Research

The research topics of the group are oriented to performance, exploration and quality in data management, focusing particularly on large data volumes and applying methods from computational learning, machine learning, data mining, database algorithmics and formal logic to the design of innovative algorithms and systems for its analysis and prediction.

Graph Databases Benchmarking

Performance Optimization

Data Generation

Query Languages

Mobile

Graph Algorithms and Applications Social Networks

Recommendation Systems

Mobility in Smart Cities

Knowledge Discovery

 

Graph Databases Benchmarking

Coming soon…

Related project: LDBC

Graph Databases Performance Optimization

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Graph Databases Data Generation

“Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.”

Related project: LDBC

Graph Databases Query Languages

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Related project: Qeast

Graph Databases Mobile

The content stored in Mobile Devices grows as the users evolve in their tastes, the trends in applications change and the needs for each work environment grow. This way, the users of mobile devices keep increasing the amount of data and metadata generated as well as the apps installed in their device. Also, the users keep growing their interaction with social media apps such as Twitter, Facebook or LinkedIn, increasing the amount of data managed by third parties.

We believe that Mobile Graph Databases (M-GDBs) are the perfect match to manage and query all those type of connected datasets for two main reasons: the management of a single data repository will provide added-value linked data and the querying capabilities will be rocketed with M-GDBs. This is why DAMA-UPC is pushing hard towards expanding our knowledge base about M-GDBs

Related project: CIGO!

Social Networks

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Related projects: SOMATCH, IT2Rail, TETRACOM

Recommendation Systems

“Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.”

Related projects: SOMATCH, IT2RailQeast

Mobility in Smart Cities

Integrating data from various sources such as mobile apps, sensors, government data, private data and Open Data is playing a key role if we want to develop better understanding on how citizens behave and how cities evolve. Applying this knowledge is going to become a crucial for the next generation of Smart Cities. Graph databases  allow the visualisation and analysis of all the data generated in a modern city, making it actionable through associated Mobile Apps.

The CIGO! platform, developed by Sparsity Technologies with DAMA-UPC support, helps cities and companies make sense out of all the information available in order to improve their operational efficiency and/or the quality of their product or service to ultimately make an impact on the citizen’s quality of life.

Related project: CIGO!

Knowledge Discovery

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Related project: Qeast

Query Languages

Coming soon…

Related project: CoherentPaaS

 

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