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The purpose of this paper is to detect whether both file type (a set of rich and web files) and language (English, Spanish, German, French and Italian) influence the web visibility of European universities.

A webometrics analysis of the top 200 European universities (as ranked in the Ranking web of World Universities) was carried out by a manual query for each official URL identified by using the Google search engine (April 2012). A correlation analysis between visibility and file format page count is offered according to language. Finally, a prediction of visibility is shown by using the SMOreg function.

The results indicate that Spanish and English are the languages that correlate most highly with web visibility. This correlation becomes greater – though moderate – when considering only PDF files.

The results are limited due to the low correlation between overall page count and visibility. The lack of an accurate search engine that would assist in link counting procedures makes this process difficult.

An observed increase in correlation – although moderate – while analysing PDF files (in English and Spanish) is considered to be meaningful. This may indirectly confirm that specific file formats and languages generate different web visibility behaviour on European university web sites.

A library serves many functions but one of the most important, perhaps the central function, has been to make a wide variety of knowledge and literature locally available. In the past we have always treated electronic technology as a means to enhance library functions. Today a somewhat different perspective may be emerging in which we may begin to see electronic technology starting to encroach on this central library function.

The purpose of this paper is to review the basic principles of qualitative analysis, and examine the practical application of these principles to analyze student assignments using the ATLAS.ti software.

Student comments from an assignment are prepared for import into ATLAS.ti. The comments are coded, and then analyzed for patterns using ATLAS.ti and its mechanisms for exploring data and data patterns.

ATLAS.ti offers myriad analytic tools that allow the researcher to quantify qualitative information through coding, data query, cross‐tabulation, and networked visualization of project design. By developing both technical expertise with the software, and developing familiarity with qualitative methodology, librarians can wield an effective means to assess and evaluate text‐based data, such as student assignments or surveys.

Because the ATLAS.ti software, and the qualitative analysis process itself is so complex, this article can only outline the most prominent aspects of the tool.

The document can serve as a “jumping‐off” point for other researchers wishing to either explore the qualitative analysis process, particularly as conducted with ATLAS.ti. The reader will become more familiar with the basic concepts of qualitative analysis as reflected in the organization and functions of the ATLAS.ti, as well as the process of preparing and analyzing textual information with ATLAS.ti.

Because there is a general lack of literature on setting up a project with the software, the article is potentially valuable to anyone wishing to expand and improve their evaluative skills using ATLAS.ti or similar tools.

The Open Archives Initiative (OAI) Protocol for Metadata Harvesting presents one promising method by which metadata regarding archives and manuscripts can be shared and made more interoperable with metadata from other sources. Against the background of archival descriptive theory and practice, this article outlines a method for exposing deep, hierarchical metadata from encoded archival description (EAD) files and assesses some theoretical and practical issues that will need to be confronted by institutions choosing to provide or harvest OAI records generated from EAD files. Using OAI on top of existing EAD implementations would allow institutions to repurpose their data and potentially reach more users but would also accelerate the process of reengineering archival access mechanisms. Archivists and technologists using OAI with EAD must pay careful attention to the necessity of preserving archival context and provenance.

This article sets out to explain the purpose of PDF/A, how it addresses archival and records management concerns, how PDF/A was designed to have “desirable properties of a long‐term preservation format”, and the future of PDF/A.

The contents of this article are based on the author's knowledge and experience of the subject.

It is emphasized that PDF/A must be implemented in conjunction with policies and procedures, including quality assurance procedures to ensure acceptable replication of source material.

This article will be of interest to anyone working with PDF files. Work has already begun on PDF/A Part 2 which will be based on PDF 1.6. Application notes and a listing of frequently asked questions will be made publicly available to assist developers of PDF/A applications to better understand the requirements of the file format and provide implementation guidance.

Mobile technology research focuses on supporting the individual mobile worker. CCSW research has primarily focused on supporting distributed, but fixed‐site workers. This research bridges both research foci by expanding to include mobile, anytime, anyplace support. The VLab (Virtual laboratory) provides anytime, anyplace process support for mobile software development teams. A longitudinal evaluation of group interactions in multiple extant teams establishes a baseline that helps to identify process support requirements. This baseline can be used to judge the effect of introducing process support technology that addresses specific context variables in group interactions.

The Greenstone digital library software is an open‐source system for the construction and presentation of information collections. Collections built with Greenstone offer effective full‐text searching and metadata‐based browsing facilities that are attractive and easy to use. Moreover, they are easily maintainable and can be augmented and rebuilt entirely automatically. The system is extensible: software “plugins” accommodate different document and metadata types. Greenstone incorporates an interface that makes it easy for people to create their own library collections. Collections may be built and served locally from the user’s own Web server, or (given appropriate permissions) remotely on a shared digital library host. End users can easily build new collections styled after existing ones from material on the Web or from their local files (or both), and collections can be updated and new ones brought online at any time.

This study aims to explore the link creating behaviour of European highly cited scientists based upon their online lists of publications and their institutional personal websites.

A total of 1,525 highly cited scientists working at European institutions were first identified. Outlinks from their online lists of publications and their personal websites pointing to a pre-defined collection of popular academic websites and file types were then gathered by a personal web crawler.

Perhaps surprisingly, a larger proportion of social scientists provided at least one outlink compared to the other disciplines investigated. By far the most linked-to file type was PDF and the most linked-to type of target website was scholarly databases, especially the Digital Object Identifier website. Health science and life science researchers mainly linked to scholarly databases, while scientists from engineering, hard sciences and social sciences linked to a wider range of target websites. Both book sites and social network sites were rarely linked to, especially the former. Hence, whilst successful researchers frequently use the Web to point to online copies of their articles, there are major disciplinary and other differences in how they do this.

This is the first study to analyse the outlinking patterns of highly cited researchers' institutional web presences in order to identify which web resources they use to provide access to their publications.

Linking libraries and Wikipedia can significantly improve the quality of services provided by these two major silos of knowledge. Such linkage would enrich the quality of Wikipedia articles and at the same time increase the visibility of library resources. To this end, the purpose of this paper is to describe the design and development of a software system for automatic mapping of FAST subject headings, used to index library materials, to their corresponding articles in Wikipedia.

The proposed system works by first detecting all the candidate Wikipedia concepts (articles) occurring in the titles of the books and other library materials which are indexed with a given FAST subject heading. This is then followed by training and deploying a machine learning (ML) algorithm designed to automatically identify those concepts that correspond to the FAST heading. In specific, the ML algorithm used is a binary classifier which classifies the candidate concepts into either “corresponding” or “non-corresponding” categories. The classifier is trained to learn the characteristics of those candidates which have the highest probability of belonging to the “corresponding” category based on a set of 14 positional, statistical, and semantic features.

The authors have assessed the performance of the developed system using standard information retrieval measures of precision, recall, and F-score on a data set containing 170 FAST subject headings manually mapped to their corresponding Wikipedia articles. The evaluation results show that the developed system is capable of achieving F-scores as high as 0.65 and 0.99 in the corresponding and non-corresponding categories, respectively.

The size of the data set used to evaluate the performance of the system is rather small. However, the authors believe that the developed data set is large enough to demonstrate the feasibility and scalability of the proposed approach.

The sheer size of English Wikipedia makes the manual mapping of Wikipedia articles to library subject headings a very labor-intensive and time-consuming task. Therefore, the aim is to reduce the cost of such mapping and integration.

The proposed mapping paves the way for connecting libraries and Wikipedia as two major silos of knowledge, and enables the bi-directional movement of users between the two.

To the best of the authors’ knowledge, the current work is the first attempt at automatic mapping of Wikipedia to a library-controlled vocabulary.

This study is an attempt to develop an automatic identification method for Arabic web queries and divide them into several query types using data mining. In addition, it seeks to evaluate the impact of the academic environment on using the internet.

The web log files were collected from one of the higher institute's servers over a one‐month period. A special program was designed and implemented to extract web search queries from these files and also to automatically classify Arabic queries into three query types (i.e. Navigational, Transactional, and Informational queries) based on predefined specifications for each type.

The results indicate that students are slowly and gradually using the internet for more relevant academic purposes. Tests showed that it is possible to automatically classify Arabic queries based on query terms, with 80.6 per cent to 80.2 per cent accuracy for the two phases of the test respectively. In their future strategies, Jordanian universities should apply methods to encourage university students to use the internet for academic purposes. Web search engines in general and Arabic search engines in particular may benefit from the proposed classification method in order to improve the effectiveness and relevancy of their results in accordance with users' needs.

Studying internet web logs has been the subject of many papers. However, the particular domain, and the specific focuses on this research are what can distinguish it from the others.