96 research outputs found

    To Map or Not to Map: Rethinking Crosswalk Agendas

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    In the two decades since their publication, the Functional Requirements of Bibliographic Records and succeeding standards such as the Library Reference Model have had a marked impact on discourse concerning descriptive theory and practice. The BIBFRAME model, which began as an effort to replace MARC as a linked data-capable modeling format, offers an alternate view of the bibliographic universe with three principal entities rather than four. Differences between BIBFRAME and LRM are based in competing intuitions on the nature of creative works, and at first the two approaches appear to compete for the same intellectual space. BIBFRAME offers us a less constrained model of bibliographic descriptions than the FRBR models, and if interoperability between BIBFRAME and WEMI-aligned standards like Resource Description and Access requires translation of RDA records both to and from BIBFRAME descriptions, then the latter’s flexibility poses problems for mapping between the models. Proposed solutions to those problems reveal as much about different modeling philosophies as they do about different views of creative works and their relationships to texts and copies. Linked data protocols are intended to support resources and scenarios that are far too diverse for either a single account of creative works or for a subsumption-based taxonomy of models. But a need for descriptions flexible enough to include them all does not require us to retreat from modeling commitments to either reductionism or operationalism. BIBFRAME can be seen as reaching for or pointing toward a descriptive domain that supports a complementary role to the IFLA standards

    OCR Quality Affects Perceived Usefulness of Historical Newspaper Clippings. A User Study

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    Publisher Copyright: © 2022 Copyright for this paper by its authors.Effects of Optical Character Recognition (OCR) quality on historical information retrieval have so far been studied in data-oriented scenarios regarding the effectiveness of retrieval results. Such studies have either focused on the effects of artificially degraded OCR quality (see, e.g., [1-2]) or utilized test collections containing texts based on authentic low quality OCR data (see, e.g., [3]). In this paper the effects of OCR quality are studied in a user-oriented information retrieval setting. Thirty-two users evaluated subjectively query results of six topics each (out of 30 topics) based on pre-formulated queries using a simulated work task setting. To the best of our knowledge our simulated work task experiment is the first one showing empirically that users' subjective relevance assessments of retrieved documents are affected by a change in the quality of optically read text. Users of historical newspaper collections have so far commented effects of OCR'ed data quality mainly in impressionistic ways, and controlled user environments for studying effects of OCR quality on users' relevance assessments of the retrieval results have so far been missing. To remedy this The National Library of Finland (NLF) set up an experimental query environment for the contents of one Finnish historical newspaper, Uusi Suometar 1869-1918, to be able to compare users' evaluation of search results of two different OCR qualities for digitized newspaper articles. The query interface was able to present the same underlying document for the user based on two alternatives: either based on the lower OCR quality, or based on the higher OCR quality, and the choice was randomized. The users did not know about quality differences in the article texts they evaluated. The main result of the study is that improved optical character recognition quality affects perceived usefulness of historical newspaper articles significantly. The mean average evaluation score for the improved OCR results was 7.94% higher than the mean average evaluation score of the old OCR results.Peer reviewe

    Supporting Account-based Queries for Archived Instagram Posts

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    Social media has become one of the primary modes of communication in recent times, with popular platforms such as Facebook, Twitter, and Instagram leading the way. Despite its popularity, Instagram has not received as much attention in academic research compared to Facebook and Twitter, and its significant role in contemporary society is often overlooked. Web archives are making efforts to preserve social media content despite the challenges posed by the dynamic nature of these sites. The goal of our research is to facilitate the easy discovery of archived copies, or mementos, of all posts belonging to a specific Instagram account in web archives. We proposed two approaches to support account-based queries for archived Instagram posts. The first approach uses existing technologies in the Internet Archive by using WARC revisit records to incorporate Instagram usernames into the WARC-Target-URI field in the WARC file header. The second approach involves building an external index that maps Instagram user accounts to their posts. The user can query this index to retrieve all post URLs for a particular user, which they can then use to query web archives for each individual post. The implementation of both approaches was demonstrated, and their advantages and disadvantages were discussed. This research will enable web archivists to make informed decisions on which approach to adopt based on practicality and unique requirements for their archives

    Proceedings of the 12th International Conference on Digital Preservation

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    The 12th International Conference on Digital Preservation (iPRES) was held on November 2-6, 2015 in Chapel Hill, North Carolina, USA. There were 327 delegates from 22 countries. The program included 12 long papers, 15 short papers, 33 posters, 3 demos, 6 workshops, 3 tutorials and 5 panels, as well as several interactive sessions and a Digital Preservation Showcase

    Proceedings of the 12th International Conference on Digital Preservation

    Get PDF
    The 12th International Conference on Digital Preservation (iPRES) was held on November 2-6, 2015 in Chapel Hill, North Carolina, USA. There were 327 delegates from 22 countries. The program included 12 long papers, 15 short papers, 33 posters, 3 demos, 6 workshops, 3 tutorials and 5 panels, as well as several interactive sessions and a Digital Preservation Showcase

    BIM semantic-enrichment for built heritage representation

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    In the built heritage context, BIM has shown difficulties in representing and managing the large and complex knowledge related to non-geometrical aspects of the heritage. Within this scope, this paper focuses on a domain-specific semantic-enrichment of BIM methodology, aimed at fulfilling semantic representation requirements of built heritage through Semantic Web technologies. To develop this semantic-enriched BIM approach, this research relies on the integration of a BIM environment with a knowledge base created through information ontologies. The result is knowledge base system - and a prototypal platform - that enhances semantic representation capabilities of BIM application to architectural heritage processes. It solves the issue of knowledge formalization in cultural heritage informative models, favouring a deeper comprehension and interpretation of all the building aspects. Its open structure allows future research to customize, scale and adapt the knowledge base different typologies of artefacts and heritage activities

    Citation Recommendation: Approaches and Datasets

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    Citation recommendation describes the task of recommending citations for a given text. Due to the overload of published scientific works in recent years on the one hand, and the need to cite the most appropriate publications when writing scientific texts on the other hand, citation recommendation has emerged as an important research topic. In recent years, several approaches and evaluation data sets have been presented. However, to the best of our knowledge, no literature survey has been conducted explicitly on citation recommendation. In this article, we give a thorough introduction into automatic citation recommendation research. We then present an overview of the approaches and data sets for citation recommendation and identify differences and commonalities using various dimensions. Last but not least, we shed light on the evaluation methods, and outline general challenges in the evaluation and how to meet them. We restrict ourselves to citation recommendation for scientific publications, as this document type has been studied the most in this area. However, many of the observations and discussions included in this survey are also applicable to other types of text, such as news articles and encyclopedic articles.Comment: to be published in the International Journal on Digital Librarie
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