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| 2. |
- Andrejev, Andrej, et al.
(författare)
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Scientific data as RDF with arrays : Tight integration of SciSPARQL queries into MATLAB
- 2014
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Ingår i: Proc. ISWC 2014 Posters & Demonstrations Track. - : RWTH Aachen University. ; , s. 221-224
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Konferensbidrag (refereegranskat)abstract
- We present an integrated solution for storing and querying scientific data and metadata, using MATLAB envi ronment as client front-end and our prototype DBMS on the server. We use RDF for experiment metadata, and numeric arrays for the rest. Our extension of SPARQL supports array operations and extensibility with foreign functions.
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| 4. |
- Andrejev, Andrej, et al.
(författare)
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Spatio-Temporal Gridded Data Processing on the Semantic Web
- 2015
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Ingår i: 2015 IEEE International Conference On Data Science And Data Intensive Systems. - 9781509002146 ; , s. 38-45
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Konferensbidrag (refereegranskat)abstract
- Multidimensional array data, such as remote-sensing imagery and timeseries, climate model simulations, telescope observations, and medical images, contribute massively to virtually all science and engineering domains, and hence play a key role in 'Big Data' challenges. Pure array storage management and analytics is relatively well understood today. However, arrays in practice never come alone, but are accompanied by metadata, including domain, range, provenance information, etc. The structure of this metadata is far less regular than arrays or tables, and may be incomplete or different from one array instance to another. Particularly in the field of the Semantic Web such integrated representations must convey a sufficiently complete and reasonable semantics for machine-machine communication. We show how the Resource Description Framework (RDF), the Semantic Web graph model for metadata, can be leveraged for such data/metadata integration specifically for representing spatio-temporal grid data. Based on the notion of a coverage as established by the Open Geospatial Consortium (OGC) we present a hybrid data store where efficiently represented arrays are incorporated as nodes into RDF graphs and connected to their metadata. We have extended the Semantic Web query language SPARQL to incorporate array query semantics and other functionality making it suitable for processing of large numeric arrays, including geo coverages.
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| 5. |
- Andrejev, Andrej, et al.
(författare)
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Strategies for array data retrieval from a relational back-end based on access patterns
- 2020
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 102:5, s. 1139-1158
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Tidskriftsartikel (refereegranskat)abstract
- Multidimensional numeric arrays are often serialized to binary formats for efficient storage and processing. These representations can be stored as binary objects in existing relational database management systems. To minimize data transfer overhead when arrays are large and only parts of arrays are accessed, it is favorable to split these arrays into separately stored chunks. We process queries expressed in an extended graph query language SPARQL, treating arrays as node values and having syntax for specifying array projection, element and range selection operations as part of a query. When a query selects parts of one or more arrays, only the relevant chunks of each array should be retrieved from the relational database. The retrieval is made by automatically generated SQL queries. We evaluate different strategies for partitioning the array content, and for generating the SQL queries that retrieve it on demand. For this purpose, we present a mini-benchmark, featuring a number of typical array access patterns. We draw some actionable conclusions from the performance numbers.
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| 7. |
- Badiozamany, Sobhan, 1983-, et al.
(författare)
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Framework for real-time clustering over sliding windows
- 2016
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Ingår i: Proc. 28th International Conference on Scientific and Statistical Database Management. - New York : ACM Press. - 9781450342155 ; , s. 1-13
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Konferensbidrag (refereegranskat)
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| 8. |
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| 9. |
- Badiozamany, Sobhan, et al.
(författare)
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Scalable ordered indexing of streaming data
- 2012
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Ingår i: 3rd International Workshop on Accelerating Data Management Systems using Modern Processor and Storage Architectures. ; , s. 11-
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Konferensbidrag (refereegranskat)
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| 10. |
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