Knowledge organization and its contributions in a Big Data context

被引:0
作者
Meschini, Fabio Orsi [1 ]
Francelin, Marivalde Moacir [2 ]
机构
[1] Univ Sao Paulo, Escola Comunicacoes & Artes, Programa Posgrad Ciencia Informacao, 443, Cidade Univ, BR-05508020 Sao Paulo, SP, Brazil
[2] Univ Sao Paulo, Escola Comunicacoes & Artes, Programa Posgrad Ciencia Informacao, Sao Paulo, SP, Brazil
来源
TRANSINFORMACAO | 2022年 / 34卷
关键词
Categorization; Data; Scientific production; Representation of information; CITATION ANALYSIS; SYSTEMS; POWER;
D O I
10.1590/2318-0889202234e210075
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
to the collection, curation and use of data. The study concludes that it is necessary to expand research related to social, cognitive, epistemological, and methodological issues, as well as the elaboration of more studies focused on The objective of this work is to analyze the Big Data phenomenon (a technological context that deals with the analysis of intense data flows to obtain information that may be relevant to different social actors) and its impact on Knowledge Organization (an area that enables informational discovery, using for this the construction of organizational tools of semantic nature such as thesauri, taxonomies and classification systems aiming at the dissemination and development of knowledge in society) through a proposal to categorize scientific production. Based on the categories: product, processes and cognition oriented and in the epistemological, applied, political and social dimensions of ISKO-Brasil, this proposal represents a possibility of understanding the phenomenon of data in Knowledge Organization. It uses the exploratory method for reviewing literature and searching specialized databases on the topic of Big Data and Knowledge Organization. The results demonstrate the predominance of a more applied profile and oriented to processes related in this intense data scenario. It contributes to the understanding and expansion of research scenarios on Big Data in Knowledge Organization.
引用
收藏
页数:11
相关论文
共 50 条
  • [21] Big data analytics business value and firm performance: linking with environmental context
    Vitari, Claudio
    Raguseo, Elisabetta
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2020, 58 (18) : 5456 - 5476
  • [22] Using small data to interpret big data: 311 reports as individual contributions to informal social control in urban neighborhoods
    O'Brien, Daniel Tumminelli
    SOCIAL SCIENCE RESEARCH, 2016, 59 : 83 - 96
  • [23] Unstructured big data analytics for retrieving e-commerce logistics knowledge
    Wu, Pei-Ju
    Lin, Kun-Chen
    TELEMATICS AND INFORMATICS, 2018, 35 (01) : 237 - 244
  • [24] Data challenges for public libraries: African perspectives and the social context of knowledge
    Lynch, Renee
    Young, Jason C.
    Jowaisas, Chris
    Rothschild, Chris
    Garrido, Maria
    Sam, Joel
    Boakye-Achampong, Stanley
    INFORMATION DEVELOPMENT, 2021, 37 (02) : 292 - 306
  • [25] Probabilistic Estimation of the State of Electric Vehicles for Smart Grid Applications in Big Data Context
    Soares, Joao
    Borges, Nuno
    Canizes, Bruno
    Vale, Zita
    2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2015,
  • [26] Big data analytics and competitive advantage: the strategic role of firm-specific knowledge
    Dahiya, Rajiv
    Le, Son
    Ring, John Kirk
    Watson, Kevin
    JOURNAL OF STRATEGY AND MANAGEMENT, 2022, 15 (02) : 175 - 193
  • [27] Unveiling knowledge dynamics for competitive advantage: insights into hiding, sharing and big data management
    Rehman, Shafique Ur
    Bresciani, Stefano
    Riaz, Adil
    Giovando, Guido
    EUROMED JOURNAL OF BUSINESS, 2024,
  • [28] Big data and firm marketing performance: Findings from knowledge-based view
    Gupta, Shivam
    Justy, Theo
    Kamboj, Shampy
    Kumar, Ajay
    Kristoffersen, Eivind
    TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2021, 171
  • [29] Big data for small and medium-sized enterprises (SME): a knowledge management model
    Wang Shouhong
    Wang Hai
    JOURNAL OF KNOWLEDGE MANAGEMENT, 2020, 24 (04) : 881 - 897