Details
| Original language | English |
|---|---|
| Title of host publication | 21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Proceedings |
| Subtitle of host publication | 21st International Conference on Information Integration and Web-Based Applications & Services |
| Editors | Maria Indrawan-Santiago, Eric Pardede, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Anderst-Kotsis |
| Publisher | Association for Computing Machinery (ACM) |
| ISBN (electronic) | 9781450371797 |
| Publication status | Published - 2 Dec 2019 |
| Externally published | Yes |
| Event | 21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Munich, Germany Duration: 2 Dec 2019 → 4 Dec 2019 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Abstract
Increasing data volumes have extensively increased application possibilities. However, accessing this data in an ad hoc manner remains an unsolved problem due to the diversity of data management approaches, formats and storage frameworks, resulting in the need to effectively access and process distributed heterogeneous data at scale. For years, SemanticWeb techniques have addressed data integration challenges with practical knowledge representation models and ontology-based mappings. Leveraging these techniques, we provide a solution enabling uniform access to large, heterogeneous data sources, without enforcing centralization; thus realizing the vision of a Semantic Data Lake. In this paper, we define the core concepts underlying this vision and the architectural requirements that systems implementing it need to fulfill. Squerall, an example of such a system, is an extensible framework built on top of state-ofthe- A rt Big Data technologies. We focus on Squerall's distributed query execution techniques and strategies, empirically evaluating its performance throughout its various sub-phases.
Keywords
- Big Data, Data Variety, NoSQL, Semantic Data Lake, SPARQL
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Computer Networks and Communications
Cite this
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21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Proceedings: 21st International Conference on Information Integration and Web-Based Applications & Services. ed. / Maria Indrawan-Santiago; Eric Pardede; Ivan Luiz Salvadori; Matthias Steinbauer; Ismail Khalil; Gabriele Anderst-Kotsis. Association for Computing Machinery (ACM), 2019. (ACM International Conference Proceeding Series).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Uniform Access to Multiform Data Lakes using Semantic Technologies
AU - Mami, Mohamed Nadjib
AU - Graux, Damien
AU - Scerri, Simon
AU - Jabeen, Hajira
AU - Auer, Soren
AU - Lehmann, Jens
N1 - Funding Information: This work is partly supported by the EU H2020 projects BETTER (GA 776280) and QualiChain (GA 822404); and by the ADAPT Centre for Digital Content Technology funded under the SFI Research Centres Programme (Grant 13/RC/2106) and co-funded under the European Regional Development Fund.
PY - 2019/12/2
Y1 - 2019/12/2
N2 - Increasing data volumes have extensively increased application possibilities. However, accessing this data in an ad hoc manner remains an unsolved problem due to the diversity of data management approaches, formats and storage frameworks, resulting in the need to effectively access and process distributed heterogeneous data at scale. For years, SemanticWeb techniques have addressed data integration challenges with practical knowledge representation models and ontology-based mappings. Leveraging these techniques, we provide a solution enabling uniform access to large, heterogeneous data sources, without enforcing centralization; thus realizing the vision of a Semantic Data Lake. In this paper, we define the core concepts underlying this vision and the architectural requirements that systems implementing it need to fulfill. Squerall, an example of such a system, is an extensible framework built on top of state-ofthe- A rt Big Data technologies. We focus on Squerall's distributed query execution techniques and strategies, empirically evaluating its performance throughout its various sub-phases.
AB - Increasing data volumes have extensively increased application possibilities. However, accessing this data in an ad hoc manner remains an unsolved problem due to the diversity of data management approaches, formats and storage frameworks, resulting in the need to effectively access and process distributed heterogeneous data at scale. For years, SemanticWeb techniques have addressed data integration challenges with practical knowledge representation models and ontology-based mappings. Leveraging these techniques, we provide a solution enabling uniform access to large, heterogeneous data sources, without enforcing centralization; thus realizing the vision of a Semantic Data Lake. In this paper, we define the core concepts underlying this vision and the architectural requirements that systems implementing it need to fulfill. Squerall, an example of such a system, is an extensible framework built on top of state-ofthe- A rt Big Data technologies. We focus on Squerall's distributed query execution techniques and strategies, empirically evaluating its performance throughout its various sub-phases.
KW - Big Data
KW - Data Variety
KW - NoSQL
KW - Semantic Data Lake
KW - SPARQL
UR - http://www.scopus.com/inward/record.url?scp=85117539584&partnerID=8YFLogxK
U2 - 10.1145/3366030.3366054
DO - 10.1145/3366030.3366054
M3 - Conference contribution
T3 - ACM International Conference Proceeding Series
BT - 21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Proceedings
A2 - Indrawan-Santiago, Maria
A2 - Pardede, Eric
A2 - Salvadori, Ivan Luiz
A2 - Steinbauer, Matthias
A2 - Khalil, Ismail
A2 - Anderst-Kotsis, Gabriele
PB - Association for Computing Machinery (ACM)
T2 - 21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019
Y2 - 2 December 2019 through 4 December 2019
ER -