information-seeking task required specific information, participants preferred the search interface. Conversely, where the information-seeking task was more general, participants preferred the tag cloud. While the tag cloud is not without value, it is not sufficient as the sole means of navigation for a folksonomy-based dataset.

The folksonomy tag cloud: when is it useful?

This paper reports on a study that examined the ability of resource authors to create acceptable metadata in an organizational setting. The results indicate that authors can create good quality metadata when working with the Dublin Core, and that is in some cases they may be able to create metadata that is of better quality than what a metadata professional can produce. This research suggests that authors think metadata is valuable for resource discovery, that it should be created for web resources, and that they, as authors, should be involved in metadata production for their works. The study also indicates that a simple web form, with textual guidance and selective use of features (e.g., popup windows, drop-down menus, etc.) can assist authors in generating good quality metadata.

http://dcpapers.dublincore.org/pubs/article/download/647/643

Author-generated Dublin Core Metadata for Web Resources: A Baseline Study in an Organization

This paper describes an ongoing research project that involves the study of teachers' information seeking behaviors, needs and practices in relation to a collection of primary source materials available through the University of North Carolina at Chapel Hill (UNC) Library's digital library Documenting the American South (DocSouth). By gaining an in-depth understanding of the needs and wants of teachers in the context of their work, we hope to build a collection of learning objects and a domain ontology applied to the collection to improve teachers' access to the cultural heritage materials and to facilitate their actual use in the classroom.

Teachers' perspectives and contextual dimensions to guide the design of N.C. history learning objects and ontology

Many early web-based digital libraries (DLs) had implicit assumptions reflected in their architecture that the unit of focus in the DL (frequently "reports" or "e-prints") would only be manifested in a single, or at most a few, common file formats such as PDF or PostScript. DLs have now matured to the point where their contents are commonly no longer simple files. Complex objects in DLs have emerged from in response to various requirements, including: simple aggregation of formats and supporting files, bundling additional information to aid digital preservation, creating opaque digital objects for e-commerce applications, and the incorporation of dynamic services with the traditional data files. We examine a representative (but not necessarily exhaustive) number of current and recent historical web-based complex object technologies and projects that are applicable to DLs: Aurora, Buckets, ComMentor, Cryptolopes, Digibox, Document Management Alliance, FEDORA, Kahn-Wilensky Framework Digital Objects, Metadata Encoding & Transmission Standard, Multivalent Documents, Open eBooks, VERS Encapsulated Objects, and the Warwick Framework.

/pdf/a-survey-of-complex-object-technologies-for-digital-5ax3nij6yh.pdf

A Survey of Complex Object Technologies for Digital Libraries

One of the problems that people have in using statistical information from government websites, is that the level of statistical knowledge in the general population is low. People’s lack of statistical knowledge is a barrier to finding the statistics they need and understanding what the statistics mean and how to use them. We describe the Statisticaf Interactive Glossary (SIG), an enhanced glossary of statistical terms, and the GovStat ontology of statistical concepts which supports it. The overall goal of the glossary is to help users understand important statistical terms and concepts in the context in which they are used. We present a conceptual framework whose components articulate the different aspects of a term’s basic explanation that can be manipulated to produce a variety of presentations. Developing the general explanation for each term involves three types of information: the content of the explanation, the context in which the explanation will be displayed, and the format in which the explanation will be delivered. Taxonomic relationships between concepts in the GovStat ontology support the provision of context-specific presentations. These same relationships are also associated with explanation templates, which are patterns for defining or giving an example of a concept. We conclude by discussing evaluation of the SIG. The overarching criterion of effectiveness is whether the SIG helps users Complete their statistical information tasks.

https://cpattuelli.files.wordpress.com/2010/04/haas-et-al.pdf

Understanding statistical concepts and terms in context: The GovStat ontology and the statistical interactive glossary

https://cdr.lib.unc.edu/downloads/sj1392699

Maria Cristina Pattuelli

Papers

Author-generated Dublin Core Metadata for Web Resources: A Baseline Study in an Organization

Teachers' perspectives and contextual dimensions to guide the design of N.C. history learning objects and ontology

A Survey of Complex Object Technologies for Digital Libraries

Understanding statistical concepts and terms in context: The GovStat ontology and the statistical interactive glossary

A user-centered approach to the development of a history domain ontology : helping teachers use digital primary sources