Scholarly essay database

This database is designed to show the relationship between academic papers and the papers they reference, covering papers of Japanese academic society journals in the field of natural sciences.

Institutional Repository is an archive system by research institutions, such as universities, in order to collect, accumulate and disclose their products for free. If there are articles on institutional repositories, it can be searched with CiNii articles. This is a digitized database that started in JASI incorporates journal information of articles published in approximately domestic forestry and fisheries-related academic journals. Some articles have links to external. It incorporates approximately 7. Only incorporated data from other databases, links to the article information of Ichushi Web are displayed by using a data provided by Japan Medical Abstracts Society.

The architecture of Utopia Documents, showing the relationship between the GUI top , plugins middle and ontology bottom. The core serves two purposes: i it performs the relatively mundane tasks necessary to generate and manage the interactive Graphical User Interface GUI and to co-ordinate the behavior of the plugins, which are loaded on demand at run-time; ii it carries out the low-level analysis of PDF documents, including reading their file format and converting them into both a visual representation to be displayed on-screen and a hierarchical semantic model for later higher-level analysis and annotation by the plugins.

The analysis performed by the core is generic in nature, and is restricted at this stage to identifying typographical and layout-based features common to scholarly papers from any discipline.

Distinguish between Scholarly and Non-Scholarly Sources?

Once this raw structure has been generated, using various heuristics, the system then identifies higher-level typographical constructs titles, sections, headings, figures, tables, references, etc. Annotations identifying these features are assembled, and added to the raw hierarchy to form a semantic model that is then shared with, and further annotated by, the plugins.

Two broad classes of plugin are defined. Annotator plugins may be configured to execute automatically when a document is loaded, typically performing document-wide tasks, such as identifying terms of biological or chemical interest; alternatively, they may be invoked manually via the GUI—in these cases, the plugins have access to the GUI's state, and can generate context-specific annotations e.

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This form of semantic integration allows the components to cooperate flexibly in the analysis of document content and structure, and allows plugins to be developed independently of one another, with sensible relationships and behavior being inferred at run-time rather than being pre-determined: e. Via its plugins, Utopia Documents has access to a wealth of bioinformatics data.


Each plugin can use whatever client libraries are appropriate to access web-service endpoints both SOAP- and REST-style , as well as other remotely accessible resources, such as relational databases and RDF stores. This both offers a single mechanism via which Utopia Documents can search multiple primary databases, and enforces a consistent naming scheme between sources, allowing results to be interrelated.

Although containing much information that is irrelevant to the life sciences, Wikipedia and thus DBPedia has evolved to represent a significant and mostly authoritative corpus of scientific knowledge—a study performed by the journal Nature concluded that its entries were as accurate or indeed, as error prone as those published in Encylopaedia Britannica Giles, , The combined application of ontologies and RDF in DBPedia allows queries performed by Utopia Documents to traverse only the portions of the DBPedia network that are semantically related to the life sciences.

We welcome any feedback on the software. Utopia Documents was developed in response to the need to achieve tighter coupling between published articles and their underlying data, ultimately to facilitate knowledge discovery. The tool was designed with two classes of user in mind; the reader, as consumer of published material; and the journal editor, as curator.

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To this end, the software was piloted with Portland Press Limited PPL with the goal of rendering the content of BJ electronic publications and supplemental data richer and more accessible. With the customized software in-house, article annotation was fairly swift, individual papers taking 10—30 min, depending on their suitability for mark-up. Entities relating to protein sequences and structures have been, of necessity, the main targets for mark-up, because this was the functionality built into the original Utopia toolkit.

The kinds of additional mark-up provided by the software include links from the text to external web sites, term definitions from ontologies and controlled vocabularies, embedded data and materials images, videos, etc. The tool installs easily on the desktop as an alternative PDF viewer. Once opened, it displays a window consisting of three regions Fig. Below this, thumbnail images give an overview of the document and allow rapid navigation through it.

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The sidebar on the right displays the contents of annotations, providing term definitions and access to auxiliary data as the article is explored. When no specific terms are selected, the sidebar defaults to displaying document-wide metadata [including the title, authors, keywords, abbreviations, etc. Where the PDF version is not available to the reader, clicking on the reference currently launches a Google Scholar search instead.

Similar marks are added to the corner of the corresponding thumbnail in the pager, to indicate that additional information exists somewhere on that page. Mousing-over a glyph highlights the nearby terms, or document regions, that contain annotations; selecting these areas causes the associated data to be displayed—this may involve populating the sidebar with definitions, or may activate an embedded interactive visualization.

Highlighting any word or phrase in the paper 3a initiates a context-sensitive search of the online resources to which Utopia Documents is connected, all results again appearing in the sidebar. Selecting a term invokes the display of all possible definitions, allowing the reader or editor to select for themselves the most appropriate version. The provenance of these definitions is indicated in their headers, as illustrated in Figure 3 : the icon on the left 3c represents the item's origin [e. The current version of Utopia Documents supports three forms of embedded interactive content; as with term definitions, these are indicated by red glyphs in the margins.

Each type of interactive content has its own functionality: 3D molecules Fig. Figure 4 illustrates the simple transformation from static images of tables and figures into semantically annotated, interactive objects. Image sequences showing the transformation of a 2D image left-hand panel and of a static table of figures right-hand panel into interactive objects: i. Utopia Documents provides new ways of reading, of interacting with and ultimately of assimilating the knowledge embodied within research articles.

Locate and Evaluate Scholarly Articles - UMGC Library

The approach taken here departs from many initiatives in scholarly publishing in that the focus for enrichment is the hitherto-largely-neglected static PDF file, rather than HTML- or XML-based files. Utopia Documents is hence an attempt to provide a semantic bridge that connects the benefits of both the static and the dynamic online incarnations of published texts. Inevitably, those who prefer to read articles online in a web browser will view the need to download a new, desktop-based PDF reader as a weakness.

The philosophy embodied in Utopia Documents is to hide as much of the underlying complexity as possible, to avoid requiring users whether editors, authors or readers to change their existing document-reading behaviors, and to present no significant extra hurdles to publication.

Like the initiatives in semantic publishing outlined earlier, the Semantic BJ , powered by Utopia Documents, is a pilot, the success of which will depend on various factors, including whether the barriers to adoption are sufficiently low, and whether the approach is considered to add sufficient value. Although it is too early to assess the impact of the pilot on readers of the Semantic BJ , the take-up of the software by the BJ 's full editorial team, and it use to mark up every issue since the launch, is a testament to the software's ease-of-use.

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  • Of course, as the project with PPL develops, we will gather relevant usage and usability data in order to provide a more meaningful evaluation. Many of the projects discussed in this article have exploited fairly traditional text-mining methods, in conjunction with controlled vocabularies and ontologies, to facilitate the launch of relevant external web pages from marked-up entities in documents. As such, they come with all the limitations in precision of current text-mining tools; this brings a significant overhead to readers in terms of having to identify errors.

    Of course, the difficulty for non-experts in any given field is to be able to recognize when particular annotations really are errors, and failure to identify them as such leads to the danger of error propagation. In light of these issues, we took a slightly different approach to entity mark-up in this first incarnation of Utopia Documents, taking advantage of linked-data initiatives to facilitate mark-up and add value to published texts.

    However, because the functionality of the system is easily customizable via its flexible plugin architecture, any text-mining tool or database that is accessible via web services can be trivially added to the suite. As a demonstration of the potential of this architecture, in collaboration with their developers, three prototype plugins that link Utopia to other systems have been implemented:. Its entity-recognition engine, however, may also be accessed programmatically via a web service, which, given a section of text, identifies objects of biological interest and returns links to the summary pop-ups.

    Integration of Reflect's functionality with Utopia Documents is therefore a comparatively straightforward task: as a user reads a PDF document, its textual content is extracted and sent to the Reflect web service; the resulting entities are then highlighted in the PDF article, and linked to the appropriate pop-up, which is displayed when a highlighted term is selected.

    About the journal Database : The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between … Find out more. Latest articles Extraction of chemical—protein interactions from the literature using neural networks and narrow instance representation.

    RumimiR: a detailed microRNA database focused on ruminant species. Progress in the study of genome size evolution in Asteraceae: analysis of the last update. DeepScreening: a deep learning-based screening web server for accelerating drug discovery.

    101 Free Online Journal and Research Databases for Academics

    A survey of ontology learning techniques and applications. ApicoTFdb: the comprehensive web repository of apicomplexan transcription factors and transcription-associated co-factors. BioCreative-IV virtual issue. Community annotation and bioinformatics workforce development in concert—Little Skate Genome Annotation Workshops and Jamborees. Most cited UniProt Knowledgebase: a hub of integrated protein data.

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