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About

About

Investigadora no projeto "TAIL" - Research Data Management. Prepare and describe data for sharing and re-use.

Tenho licenciatura em Matematica e Informática, Mestrado em Ciencias de Informação.

Meus interesses atuais da investigação ligados à gestão de dados de investigação, vocabulários controlados, descrição de dados, qualidade de metadados, colaboração com investigadores de otros domínios com o objetivo de motivar e promover a descrição  e partilha de dados de investigação com através de plataforma de gestão de dados Dendro e repositório de dados de investigação CKAN-INESC TEC e CKAN-UP,  além disto realizo testes de funcionamento destes plataformas.

Interest
Topics
Details

Details

  • Name

    Yulia Karimova
  • Cluster

    Computer Science
  • Role

    Research Assistant
  • Since

    17th June 2016
001
Publications

2021

Institutional support for data management plans: case studies for a systematic approach

Authors
Karimova, Y; Ribeiro, C; David, G;

Publication
Int. J. Metadata Semant. Ontologies

Abstract
Researchers have to ensure that their projects comply with Research Data Management (RDM) requirements. Consequently, the main funding agencies require Data Management Plans (DMPs) for grant applications. So, institutions are investing in RDM tools and implementing RDM workflows in order to support their researchers. In this context, we propose a collaborative DMP-building method that involves researchers, data stewards and other parties if required. This method was applied as part of an RDM workflow in research groups across several scientific domains. We describe it as a systematic approach and illustrate it through a set of case studies. We also address the DMP monitoring process during the life cycle of projects. The feedback from the researchers highlighted the advantages of creating DMPs and their growing need. So, there is motivation to improve the DMP support process according to the machine-actionable DMPs concept and to the best practices in each scientific community. © 2021 Inderscience Enterprises Ltd.. All rights reserved.

2020

Institutional Support for Data Management Plans: Five Case Studies

Authors
Karimova, Y; Ribeiro, C; David, G;

Publication
Metadata and Semantic Research - 14th International Conference, MTSR 2020, Madrid, Spain, December 2-4, 2020, Revised Selected Papers

Abstract

2019

Data Deposit in a CKAN Repository: A Dublin Core-Based Simplified Workflow

Authors
Karimova, Y; Castro, JA; Ribeiro, C;

Publication
Digital Libraries: Supporting Open Science - 15th Italian Research Conference on Digital Libraries, IRCDL 2019, Pisa, Italy, January 31 - February 1, 2019, Proceedings

Abstract

2017

Involving data creators in an ontology-based design process for metadata models

Authors
Castro, JA; Amorim, RC; Gattelli, R; Karimova, Y; Da Silva, JR; Ribeiro, C;

Publication
Developing Metadata Application Profiles

Abstract
Research data are the cornerstone of science and their current fast rate of production is disquieting researchers. Adequate research data management strongly depends on accurate metadata records that capture the production context of the datasets, thus enabling data interpretation and reuse. This chapter reports on the authors' experience in the development of the metadata models, formalized as ontologies, for several research domains, involving members from small research teams in the overall process. This process is instantiated with four case studies: vehicle simulation; hydrogen production; biological oceanography and social sciences. The authors also present a data description workflow that includes a research data management platform, named Dendro, where researchers can prepare their datasets for further deposit in external data repositories. © 2017, IGI Global.

2017

Promoting Semantic Annotation of Research Data by Their Creators: A Use Case with B2NOTE at the End of the RDM Workflow

Authors
Karimova, Y; Castro, JA; da Silva, JR; Pereira, N; Ribeiro, C;

Publication
Metadata and Semantic Research - Communications in Computer and Information Science

Abstract