Klasifikasi Online dan Google

The purpose of this paper is to examine challenges facing bibliographic classification at both the practical and theoretical levels. At the practical level, libraries are increasingly dispensing with classifying books. At the theoretical level, many researchers, managers, and users believe that the activity of “classification” is not worth the effort, as search engines can be improved without the heavy cost of providing metadata

Is classification necessary after Google?

This presentation considers the nature of classification and the challenges that bibliographical faces in the digital age both in library practice and in information retrieval theory. It considers fundamental questions such as ?how do establish that A is a kind of X?? and ?how do we distinguish good from bad classifications?? The new trend of evidence based practice (EBP) is seen as an argument why classification is still necessary for scientific documentation, and the basic epistemological positions (empiricism, rationalism, historicism and pragmatism) is briefly considered in relation to classification

Organisation of information in a digital library: challenges and possibilities

Cilj ovoga rada je proučiti organizaciju informacija u digitalnim knjižnicama pošto su informacijske tehnologije revolucionizirale samu ulogu knjižnica. Za uvod u temu, prvotno će se objasniti što su digitalne knjižnice i koje su njihove zadaće, što ih razlikuje od tradicionalnih knjižnica te s kojim izazovima se suočavaju. Proučiti će se bibliografska i informacijska organizacija općenito u digitalnim knjižnicama, koja se kasnije nadovezuje na organizaciju mrežnih izvora odnosno sustava za organizaciju znanja. Naposljetku će se sve to pokušati ujediniti i prikazati na primjeru organizacije informacija Smithsonian digitalne knjižnice

Organisation of information in a digital library: challenges and possibilities

Cilj ovoga rada je proučiti organizaciju informacija u digitalnim knjižnicama pošto su informacijske tehnologije revolucionizirale samu ulogu knjižnica. Za uvod u temu, prvotno će se objasniti što su digitalne knjižnice i koje su njihove zadaće, što ih razlikuje od tradicionalnih knjižnica te s kojim izazovima se suočavaju. Proučiti će se bibliografska i informacijska organizacija općenito u digitalnim knjižnicama, koja se kasnije nadovezuje na organizaciju mrežnih izvora odnosno sustava za organizaciju znanja. Naposljetku će se sve to pokušati ujediniti i prikazati na primjeru organizacije informacija Smithsonian digitalne knjižnice

Evaluating BERT-based scientific relation classifiers for scholarly knowledge graph construction on digital library collections

The rapid growth of research publications has placed great demands on digital libraries (DL) for advanced information management technologies. To cater to these demands, techniques relying on knowledge-graph structures are being advocated. In such graph-based pipelines, inferring semantic relations between related scientific concepts is a crucial step. Recently, BERT-based pre-trained models have been popularly explored for automatic relation classification. Despite significant progress, most of them were evaluated in different scenarios, which limits their comparability. Furthermore, existing methods are primarily evaluated on clean texts, which ignores the digitization context of early scholarly publications in terms of machine scanning and optical character recognition (OCR). In such cases, the texts may contain OCR noise, in turn creating uncertainty about existing classifiers’ performances. To address these limitations, we started by creating OCR-noisy texts based on three clean corpora. Given these parallel corpora, we conducted a thorough empirical evaluation of eight Bert-based classification models by focusing on three factors: (1) Bert variants; (2) classification strategies; and, (3) OCR noise impacts. Experiments on clean data show that the domain-specific pre-trained Bert is the best variant to identify scientific relations. The strategy of predicting a single relation each time outperforms the one simultaneously identifying multiple relations in general. The optimal classifier’s performance can decline by around 10% to 20% in F-score on the noisy corpora. Insights discussed in this study can help DL stakeholders select techniques for building optimal knowledge-graph-based systems

Assessment, Usability, and Sociocultural Impacts of DataONE

DataONE, funded from 2009-2019 by the U.S. National Science Foundation, is an early example of a large-scale project that built both a cyberinfrastructure and culture of data discovery, sharing, and reuse. DataONE used a Working Group model, where a diverse group of participants collaborated on targeted research and development activities to achieve broader project goals. This article summarizes the work carried out by two of DataONE’s working groups: Usability & Assessment (2009-2019) and Sociocultural Issues (2009-2014). The activities of these working groups provide a unique longitudinal look at how scientists, librarians, and other key stakeholders engaged in convergence research to identify and analyze practices around research data management through the development of boundary objects, an iterative assessment program, and reflection. Members of the working groups disseminated their findings widely in papers, presentations, and datasets, reaching international audiences through publications in 25 different journals and presentations to over 5,000 people at interdisciplinary venues. The working groups helped inform the DataONE cyberinfrastructure and influenced the evolving data management landscape. By studying working groups over time, the paper also presents lessons learned about the working group model for global large-scale projects that bring together participants from multiple disciplines and communities in convergence research

Organização e representação de conhecimento: incrementos metodológicos e tecnológicos para o mapeamento conceitual.

Resumo. Na era do conhecimento, os processos de pesquisa, desenvolvimento e inovação têm sido executados, cada vez mais, por meio das chamadas redes de conhecimento, devido ao alto grau de complexidade e multi-inter-transdisciplinaridade das temáticas envolvidas. Este artigo apresenta e descreve uma metodologia de mapeamento de domínios de conhecimento, cuja execução permite o alinhamento de várias ferramentas objetivando sistemas de organização de conhecimento como recurso para facilitar a elaboração de sistemas de conceitos, expressões de busca e significação da informação recuperada em bases de dados. A metodologia proposta se constitui de quatro etapas, baseadas em métodos e técnicas de: mapeamento do domínio do conhecimento; codificação do conhecimento; aplicação de linguística de corpus e de processamento de linguagem natural e representação do conhecimento.Editores: Antonio Pedro Costa, Isabel Pinho, Brígida Mônica Faria, Luís Paulo Reis. CIAIQ 2019