Mooshka: a system for the management of multidimensional gene expression data in situ

Pisarev, Andrei; Poustelnikova, Ekaterina; Samsonova, Maria; Baumann, Peter

doi:10.1016/s0306-4379(02)00074-1

Cited by 13 publications

(2 citation statements)

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“…The management, retrieval and analysis of multidimensional gene expression data [29] lands itself nicely to the integration of relational and array data. Data ranges from two-dimensional images of gene expression patterns to complex arrays describing spatio-temporal dynamics of gene expression within regulatory network.…”

Section: Gene Expression Data Managementmentioning

confidence: 99%

“…Based on the aforementioned ISO SQL stub it provides a fully-fledged set of structural and operational array constructs completely integrated and compatible with SQL and orthogonal to its set semantics. While based mainly on the conceptualization of rasdaman [3], which has been proven successful in numerous multi-Terabyte operational services [6,26,7,28,29], it also honors recent developments in the array databases field, notably SciDB and SciQL.…”

Section: Introductionmentioning

confidence: 99%

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Homogenizing Data and Metadata Retrieval in Scientific Applications

Mišev

Baumann

2015

Proceedings of the ACM Eighteenth International Workshop on Data Warehousing and OLAP

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Support for large arrays has been increasingly gaining attention by the database community. Array databases are a quickly expanding category of database management systems that treat large, multidimensional array data as firstclass database citizens, allowing convenient and efficient storage and retrieval. Large array data on its own, however, is rarely meaningful or machine understandable. Therefore, arrays are almost always linked to additional, small metadata, typically managed in relational databases. This leads to an information integration gap, an "impedance mismatch" that we address with the work presented in this paper.We aim to remedy this with ASQL (Array SQL), an augmentation of the standard relational database language SQL with multidimensional array processing capabilities. Besides core ASQL concepts, this paper presents a general mediator approach to implementing it by combining a relational with an array DBMS. This improves on the most common situation of systems specializing in either relational or array processing, but not both. In particular we implement ASQLDB on top of the array DBMS rasdaman and relational DBMS HSQLDB, and demonstrate its potential for practical applicability through real world use cases. Initial benchmark comparisons against another array DBMS with a similar goal but rather different approach reveal advantageous results for ASQL.

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Section: Gene Expression Data Managementmentioning

confidence: 99%