Search (6 results, page 1 of 1)

0.022568969 = product of:
  0.067706905 = sum of:
    0.067706905 = sum of:
      0.037864767 = weight(_text_:digital in 1347) [ClassicSimilarity], result of:
        0.037864767 = score(doc=1347,freq=2.0), product of:
          0.14480425 = queryWeight, product of:
            3.944552 = idf(docFreq=2326, maxDocs=44218)
            0.03670994 = queryNorm
          0.26148933 = fieldWeight in 1347, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.944552 = idf(docFreq=2326, maxDocs=44218)
            0.046875 = fieldNorm(doc=1347)
      0.029842136 = weight(_text_:22 in 1347) [ClassicSimilarity], result of:
        0.029842136 = score(doc=1347,freq=2.0), product of:
          0.12855195 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.03670994 = queryNorm
          0.23214069 = fieldWeight in 1347, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=1347)
  0.33333334 = coord(1/3)

Abstract

Terminology registries (TRs) are a crucial element of the infrastructure required for resource discovery services, digital libraries, Linked Data, and semantic interoperability generally. They can make the content of knowledge organization systems (KOS) available both for human and machine access. The paper describes the attributes and functionality for a TR, based on a review of published literature, existing TRs, and a survey of experts. A domain model based on user tasks is constructed and a set of core metadata elements for use in TRs is proposed. Ideally, the TR should allow searching as well as browsing for a KOS, matching a user's search while also providing information about existing terminology services, accessible to both humans and machines. The issues surrounding metadata for KOS are also discussed, together with the rationale for different aspects and the importance of a core set of KOS metadata for future machine-based access; a possible core set of metadata elements is proposed. This is dealt with in terms of practical experience and in relation to the Dublin Core Application Profile.

Date

22. 8.2014 17:12:54

0.011759471 = product of:
  0.035278413 = sum of:
    0.035278413 = product of:
      0.07055683 = sum of:
        0.07055683 = weight(_text_:digital in 463) [ClassicSimilarity], result of:
          0.07055683 = score(doc=463,freq=10.0), product of:
            0.14480425 = queryWeight, product of:
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.03670994 = queryNorm
            0.4872566 = fieldWeight in 463, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.0390625 = fieldNorm(doc=463)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

The interdisciplinary field known as digital humanities (DH) is represented in various forms in the teaching and research practiced in iSchools. Building on the work of an iSchools organization committee charged with exploring digital humanities curricula, we present findings from a series of related studies exploring aspects of DH teaching, education, and research in iSchools, often in collaboration with other units and disciplines. Through a survey of iSchool programs and an online DH course registry, we investigate the various education models for DH training found in iSchools, followed by a detailed look at DH courses and curricula, explored through analysis of course syllabi and course descriptions. We take a brief look at collaborative disciplines with which iSchools cooperate on DH research projects or in offering DH education. Next, we explore DH careers through an analysis of relevant job advertisements. Finally, we offer some observations about the management and administrative challenges and opportunities related to offering a new iSchool DH program. Our results provide a snapshot of the current state of digital humanities in iSchools which may usefully inform the design and evolution of new DH programs, degrees, and related initiatives.

Series

JASIST special issue on digital humanities (DH): A. Landscapes of DH

0.009108848 = product of:
  0.027326543 = sum of:
    0.027326543 = product of:
      0.054653086 = sum of:
        0.054653086 = weight(_text_:digital in 5982) [ClassicSimilarity], result of:
          0.054653086 = score(doc=5982,freq=6.0), product of:
            0.14480425 = queryWeight, product of:
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.03670994 = queryNorm
            0.37742734 = fieldWeight in 5982, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5982)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

As the humanities develop in the realm of increasingly more pronounced digital scholarship, it is important to provide quality subject access to a vast range of heterogeneous information objects in digital services. The study aims to paint a representative picture of the current state of affairs of the use of subject index terms in humanities journal articles with particular reference to the well-established subject access needs of humanities researchers, with the purpose of identifying which improvements are needed in this context. Design/methodology/approach The comparison of subject metadata on a sample of 649 peer-reviewed journal articles from across the humanities is conducted in a university repository, against Scopus, the former reflecting local and national policies and the latter being the most comprehensive international abstract and citation database of research output. Findings The study shows that established bibliographic objectives to ensure subject access for humanities journal articles are not supported in either the world's largest commercial abstract and citation database Scopus or the local repository of a public university in Sweden. The indexing policies in the two services do not seem to address the needs of humanities scholars for highly granular subject index terms with appropriate facets; no controlled vocabularies for any humanities discipline are used whatsoever. Originality/value In all, not much has changed since 1990s when indexing for the humanities was shown to lag behind the sciences. The community of researchers and information professionals, today working together on digital humanities projects, as well as interdisciplinary research teams, should demand that their subject access needs be fulfilled, especially in commercial services like Scopus and discovery services.

0.007362594 = product of:
  0.02208778 = sum of:
    0.02208778 = product of:
      0.04417556 = sum of:
        0.04417556 = weight(_text_:digital in 2294) [ClassicSimilarity], result of:
          0.04417556 = score(doc=2294,freq=2.0), product of:
            0.14480425 = queryWeight, product of:
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.03670994 = queryNorm
            0.30507088 = fieldWeight in 2294, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2294)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Purpose: Investigate the combination of controlled and folksonomy approaches to support resource discovery in repositories and digital collections. Aim: Investigate whether use of an established controlled vocabulary can help improve social tagging for better resource discovery. Objectives: (1) Investigate indexing aspects when using only social tagging versus when using social tagging with suggestions from a controlled vocabulary; (2) Investigate above in two different contexts: tagging by readers and tagging by authors; (3) Investigate influence of only social tagging versus social tagging with a controlled vocabulary on retrieval. - Vgl.: http://www.ukoln.ac.uk/projects/enhanced-tagging/.

0.0063107945 = product of:
  0.018932384 = sum of:
    0.018932384 = product of:
      0.037864767 = sum of:
        0.037864767 = weight(_text_:digital in 1461) [ClassicSimilarity], result of:
          0.037864767 = score(doc=1461,freq=2.0), product of:
            0.14480425 = queryWeight, product of:
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.03670994 = queryNorm
            0.26148933 = fieldWeight in 1461, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.046875 = fieldNorm(doc=1461)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Automated subject classification has been a challenging research issue for many years now, receiving particular attention in the past decade due to rapid increase of digital documents. The most frequent approach to automated classification is machine learning. It, however, requires training documents and performs well on new documents only if these are similar enough to the former. We explore a string-matching algorithm based on a controlled vocabulary, which does not require training documents - instead it reuses the intellectual work put into creating the controlled vocabulary. Terms from the Engineering Information thesaurus and classification scheme were matched against title and abstract of engineering papers from the Compendex database. Simple string-matching was enhanced by several methods such as term weighting schemes and cut-offs, exclusion of certain terms, and en- richment of the controlled vocabulary with automatically extracted terms. The best results are 76% recall when the controlled vocabulary is enriched with new terms, and 79% precision when certain terms are excluded. Precision of individual classes is up to 98%. These results are comparable to state-of-the-art machine-learning algorithms.

0.005258995 = product of:
  0.015776984 = sum of:
    0.015776984 = product of:
      0.03155397 = sum of:
        0.03155397 = weight(_text_:digital in 4171) [ClassicSimilarity], result of:
          0.03155397 = score(doc=4171,freq=2.0), product of:
            0.14480425 = queryWeight, product of:
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.03670994 = queryNorm
            0.21790776 = fieldWeight in 4171, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.944552 = idf(docFreq=2326, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4171)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Purpose - Traditional subject indexing and classification are considered infeasible in many digital collections. This paper seeks to investigate ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance. Design/methodology/approach - Enhanced tagging interfaces were developed for exemplar online repositories, and trials were undertaken with author and reader groups to evaluate the effectiveness of tagging augmented with control vocabulary for subject indexing of papers in online repositories. Findings - The results showed that using a knowledge organisation system to augment tagging does appear to increase the effectiveness of non-specialist users (that is, without information science training) in subject indexing. Research limitations/implications - While limited by the size and scope of the trials undertaken, these results do point to the usefulness of a mixed approach in supporting the subject indexing of online resources. Originality/value - The value of this work is as a guide to future developments in the practical support for resource indexing in online repositories.