TY - JOUR
T1 - Managing big RDF data in clouds
T2 - Challenges, opportunities, and solutions
AU - Elzein, Nahla Mohammed
AU - Majid, Mazlina Abdul
AU - Hashem, Ibrahim Abaker Targio
AU - Yaqoob, Ibrar
AU - Alaba, Fadele Ayotunde
AU - Imran, Muhammad
N1 - Funding Information:
This paper is financially supported by the Malaysian Ministry of Education under the University of Malaya High Impact Research Grant UM.C/625/1/HIR/MoE/FCSIT/03 . Imran's work is supported by the Deanship of Scientific Research at King Saud University through research group no . (RG # 1435-051 ).
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/5
Y1 - 2018/5
N2 - The expansion of the services of the Semantic Web and the evolution of cloud computing technologies have significantly enhanced the capability of preserving and publishing information in standard open web formats, such that data can be both human-readable and machine-processable. This situation meets the challenge in the current big data era to effectively store, retrieve, and analyze resource description framework (RDF) data in swarms. This paper presents an overview of the existing challenges, evolving opportunities, and current developments towards managing big RDF data in clouds and provides guidance and substantial lessons learned from research in big data management. In particular, it highlights the basic principles of RDF data management, which allow researchers to know the most recent stage in developing RDF graphs and its achievement. Additionally, the research provides comparative studies among current storage systems and query processing approaches in understanding their efficiency. The paper also provides a vision for long-term future research directions by providing highlights on future challenges and opportunities in RDF domain.
AB - The expansion of the services of the Semantic Web and the evolution of cloud computing technologies have significantly enhanced the capability of preserving and publishing information in standard open web formats, such that data can be both human-readable and machine-processable. This situation meets the challenge in the current big data era to effectively store, retrieve, and analyze resource description framework (RDF) data in swarms. This paper presents an overview of the existing challenges, evolving opportunities, and current developments towards managing big RDF data in clouds and provides guidance and substantial lessons learned from research in big data management. In particular, it highlights the basic principles of RDF data management, which allow researchers to know the most recent stage in developing RDF graphs and its achievement. Additionally, the research provides comparative studies among current storage systems and query processing approaches in understanding their efficiency. The paper also provides a vision for long-term future research directions by providing highlights on future challenges and opportunities in RDF domain.
KW - Big data
KW - Cloud computing
KW - Linked data
KW - RDF graphs
KW - Semantic Web
UR - http://www.scopus.com/inward/record.url?scp=85044868198&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2018.02.019
DO - 10.1016/j.scs.2018.02.019
M3 - Article
AN - SCOPUS:85044868198
SN - 2210-6707
VL - 39
SP - 375
EP - 386
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
ER -