1,720,961 research outputs found
Imago Tusciae: A digital archive of historical maps of Tuscany (Italy)
No full textIl progetto Imago Tusciae, realizzato presso il Laboratorio di Geografia del Dipartimento di Storia dell'Università di Siena (gruppo di lavoro: Cinzia Bartoli, Luca Deravignone, Barbara Gelli, Claudio Greppi, Giuseppe Lauricella, Fortunato Lepore, Giancarlo Macchi Janica, Giulio Tarchi), è un archivio digitale on line della cartografia storica della Toscana. Al momento, l’archivio comprende circa 2000 documenti appartenenti a diversi fondi dell’Archivio di Stato di Siena, ai quali si aggiungeranno presto le mappe dell'Archivio di Stato di Grosseto. L'obiettivo è quello di accogliere progressivamente nell’archivio la documentazione cartografica delle diverse conservatorie della Toscana (archivi e biblioteche pubblici e privati), oltre a quella relativa alla Toscana ma conservata altrove (in Italia e all’estero). Oltre che presentarsi come mezzo di consultazione dei dati e di ricerca di informazioni, l’applicazione permette la visualizzazione delle riproduzioni delle mappe e di altri documenti correlati ad alta risoluzione ed offre strumenti di studio e di riflessione: schede informative sui documenti, elenchi di autori con relative notizie biografiche, riferimenti bibliografici, elenchi di fondi archivistici e atlanti di mappe con loro descrizione e una cronologia interattiva e localizzata sulla mappa della Toscana odierna.
Sfruttando le tecniche caratteristiche di Web 2.0 (grazie alla navigazione tabbed) e utilizzando un’architettura di interfaccia lineare e intuitiva, l’applicazione cerca di offrire all’utente una user experience il più possibile simile a quella che si vive sul tavolo di uno studioso in archivio con documenti di provenienza diversa e spunti suscitati dal vaglio incrociato delle fonti.The Imago Tusciae project, developed at the Geography Workshop of the Department of History at the University of Siena (working group: Cinzia Bartoli, Luca Deravignone, Barbara Gelli, Claudio Greppi, Giuseppe Lauricella, Fortunato Lepore, Giancarlo Macchi Janica and Giulio Tarchi), is an online digital archive of the historic cartography of Tuscany. At present the archive comprises around 2,000 documents belonging to different fonds of the Siena State Archives, soon to be joined by the maps from the Grosseto State Archives. The objective is that of progressively gathering within the archive the cartographic documentation from the various registries in Tuscany (archives and both public and private libraries) as well as that concerning Tuscany but conserved elsewhere (in Italy and abroad).
In addition to operating as a means for consulting the data and seeking information, the application also makes it possible to view the maps and other related documents in high resolution and offers a range of tools for study and reflection: informative factsheets on the documents, lists of authors with respective biographical details, bibliographic references, lists of archive fonds and atlases of maps complete with descriptions and an interactive chronology localised on the map of modern-day Tuscany. By exploiting the technical features of Web 2.0 (through tabbed browsing) and using a linear and intuitive interface architecture, the application seeks to offer a user experience as similar as possible to that of a scholar at a desk in an archive, with documents of diverse provenance and suggestions generated by the cross-referenced examination of the sources
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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