Leveraging Spatio-Temporal Soccer Data to Define a Graphical Query Language for Game Recordings

2018 ◽  
Author(s):  
Keven Richly
Keyword(s):  
Query Language ◽  
Spatio Temporal ◽  
Graphical Query Language

scholarly journals Array databases: concepts, standards, implementations

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peter Baumann ◽  
Dimitar Misev ◽  
Vlad Merticariu ◽  
Bang Pham Huu
Keyword(s):  
Service Quality ◽  
Ad Hoc ◽  
Query Language ◽  
Distributed Processing ◽  
Database Systems ◽  
Database Technology ◽  
Comprehensive Survey ◽  
Spatio Temporal ◽  
And Performance ◽  
Array Databases

AbstractMulti-dimensional arrays (also known as raster data or gridded data) play a key role in many, if not all science and engineering domains where they typically represent spatio-temporal sensor, image, simulation output, or statistics “datacubes”. As classic database technology does not support arrays adequately, such data today are maintained mostly in silo solutions, with architectures that tend to erode and not keep up with the increasing requirements on performance and service quality. Array Database systems attempt to close this gap by providing declarative query support for flexible ad-hoc analytics on large n-D arrays, similar to what SQL offers on set-oriented data, XQuery on hierarchical data, and SPARQL and CIPHER on graph data. Today, Petascale Array Database installations exist, employing massive parallelism and distributed processing. Hence, questions arise about technology and standards available, usability, and overall maturity. Several papers have compared models and formalisms, and benchmarks have been undertaken as well, typically comparing two systems against each other. While each of these represent valuable research to the best of our knowledge there is no comprehensive survey combining model, query language, architecture, and practical usability, and performance aspects. The size of this comparison differentiates our study as well with 19 systems compared, four benchmarked to an extent and depth clearly exceeding previous papers in the field; for example, subsetting tests were designed in a way that systems cannot be tuned to specifically these queries. It is hoped that this gives a representative overview to all who want to immerse into the field as well as a clear guidance to those who need to choose the best suited datacube tool for their application. This article presents results of the Research Data Alliance (RDA) Array Database Assessment Working Group (ADA:WG), a subgroup of the Big Data Interest Group. It has elicited the state of the art in Array Databases, technically supported by IEEE GRSS and CODATA Germany, to answer the question: how can data scientists and engineers benefit from Array Database technology? As it turns out, Array Databases can offer significant advantages in terms of flexibility, functionality, extensibility, as well as performance and scalability—in total, the database approach of offering “datacubes” analysis-ready heralds a new level of service quality. Investigation shows that there is a lively ecosystem of technology with increasing uptake, and proven array analytics standards are in place. Consequently, such approaches have to be considered a serious option for datacube services in science, engineering and beyond. Tools, though, vary greatly in functionality and performance as it turns out.

Constraint-Based Multi-Dimensional Databases

2009 ◽  
pp. 961-986
Author(s):  
Franck Ravat ◽  
Olivier Teste ◽  
Gilles Zurfluh
Keyword(s):  
Graphical Representation ◽  
Query Language ◽  
Computer Scientist ◽  
Data Querying ◽  
Definition Of ◽  
Multidimensional Modelling ◽  
Graphical Query Language ◽  
Drill Down

This chapter deals with constraint-based multidimensional modelling. The model we define integrates a constellation of facts and dimensions. Along each dimension, various hierarchies are possibly defined and the model supports multiple instantiations of dimensions. The main contribution is the definition of intra-dimension constraints between hierarchies of a same dimension as well as inter-dimension constraints of various dimensions. To facilitate data querying, we define a multi-dimensional query algebra, which integrates the main multi-dimensional operators such as rotations, drill down, roll up… These operators support the constraint-based multi-dimensional modelling. Finally, we present two implementations of this algebra. First, OLAP-SQL is a textual language integrating multi-dimensional concepts (fact, dimension, hierarchy), but it is based on classical SQL syntax. This language is dedicated to specialists such as multi-dimensional database administrators. Second, a graphical query language is presented. This language consists in a graphical representation of multi-dimensional databases, and users specify directly their queries over this graph. This approach is dedicated to non-computer scientist users.

Constraint-Based Multi-Dimensional Databases

2011 ◽  
pp. 323-360 ◽  
Author(s):  
Franck Ravat ◽  
Olivier Teste ◽  
Gilles Zurfluh
Keyword(s):  
Graphical Representation ◽  
Query Language ◽  
Computer Scientist ◽  
Data Querying ◽  
Definition Of ◽  
Graphical Query Language ◽  
Drill Down

This chapter deals with constraint-based multi-dimensional modelling. The model we define integrates a constellation of facts and dimensions. Along each dimension, various hierarchies are possibly defined and the model supports multiple instantiations of dimensions. The main contribution is the definition of intra-dimension constraints between hierarchies of a same dimension as well as inter-dimension constraints of various dimensions. To facilitate data querying, we define a multi-dimensional query algebra, which integrates the main multi-dimensional operators such as rotations, drill down, roll up… These operators support the constraint-based multi-dimensional modelling. Finally, we present two implementations of this algebra. First, OLAP-SQL is a textual language integrating multi-dimensional concepts (fact, dimension, hierarchy), but it is based on classical SQL syntax. This language is dedicated tospecialists such as multi-dimensional database administrators. Second, a graphical query language is presented. This language consists in a graphical representation of multi-dimensional databases, and users specify directly their queries over this graph. This approach is dedicated to non-computer scientist users.

Sign in / Sign up

Export Citation Format

Share Document