The scientific information ecosystem: structure and aggregation levels

The structure and characteristics of the main products for accessing scientific information are described. The different types of content, the technology used (assignment and harvesting of metadata, full text indexing, or federated search) and their results are analysed. The products are: bibliographic databases, academic journals portals, repositories, academic search engines, academic metasearch engines, and library metasearch engines

Undergraduate Full Text Databases: \u3ci\u3eBell and Howell Medical Complete\u3c/i\u3e and \u3ci\u3eInfoTrac Health Reference Center-Academic\u3c/i\u3e

This study compares and contrasts InfoTrac and ProQuest primarily as full-text resources to supplement retrieval of references contained in the CINAHL database. These databases are analyzed by examining their scope in terms of the number and types of serials covered within specific areas using Ulrich\u27s subject headings. Another important aspect of this study relates to the effectiveness of the two search engines for end-user retrieval and collection development

Hospital Preparedness for the Covid-19 Crisis; an Overview

Aim: The situation, structure, and facilities of hospitals change in a crisis, which negatively affects the provision of care quality of health services. One of the current world crises is the Covid-19 pandemic. This study aimed to investigate the preparedness of hospitals to deal with the Covid-19 crisis. Materials and Methods: This narrative review searched the SID, PubMed, Scopus, Google Scholar databases/search engines in published articles between 2019-2022. A search strategy was defined for PubMed and it was translated into other selected databases. Also, the reference list of the included articles was searched. The databases/search engines were searched by two authors independently, and any disagreement was resolved through discussions. To find related articles, Iranian and International databases were searched using Persian keywords and their English equivalents (Covid-19, Hospital, Preparedness, epidemic, and Pandemic). Results: A total of 311 articles were found, of which 15 were reviewed. Inclusion criteria included being an original paper, in Persian or English, and compliance with the purpose of the study. The exclusion criteria included not having access to the full text of the article. The study showed that hospital preparedness against the Covid-19 pandemic in most countries and different regions in Iran is not optimal. Hospitals should be prepared in terms of personal protective equipment, staffing, and beds. Rapid response management and hospital equipment should be strengthened

Searching dynamic Web pages with semi-structured contents

At present, information systems (IS) in higher education are usually supported by databases (DB) and accessed through a Web interface. So happens with SiFEUP, the IS of the Engineering Faculty of the University of Porto (FEUP). The typical SiFEUP user sees the system as a collection of Web pages and is not aware of the fact that most of them do not exist in the sense of being an actual HTML file stored in a server but corresponds to HTML code generated on the fly by a designated program that accesses the DB and brings the most up-to-date information to the user desktop. Typical search engines do not index dynamically generated Web pages or just do that for those that are specifically mentioned in a static page and do not follow on the links the dynamic page may contain. In this paper we describe the development of a search facility for SiFEUP, how the limitations put to indexing dynamic Web pages were circumvented, and an evaluation of the results obtained. The solution involves using a locally developed crawler, the Oracle Text full text indexer, plus meta-information automatically drawn from the DB or manually added to improve the relevance factor calculation.At present, information systems (IS) in higher education are usually supported by databases (DB) and accessed through a Web interface. So happens with SiFEUP, the IS of the Engineering Faculty of the University of Porto (FEUP). The typical SiFEUP user sees the system as a collection of Web pages and is not aware of the fact that most of them do not exist in the sense of being an actual HTML file stored in a server but corresponds to HTML code generated on the fly by a designated program that accesses the DB and brings the most up-to-date information to the user desktop. Typical search engines do not index dynamically generated Web pages or just do that for those that are specifically mentioned in a static page and do not follow on the links the dynamic page may contain. In this paper we describe the development of a search facility for SiFEUP, how the limitations put to indexing dynamic Web pages were circumvented, and an evaluation of the results obtained. The solution involves using a locally developed crawler, the Oracle Text full text indexer, plus meta-information automatically drawn from the DB or manually added to improve the relevance factor calculation

Exploring the academic invisible web

Purpose: To provide a critical review of Bergman's 2001 study on the Deep Web. In addition, we bring a new concept into the discussion, the Academic Invisible Web (AIW). We define the Academic Invisible Web as consisting of all databases and collections relevant to academia but not searchable by the general-purpose internet search engines. Indexing this part of the Invisible Web is central to scientific search engines. We provide an overview of approaches followed thus far. Design/methodology/approach: Discussion of measures and calculations, estimation based on informetric laws. Literature review on approaches for uncovering information from the Invisible Web. Findings: Bergman's size estimate of the Invisible Web is highly questionable. We demonstrate some major errors in the conceptual design of the Bergman paper. A new (raw) size estimate is given. Research limitations/implications: The precision of our estimate is limited due to a small sample size and lack of reliable data. Practical implications: We can show that no single library alone will be able to index the Academic Invisible Web. We suggest collaboration to accomplish this task. Originality/value: Provides library managers and those interested in developing academic search engines with data on the size and attributes of the Academic Invisible Web.Comment: 13 pages, 3 figure

HELIN Federated Search Task Force Final Report

Final report of the HELIN Federated Search Task Force, a group appointed by the HELIN Reference Committee at the request of the HELIN Directors to investigate and report on available federated search engines, which allow users simultaneously to search multiple databases. The task force was not asked to recommend a specific one for licensing by HELIN member libraries and did not do so

Using Search Engine Technology to Improve Library Catalogs

This chapter outlines how search engine technology can be used in online public access library catalogs (OPACs) to help improve users’ experiences, to identify users’ intentions, and to indicate how it can be applied in the library context, along with how sophisticated ranking criteria can be applied to the online library catalog. A review of the literature and current OPAC developments form the basis of recommendations on how to improve OPACs. Findings were that the major shortcomings of current OPACs are that they are not sufficiently user-centered and that their results presentations lack sophistication. Further, these shortcomings are not addressed in current 2.0 developments. It is argued that OPAC development should be made search-centered before additional features are applied. While the recommendations on ranking functionality and the use of user intentions are only conceptual and not yet applied to a library catalogue, practitioners will find recommendations for developing better OPACs in this chapter. In short, readers will find a systematic view on how the search engines’ strengths can be applied to improving libraries’ online catalogs

Searching a database based web site

Currently, information systems are usually supported by databases (DB) and accessed through a Web interface. Pages in such Web sites are not drawn from HTML files but are generated on the fly upon request. Indexing and searching such dynamic pages raises several extra difficulties not solved by most search engines, which were designed for static contents. In this paper we describe the development of a search engine that overcomes most of the problems for a specific Web site, how the limitations put to indexing dynamic Web pages were circumvented, and an evaluation of the results obtained. The solution involves using a locally developed crawler, the Oracle Text full text indexer, and meta-information automatically drawn from the DB or manually added to improve the relevance factor calculation. It has the advantage of uniformly covering the dynamic pages and the static Web pages of the site.Currently, information systems are usually supported by databases (DB) and accessed through a Web interface. Pages in such Web sites are not drawn from HTML files but are generated on the fly upon request. Indexing and searching such dynamic pages raises several extra difficulties not solved by most search engines, which were designed for static contents. In this paper we describe the development of a search engine that overcomes most of the problems for a specific Web site, how the limitations put to indexing dynamic Web pages were circumvented, and an evaluation of the results obtained. The solution involves using a locally developed crawler, the Oracle Text full text indexer, and meta-information automatically drawn from the DB or manually added to improve the relevance factor calculation. It has the advantage of uniformly covering the dynamic pages and the static Web pages of the site

Making the case: an academic guide to research

This guide gives advice on the best ways to find and select the most useful, reliable and relevant information to support and argument in your essay