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\"When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to learn what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you'll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. You'll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed.\"-- Provided by publisher.

Objective: This study investigates the effectiveness of bibliographic databases to retrieve qualitative studies for use in systematic and rapid reviews in Health Technology Assessment (HTA) research. Qualitative research is becoming more prevalent in reviews and health technology assessment, but standardized search methodologies—particularly regarding database selection—are still in development. Methods: To determine how commonly used databases (MEDLINE, CINAHL, PsycINFO, Scopus, and Web of Science) perform, a comprehensive list of relevant journal titles was compiled using InCites Journal Citation Reports and validated by qualitative researchers at Canada’s Drug Agency (formerly CADTH). This list was used to evaluate the qualitative holdings of each database, by calculating the percentage of total titles held in each database, as well as the number of unique titles per database. Results: While publications on qualitative search methodology generally recommend subject-specific health databases including MEDLINE, CINAHL, and PsycINFO, this study found that multidisciplinary citation indexes Scopus and Web of Science Core Collection not only had the highest percentages of total titles held, but also a higher number of unique titles. Conclusions: These indexes have potential utility in qualitative search strategies, if only for supplementing other database searches with unique records. This potential was investigated via tests on qualitative rapid review search strategies translated to Scopus to determine how the index may contribute relevant literature.

As the number and diversity of distributed Web databases on the Internet exponentially increase, it is difficult for user to know which databases are appropriate to search. Given database language models that describe the content of each database, database selection services can provide assistance in locating databases relevant to the information needs of users. In this paper, we propose a database selection approach based on statistical language modeling. The basic idea behind the approach is that, for databases that are categorized into a topic hierarchy, individual language models are estimated at different search stages, and then the databases are ranked by the similarity to the query according to the estimated language model. Two-stage smoothed language models are presented to circumvent inaccuracy due to word sparseness. Experimental results demonstrate that such a language modeling approach is competitive with current state-of-the-art database selection approaches.

Legal requirements, certification specifications, as well as the demand for real world data on cancer research and treatment led to the decision to establish the University Clinical Cancer Registry Regensburg. The first organizational step in the implementation process of this oncological data registry was the evaluation and acquisition of suitable tumor documentation and database software. For this purpose, an evaluation matrix comprising required database software criteria was designed and consented by a multidisciplinary group of experts. Next, a yearly report of the Institute for Cancer Center Certification (OnkoZert 2019) was considered to identify database software already in use. The identified systems were rated according to the established criteria matrix and other relevant aspects. Onkostar was the system considered most suited for building up an oncological data repository. In the second step, the central IT department implemented Onkostar on-premise and migrated digitally available data after an adaptation and verification process. In parallel, a uniformed process for handling emerging oncological research questions was established. For research requirements, a data analysis concept was established comprising a proposal for data extraction, procedural instructions, and statistical training materials. In the final step, the implemented software and the process for handling research requirements in practice were evaluated by using two exemplary use cases with the focus on clinic-wide analyses and currently relevant scientific topics. A 2-month test phase conducted by various user groups showed a preference for Onkostar tumor documentation software from IT-Choice, mainly because of its adjustability to support research and treatment. Newly added and migrated data can be used for certification and research purposes. This software also provides support in current tumor documentation by displaying the course of cancer disease for individual patients over time. Such oncological data registries can be a powerful tool for legally required cancer registration, the certification of medical centers, as well as for additional oncological research. Tumor databases can be helpful in projects on cancer treatment and scientific aims. The experiences made at the University Hospital Regensburg may be used as a guidance for implementing clinical databases in similar settings with interdisciplinary responsibilities.

It is widely accepted that meta-analysts should search multiple databases. The selection of databases is ideally based on the potential contribution of each database to the project or on the potential for bias if a database is excluded, as supported by research evidence. We explore whether searching Embase yields additional trials that influence a meta-analysis. We identified meta-analyses that searched Medline and Embase. A random-effects weighted mean method was used to estimate the intervention effect in articles indexed only in Embase compared with those indexed elsewhere. On average, Embase-unique trials yielded significantly smaller estimates by 29% (ratio of odds ratio [ROR] 0.71, 95% confidence interval [CI] 0.56–0.90) but influenced the pooled estimate by an average of only 6% (ROR 0.94, 95% CI 0.88–0.99). Searching Medline but not Embase risks biasing a meta-analysis by finding studies that show larger estimates, but their prevalence seems low enough that the risk may be slight, provided the rest of the search is comprehensive.

Article adapted from a chapter of The Online Deskbook: ONLINE Magazine's Essential Desk Reference for Online Internet Searchers. Pemberton Press, 1996. Offers advice on choosing a primary online system for searching. Looks at the services offered by consumer online services, professional and Internet systems in these areas: company background; company financial information; computers; current news; education, humanities, social sciences; health and wellness; industry overviews; intellectual property; people; politics; reference and science and technology.

Knowledge Index (KI), a subset of DIALOG, contains about 100 databases that are accessible during evenings and weekends at an affordable price. An aid to database selection on KI is Menu-Assisted Searching which guides users through a short series of succeeding choices to the file of files most suitable. Details use of this function.

Demonstrates the use of professional searching techniques on Knowledge Index, a subset of Dialog, which contains about 100 databases that are accessible during evenings and weekends at an affordable price. The example given, a search for information about the number of languages and their speakers in the world, led to the answer being found in a volume already on the author's own bookshelf!