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Nous présentons la méthode que nous avons suivie pour améliorer notre annotation automatique des entités nommées dans l’Encyclopédie de Diderot et d’Alembert. L’outil d’annotation sémantique PERDIDO que nous utilisons a été initialement développé pour l’annotation d’informations géographiques et la reconstruction d’itinéraire. Nous proposons d’y implémenter de nouvelles règles élaborées manuellement à partir d’une étude des cotextes co-occurrentiels des noms propres du corpus accomplie au moyen d’une plateforme automatique d’exploration et de calcul.

A World of Paper: Louis XIV, Colbert de Torcy, and the Rise of the Information State, by John C. Rule and Ben S. Trotter. Montreal & Kingston, McGill-Queen's University Press, [...]

We present a new dataset for the task of toponym resolution in digitized historical newspapers in English. It consists of 343 annotated articles from newspapers based in four different locations in England (Manchester, Ashton-under-Lyne, Poole and Dorchester), published between 1780 and 1870. The articles have been manually annotated with mentions of places, which are linked—whenever possible—to their corresponding entry on Wikipedia. The dataset consists of 3,364 annotated toponyms, of which 2,784 have been provided with a link to Wikipedia. The dataset is published in the British Library shared research repository, and is especially of interest to researchers working on improving semantic access to historical newspaper content. [ABSTRACT FROM AUTHOR]

Although the Ordnance Survey has itself been the subject of historical research, scholars have not systematically used its maps as primary sources of information. This is partly for disciplinary reasons and partly for the technical reason that high-quality maps have not until recently been available digitally, geo-referenced, and in color. A final, and crucial, addition has been the creation of item-level metadata which allows map collections to become corpora which can for the first time be interrogated en masse as source material. By applying new Computer Vision methods leveraging machine learning, we outline a research pipeline for working with thousands (rather than a handful) of maps at once, which enables new forms of historical inquiry based on spatial analysis. Our 'patchwork method' draws on the longstanding desire to adopt an overall or 'complete' view of a territory, and in so doing highlights certain parallels between the situation faced by today's users of digitized maps, and a similar inflexion point faced by their predecessors in the nineteenth century, as the project to map the nation approached a form of completion. [ABSTRACT FROM AUTHOR]

Geographic text analysis (GTA) research in the digital humanities has focused on projects analyzing modern English-language corpora. These projects depend on temporally specific lexicons and gazetteers that enable place name identification and georesolution. Scholars working on the early modern period (1400–1800) lack temporally appropriate geoparsers and gazetteers and have been reliant on general purpose linked open data services like Geonames. These anachronistic resources introduce significant information retrieval and ethical challenges for early modernists. Using the geography entries of the canonical eighteenth-century Encyclopédie, we evaluate rule-based named entity recognition (NER) systems to pinpoint areas where they would benefit from adjustments for processing historical corpora. As we demonstrate, annotating nested and extended place information is one way to improve early modern GTA. Working with Enlightenment sources also motivates a critique of the landscape of digital geospatial data. [ABSTRACT FROM AUTHOR]

Effectively exploring and browsing document collections is a fundamental problem in visualization. Traditionally, document visualization is based on a data model that represents each document as the set of its comprised words, effectively characterizing what the document is. In this paper we take an alternative perspective: motivated by the manner in which users search documents in the research process, we aim to visualize documents via their usage, or how documents tend to be used. We present a new visualization scheme — cite2vec — that allows the user to dynamically explore and browse documents via how other documents use them, information that we capture through citation contexts in a document collection. Starting from a usage-oriented word-document 2D projection, the user can dynamically steer document projections by prescribing semantic concepts, both in the form of phrase/document compositions and document:phrase analogies, enabling the exploration and comparison of documents by their use. The user interactions are enabled by a joint representation of words and documents in a common high-dimensional embedding space where user-specified concepts correspond to linear operations of word and document vectors. Our case studies, centered around a large document corpus of computer vision research papers, highlight the potential for usage-based document visualization. [ABSTRACT FROM PUBLISHER]

Many health care institutions struggle with the dilemma of how to attract and sustain staff nurse participation in committee work. Based on shared decision-making, the Nursing Council at our academic ambulatory oncology center inherently depends upon nursing staff involvement. Several committee chairpersons reporting into the Council expressed concern regarding low attendance and participation among the staff nurses. Data on staff nurses' membership in hospital based committee work showed that approximately 10% were active members of multiple hospital wide committees, while the remaining 90% had minimal to no involvement. To address the problem of low staff nurse involvement on committees, the Council asked the Evidence Based Practice (EBP) Committee to explore two primary questions: What factors motivate nursing staff to become actively involved in committee work? What factors impede participation? The EBP Committee found minimal evidence in published nursing literature to answer these questions. Consequently, the committee decided to obtain (expert opinion) evidence by implementing focus groups interviews with nursing staff who were active members of multiple committees. The EBP Committee developed a series of open-ended questions. Nurses belonging to multiple committees were invited to attend one of two ninety-minute, focus group sessions. Two EBP Committee members facilitated the sessions and a third member took notes. By consensus, the sessions were audio-taped. Synthesis of information from these sources provided detailed information about what factors motivate and impede nursing staff involvement on committees. The project successfully provided answers to the two questions posed to the EBP Committee. Several recommendations were presented to the Nursing Council, including the re-examination of the Council and committee structure. To date, numerous practice changes have occurred and have contributed to increased staff participation. Information gained from focus groups can be an excellent source of evidence when there is little available in the published literature. The description of how we collected new evidence through focus groups will be useful to nurses in a variety of specialties and/or settings. [ABSTRACT FROM AUTHOR]