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Journal Cover International Journal on Digital Libraries     [SJR: 0.649]   [H-I: 22]
   [623 followers]  Follow    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1432-1300 - ISSN (Online) 1432-5012
   Published by Springer-Verlag Homepage  [2210 journals]
  • The impact of JavaScript on archivability
    • Abstract: As web technologies evolve, web archivists work to adapt so that digital history is preserved. Recent advances in web technologies have introduced client-side executed scripts (Ajax) that, for example, load data without a change in top level Universal Resource Identifier (URI) or require user interaction (e.g., content loading via Ajax when the page has scrolled). These advances have made automating methods for capturing web pages more difficult. In an effort to understand why mementos (archived versions of live resources) in today’s archives vary in completeness and sometimes pull content from the live web, we present a study of web resources and archival tools. We used a collection of URIs shared over Twitter and a collection of URIs curated by Archive-It in our investigation. We created local archived versions of the URIs from the Twitter and Archive-It sets using WebCite, wget, and the Heritrix crawler. We found that only 4.2 % of the Twitter collection is perfectly archived by all of these tools, while 34.2 % of the Archive-It collection is perfectly archived. After studying the quality of these mementos, we identified the practice of loading resources via JavaScript (Ajax) as the source of archival difficulty. Further, we show that resources are increasing their use of JavaScript to load embedded resources. By 2012, over half (54.5 %) of pages use JavaScript to load embedded resources. The number of embedded resources loaded via JavaScript has increased by 12.0 % from 2005 to 2012. We also show that JavaScript is responsible for 33.2 % more missing resources in 2012 than in 2005. This shows that JavaScript is responsible for an increasing proportion of the embedded resources unsuccessfully loaded by mementos. JavaScript is also responsible for 52.7 % of all missing embedded resources in our study.
      PubDate: 2015-01-25
    • Abstract: In this article, we present PREMIS OWL. This is a semantic formalisation of the PREMIS 2.2 data dictionary of the Library of Congress. PREMIS 2.2 are metadata implementation guidelines for digitally archiving information for the long term. Nowadays, the need for digital preservation is growing. A lot of the digital information produced merely a decade ago is in danger of getting lost as technologies are changing and getting obsolete. This also threatens a lot of information from heritage institutions. PREMIS OWL is a semantic long-term preservation schema. Preservation metadata are actually a mixture of provenance information, technical information on the digital objects to be preserved and rights information. PREMIS OWL is an OWL schema that can be used as data model supporting digital archives. It can be used for dissemination of the preservation metadata as Linked Open Data on the Web and, at the same time, for supporting semantic web technologies in the preservation processes. The model incorporates 24 preservation vocabularies, published by the LOC as SKOS vocabularies. Via these vocabularies, PREMIS descriptions from different institutions become highly interoperable. The schema is approved and now managed by the Library of Congress. The PREMIS OWL schema is published at
      PubDate: 2015-01-11
  • Named entity evolution recognition on the Blogosphere
    • Abstract: Advancements in technology and culture lead to changes in our language. These changes create a gap between the language known by users and the language stored in digital archives. It affects user’s possibility to firstly find content and secondly interpret that content. In a previous work, we introduced our approach for named entity evolution recognition (NEER) in newspaper collections. Lately, increasing efforts in Web preservation have led to increased availability of Web archives covering longer time spans. However, language on the Web is more dynamic than in traditional media and many of the basic assumptions from the newspaper domain do not hold for Web data. In this paper we discuss the limitations of existing methodology for NEER. We approach these by adapting an existing NEER method to work on noisy data like the Web and the Blogosphere in particular. We develop novel filters that reduce the noise and make use of Semantic Web resources to obtain more information about terms. Our evaluation shows the potentials of the proposed approach.
      PubDate: 2014-12-23
  • VisInfo: a digital library system for time series research data based on
           exploratory search—a user-centered design approach
    • Abstract: To this day, data-driven science is a widely accepted concept in the digital library (DL) context (Hey et al. in The fourth paradigm: data-intensive scientific discovery. Microsoft Research, 2009). In the same way, domain knowledge from information visualization, visual analytics, and exploratory search has found its way into the DL workflow. This trend is expected to continue, considering future DL challenges such as content-based access to new document types, visual search, and exploration for information landscapes, or big data in general. To cope with these challenges, DL actors need to collaborate with external specialists from different domains to complement each other and succeed in given tasks such as making research data publicly available. Through these interdisciplinary approaches, the DL ecosystem may contribute to applications focused on data-driven science and digital scholarship. In this work, we present VisInfo (2014) , a web-based digital library system (DLS) with the goal to provide visual access to time series research data. Based on an exploratory search (ES) concept (White and Roth in Synth Lect Inf Concepts Retr Serv 1(1):1–98, 2009), VisInfo at first provides a content-based overview visualization of large amounts of time series research data. Further, the system enables the user to define visual queries by example or by sketch. Finally, VisInfo presents visual-interactive capability for the exploration of search results. The development process of VisInfo was based on the user-centered design principle. Experts from computer science, a scientific digital library, usability engineering, and scientists from the earth, and environmental sciences were involved in an interdisciplinary approach. We report on comprehensive user studies in the requirement analysis phase based on paper prototyping, user interviews, screen casts, and user questionnaires. Heuristic evaluations and two usability testing rounds were applied during the system implementation and the deployment phase and certify measurable improvements for our DLS. Based on the lessons learned in VisInfo, we suggest a generalized project workflow that may be applied in related, prospective approaches.
      PubDate: 2014-12-03
  • A pipeline for digital restoration of deteriorating photographic negatives
    • Abstract: Extending work presented at the second International Workshop on Historical Document Imaging and Processing, we demonstrate a digitization pipeline to capture and restore negatives in low-dynamic range file formats. The majority of early photographs were captured on acetate-based film. However, it has been determined that these negatives will deteriorate beyond repair even with proper conservation and no suitable restoration method is available without physically altering each negative. In this paper, we present an automatic method to remove various non-linear illumination distortions caused by deteriorating photographic support material. First, using a high-dynamic range structured-light scanning method, a 2D Gaussian model for light transmission is estimated for each pixel of the negative image. Estimated amplitude at each pixel provides an accurate model of light transmission, but also includes regions of lower transmission caused by damaged areas. Principal component analysis is then used to estimate the photometric error and effectively restore the original illumination information of the negative. A novel tone mapping approach is then used to produce the final restored image. Using both the shift in the Gaussian light stripes between pixels and their variations in standard deviation, a 3D surface estimate is calculated. Experiments of real historical negatives show promising results for widespread implementation in memory institutions.
      PubDate: 2014-11-08
  • Assisting digital interoperability and preservation through advanced
           dependency reasoning
    • Abstract: Digital material has to be preserved not only against loss or corruption, but also against changes in its ecosystem. A quite general view of the digital preservation problem is to approach it from a dependency management point of view. In this paper, we present a rule-based approach for dependency management which can model also converters and emulators. We show that this modeling approach enables the automatic reasoning needed for reducing the human effort required for checking (and monitoring) whether a task on a digital object is performable. We provide examples demonstrating how real-world converters and emulators can be modeled, and show how the preservation services can be implemented. Subsequently, we detail an implementation based on semantic web technologies, describe the prototype system Epimenides which demonstrates the feasibility of the approach, and finally report various promising evaluation results.
      PubDate: 2014-10-29
  • Towards robust tags for scientific publications from natural language
           processing tools and Wikipedia
    • Abstract: In this work, two simple methods of tagging scientific publications with labels reflecting their content are presented and compared. As a first source of labels, Wikipedia is employed. A second label set is constructed from the noun phrases occurring in the analyzed corpus. The corpus itself consists of abstracts from 0.7 million scientific documents deposited in the ArXiv preprint collection. We present a comparison of both approaches, which shows that discussed methods are to a large extent complementary. Moreover, the results give interesting insights into the completeness of Wikipedia knowledge in various scientific domains. As a next step, we examine the statistical properties of the obtained tags. It turns out that both methods show qualitatively similar rank–frequency dependence, which is best approximated by the stretched exponential curve. The distribution of the number of distinct tags per document follows also the same distribution for both methods and is well described by the negative binomial distribution. The developed tags are meant for use as features in various text mining tasks. Therefore, as a final step we show the preliminary results on their application to topic modeling.
      PubDate: 2014-10-28
  • A locality-aware similar information searching scheme
    • Abstract: In a database, a similar information search means finding data records which contain the majority of search keywords. Due to the rapid accumulation of information nowadays, the size of databases has increased dramatically. An efficient information searching scheme can speed up information searching and retrieve all relevant records. This paper proposes a Hilbert curve-based similarity searching scheme (HCS). HCS considers a database to be a multidimensional space and each data record to be a point in the multidimensional space. By using a Hilbert space filling curve, each point is projected from a high-dimensional space to a low-dimensional space, so that the points close to each other in the high-dimensional space are gathered together in the low-dimensional space. Because the database is divided into many clusters of close points, a query is mapped to a certain cluster instead of searching the entire database. Experimental results prove that HCS dramatically reduces the search time latency and exhibits high effectiveness in retrieving similar information.
      PubDate: 2014-10-12
  • Exploring publication metadata graphs with the LODmilla browser and editor
    • Abstract: With the LODmilla browser, we try to support linked data exploration in a generic way learning from the 20 years of web browser evolution as well as from scholars’ opinions who try to use it as a research exploration tool. In this paper, generic functions for linked open data (LOD) browsing are presented, and it is also explained what kind of information search tactics they enable with linked data describing publications. Furthermore, LODmilla also supports the sharing of graph views and the correction of LOD data during browsing.
      PubDate: 2014-10-12
  • Linked data authority records for Irish place names
    • Abstract: Linked Data technologies are increasingly being implemented to enhance cataloguing workflows in libraries, archives and museums. We review current best practice in library cataloguing, how Linked Data is used to link collections and provide consistency in indexing, and briefly describe the relationship between Linked Data, library data models and descriptive standards. As an example we look at the dataset, an online database holding the authoritative hierarchical list of Irish and English language place names in Ireland. This paper describes the process of creating the new Linked Logainm dataset, including the transformation of the data from XML to RDF and the generation of links to external geographic datasets like DBpedia and the Faceted Application of Subject Terminology. This dataset was then used to enhance the National Library of Ireland’s metadata MARCXML metadata records for its Longfield maps collection. We also describe the potential benefits of Linked Data for libraries, focusing on the use of the Linked Logainm dataset and its future potential for Irish heritage institutions.
      PubDate: 2014-10-10
  • Digital field scholarship and the liberal arts: results from a
           2012–13 sandbox
    • Abstract: We summarize a recent multi-institutional collaboration in digital field scholarship involving four liberal arts colleges: Davidson College, Lewis & Clark College, Muhlenberg College, and Reed College. Digital field scholarship (DFS) can be defined as scholarship in the arts and sciences for which field-based research and concepts are significant, and digital tools support data collection, analysis, and communication; DFS thus gathers together and extends a wide range of existing scholarship, offering new possibilities for appreciating the connections that define liberal education. Our collaboration occurred as a sandbox, a collective online experiment using a modified WordPress platform (including mapping and other advanced capabilities) built and supported by Lewis & Clark College, with sponsorship provided by the National Institute for Technology in Liberal Education. Institutions selected course-based DFS projects for fall 2012 and/or spring 2013. Projects ranged from documentary photojournalism to home energy efficiency assessment. One key feature was the use of readily available mobile devices and apps for field-based reconnaissance and data collection; another was our public digital scholarship approach, in which student participants shared the process and products of their work via public posts on the DFS website. Descriptive and factor analysis results from anonymous assessment data suggest strong participant response and likely future potential of digital field scholarship across class level and gender. When set into the context of the four institutions that supported the 2012–2013 sandbox, we see further opportunities for digital field scholarship on our and other campuses, provided that an optimal balance is struck between challenges and rewards along technical, pedagogical, and practical axes. Ultimately, digital field scholarship will be judged for its scholarship and for extending the experimental, open-ended inquiry that characterizes liberal education.
      PubDate: 2014-09-20
  • Evaluating a digital humanities research environment: the CULTURA approach
    • Abstract: Digital humanities initiatives play an important role in making cultural heritage collections accessible to the global community of researchers and general public for the first time. Further work is needed to provide useful and usable tools to support users in working with those digital contents in virtual environments. The CULTURA project has developed a corpus agnostic research environment integrating innovative services that guide, assist and empower a broad spectrum of users in their interaction with cultural artefacts. This article presents (1) the CULTURA system and services and the two collections that have been used for testing and deploying the digital humanities research environment, and (2) an evaluation methodology and formative evaluation study with apprentice researchers. An evaluation model was developed which has served as a common ground for systematic evaluations of the CULTURA environment with user communities around the two test bed collections. The evaluation method has proven to be suitable for accommodating different evaluation strategies and allows meaningful consolidation of evaluation results. The evaluation outcomes indicate a positive perception of CULTURA. A range of useful suggestions for future improvement has been collected and fed back into the development of the next release of the research environment.
      PubDate: 2014-09-16
  • A case study on propagating and updating provenance information using the
           CIDOC CRM
    • Abstract: Provenance information of digital objects maintained by digital libraries and archives is crucial for authenticity assessment, reproducibility and accountability. Such information is commonly stored on metadata placed in various Metadata Repositories (MRs) or Knowledge Bases (KBs). Nevertheless, in various settings it is prohibitive to store the provenance of each digital object due to the high storage space requirements that are needed for having complete provenance. In this paper, we introduce provenance-based inference rules as a means to complete the provenance information, to reduce the amount of provenance information that has to be stored, and to ease quality control (e.g., corrections). Roughly, we show how provenance information can be propagated by identifying a number of basic inference rules over a core conceptual model for representing provenance. The propagation of provenance concerns fundamental modelling concepts such as actors, activities, events, devices and information objects, and their associations. However, since a MR/KB is not static but changes over time due to several factors, the question that arises is how we can satisfy update requests while still supporting the aforementioned inference rules. Towards this end, we elaborate on the specification of the required add/delete operations, consider two different semantics for deletion of information, and provide the corresponding update algorithms. Finally, we report extensive comparative results for different repository policies regarding the derivation of new knowledge, in datasets containing up to one million RDF triples. The results allow us to understand the tradeoffs related to the use of inference rules on storage space and performance of queries and updates.
      PubDate: 2014-08-29
  • Sifting useful comments from Flickr Commons and YouTube
    • Abstract: Cultural institutions are increasingly contributing content to social media platforms to raise awareness and promote use of their collections. Furthermore, they are often the recipients of user comments containing information that may be incorporated in their catalog records. However, not all user-generated comments can be used for the purpose of enriching metadata records. Judging the usefulness of a large number of user comments is a labor-intensive task. Accordingly, our aim was to provide automated support for curation of potentially useful social media comments on digital objects. In this paper, the notion of usefulness is examined in the context of social media comments and compared from the perspective of both end-users and expert users. A machine-learning approach is then introduced to automatically classify comments according to their usefulness. This approach uses syntactic and semantic comment features while taking user context into consideration. We present the results of an experiment we conducted on user comments collected from Flickr Commons collections and YouTube. A study is then carried out on the correlation between the commenting culture of a platform (YouTube and Flickr) with usefulness prediction. Our findings indicate that a few relatively straightforward features can be used for inferring useful comments. However, the influence of features on usefulness classification may vary according to the commenting cultures of platforms.
      PubDate: 2014-08-20
  • How to assess image quality within a workflow chain: an overview
    • Abstract: Image quality assessment (IQA) is a multi-dimensional research problem and an active and evolving research area. This paper aims to provide an overview of the state of the art of the IQA methods, putting in evidence their applicability and limitations in different application domains. We outline the relationship between the image workflow chain and the IQA approaches reviewing the literature on IQA methods, classifying and summarizing the available metrics. We present general guidelines for three workflow chains in which IQA policies are required. The three workflow chains refer to: high-quality image archives, biometric system and consumer collections of personal photos. Finally, we illustrate a real case study referring to a printing workflow chain, where we suggest and actually evaluate the performance of a set of specific IQA methods.
      PubDate: 2014-08-15
  • A comprehensive evaluation of scholarly paper recommendation using
           potential citation papers
    • Abstract: To help generate relevant suggestions for researchers, recommendation systems have started to leverage the latent interests in the publication profiles of the researchers themselves. While using such a publication citation network has been shown to enhance performance, the network is often sparse, making recommendation difficult. To alleviate this sparsity, in our former work, we identified “potential citation papers” through the use of collaborative filtering. Also, as different logical sections of a paper have different significance, as a secondary contribution, we investigated which sections of papers can be leveraged to represent papers effectively. While this initial approach works well for researchers vested in a single discipline, it generates poor predictions for scientists who work on several different topics in the discipline (hereafter, “intra-disciplinary”). We thus extend our previous work in this paper by proposing an adaptive neighbor selection method to overcome this problem in our imputation-based collaborative filtering framework. On a publicly-available scholarly paper recommendation dataset, we show that recommendation accuracy significantly outperforms state-of-the-art recommendation baselines as measured by nDCG and MRR, when using our adaptive neighbor selection method. While recommendation performance is enhanced for all researchers, improvements are more marked for intra-disciplinary researchers, showing that our method does address the targeted audience.
      PubDate: 2014-08-10
  • Evaluating sliding and sticky target policies by measuring temporal drift
           in acyclic walks through a web archive
    • Abstract: When viewing an archived page using the archive’s user interface (UI), the user selects a datetime to view from a list. The archived web page, if available, is then displayed. From this display, the web archive UI attempts to simulate the web browsing experience by smoothly transitioning between archived pages. During this process, the target datetime changes with each link followed, potentially drifting away from the datetime originally selected. For sparsely archived resources, this almost transparent drift can be many years in just a few clicks. We conducted 200,000 acyclic walks of archived pages, following up to 50 links per walk, comparing the results of two target datetime policies. The Sliding Target policy allows the target datetime to change as it does in archive UIs such as the Internet Archive’s Wayback Machine. The Sticky Target policy, represented by the Memento API, keeps the target datetime the same throughout the walk. We found that the Sliding Target policy drift increases with the number of walk steps, number of domains visited, and choice (number of links available). However, the Sticky Target policy controls temporal drift, holding it to \(<\) 30 days on average regardless of walk length or number of domains visited. The Sticky Target policy shows some increase as choice increases, but this may be caused by other factors. We conclude that based on walk length, the Sticky Target policy generally produces at least 30 days less drift than the Sliding Target policy.
      PubDate: 2014-08-05
  • Evaluating distance-based clustering for user (browse and click) sessions
           in a domain-specific collection
    • Abstract: We seek to improve information retrieval in a domain-specific collection by clustering user sessions from a click log and then classifying later user sessions in real time. As a preliminary step, we explore the main assumption of this approach: whether user sessions in such a site are related to the question that they are answering. Since a large class of machine learning algorithms use a distance measure at the core, we evaluate the suitability of common machine learning distance measures to distinguish sessions of users searching for the answer to same or different questions. We found that two distance measures work very well for our task and three others do not. As a further step, we then investigate how effective the distance measures are when used in clustering. For our dataset, we conducted a user study where we had multiple users answer the same set of questions. This data, grouped by question, was used as our gold standard for evaluating the clusters produced by the clustering algorithms. We found that the observed difference between the two classes of distance measures affected the quality of the clusterings, as expected. We also found that one of the two distance measures that worked well to differentiate sessions, worked significantly better than the other when clustering. Finally, we discuss why some distance metrics performed better than others in the two parts of our work.
      PubDate: 2014-08-01
  • Introduction to the focused issue on the 17th International Conference on
           Theory and Practice of Digital Libraries (TPDL 2013)
    • PubDate: 2014-06-06
  • A system for high quality crowdsourced indigenous language transcription
    • Abstract: In this article, a crowdsourcing method is proposed to transcribe manuscripts from the Bleek and Lloyd Collection, where non-expert volunteers transcribe pages of the handwritten text using an online tool. The digital Bleek and Lloyd Collection is a rare collection that contains artwork, notebooks and dictionaries of the indigenous people of Southern Africa. The notebooks, in particular, contain stories that encode the language, culture and beliefs of these people, handwritten in now-extinct languages with a specialized notation system. Previous attempts have been made to convert the approximately 20,000 pages of text to a machine-readable form using machine learning algorithms but, due to the complexity of the text, the recognition accuracy was low. This article presents details of the system used to enable transcription by volunteers as well as results from experiments that were conducted to determine the quality and consistency of transcriptions. The results show that volunteers are able to produce reliable transcriptions of high quality. The inter-transcriber agreement is 80 % for Xam text and 95 % for English text. When the Xam text transcriptions produced by the volunteers are compared with a gold standard, the volunteers achieve an average accuracy of 64.75 %, which exceeded that in previous work. Finally, the degree of transcription agreement correlates with the degree of transcription accuracy. This suggests that the quality of unseen data can be assessed based on the degree of agreement among transcribers.
      PubDate: 2014-04-11
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