Reference number : GC-2017-Q3-00521, amendment number : , agreement type : G, recipient legal name : Kargar, Mehdi (University of Windsor), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Much of the world's high-quality enterprise and social data are stored as semi-structured and structured data._x000D_
This includes enterprises' RDBMSs, knowledge graphs, and social networks. All these data collections either_x000D_
are defined already as graph databases or can be re-modeled as graphs. Over the past decade, we have_x000D_
witnessed advances in storing and manipulating structured and semi-structured data, but we have not seen_x000D_
much progress in search over them._x000D_
As Surajit Chaudhuri (a distinguished scientist at Microsoft Research) addressed in his keynote talk at IEEE_x000D_
Data Engineering Conference in 2015, search over structured databases has fallen behind search over_x000D_
unstructured data. While scientists and business users look for exciting, actionable discoveries from their_x000D_
heterogeneous datasets, the need to provide effective search is profound. If we cannot deliver a powerful search_x000D_
system, much of the big data dream will not be achieved._x000D_
The existence of structure in graph databases offers potent means for data exploration compared with a set of_x000D_
disparate, unstructured documents. Traditionally, to access structured databases, users have to learn structured_x000D_
query languages, such as SQL or SPARQL. They also need to learn the schemas of the databases in which they_x000D_
have an interest. However, a non-technical user (i.e., anyone who does not know query languages or is not_x000D_
familiar with the given schema) is effectively locked out._x000D_
Exploring graph databases for non-technical users is currently not supported in IBM's Analytics Platform. This_x000D_
project will provide a solution for this problem. More specifically, we focus on designing a distributed and_x000D_
parallel keyword search system using IBM Analytics Platform to empower non-technical users to explore graph_x000D_
databases., program purpose french : Much of the world's high-quality enterprise and social data are stored as semi-structured and structured data._x000D_
This includes enterprises' RDBMSs, knowledge graphs, and social networks. All these data collections either_x000D_
are defined already as graph databases or can be re-modeled as graphs. Over the past decade, we have_x000D_
witnessed advances in storing and manipulating structured and semi-structured data, but we have not seen_x000D_
much progress in search over them._x000D_
As Surajit Chaudhuri (a distinguished scientist at Microsoft Research) addressed in his keynote talk at IEEE_x000D_
Data Engineering Conference in 2015, search over structured databases has fallen behind search over_x000D_
unstructured data. While scientists and business users look for exciting, actionable discoveries from their_x000D_
heterogeneous datasets, the need to provide effective search is profound. If we cannot deliver a powerful search_x000D_
system, much of the big data dream will not be achieved._x000D_
The existence of structure in graph databases offers potent means for data exploration compared with a set of_x000D_
disparate, unstructured documents. Traditionally, to access structured databases, users have to learn structured_x000D_
query languages, such as SQL or SPARQL. They also need to learn the schemas of the databases in which they_x000D_
have an interest. However, a non-technical user (i.e., anyone who does not know query languages or is not_x000D_
familiar with the given schema) is effectively locked out._x000D_
Exploring graph databases for non-technical users is currently not supported in IBM's Analytics Platform. This_x000D_
project will provide a solution for this problem. More specifically, we focus on designing a distributed and_x000D_
parallel keyword search system using IBM Analytics Platform to empower non-technical users to explore graph_x000D_
databases., agreement title english : Distributed Keyword Search over Graph Databases using IBM Analytics Platform, agreement title french : Distributed Keyword Search over Graph Databases using IBM Analytics Platform, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-10-18, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada