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A description of the demon
SageCite demonstrator overview
SageCite demonstrator overview
monicaduke
Active Data : Managing Data-Life Cycle on Heterogeneous Systems and Infrastructures The Big Data challenge consists in managing, storing, analyzing and visualizing these huge and ever growing data sets to extract sense and knowledge. As the volume of data grows exponentially, the management of these data becomes more complex in proportion. A key point is to handle the complexity of the 'Data Life Cycle', i.e. the various operations performed on data: transfer, archiving, replication, deletion, etc. Indeed, data-intensive applications span over a large variety of devices and e-infrastructures which implies that many systems are involved in data management and processing. ''Active Data'' is new approach to automate and improve the expressiveness of data management applications. It consists of * a 'formal model' for Data Life Cycle, based on Petri Net, that allows to describe and expose data life cycle across heterogeneous systems and infrastructures. * a 'programming model' allows code execution at each stage of the data life cycle: routines provided by programmers are executed when a set of events (creation, replication, transfer, deletion) happen to any data.
Active Data: Managing Data-Life Cycle on Heterogeneous Systems and Infrastruc...
Active Data: Managing Data-Life Cycle on Heterogeneous Systems and Infrastruc...
Gilles Fedak
MOCHA Challenge was hosted by European Semantic Web Conference ESWC, 3-7 June 2018, held in Heraklion, Crete, Greece (Aldemar Knossos Royal & Royal Villa). This work was supported by grants from the EU H2020 Framework Programme provided for the project HOBBIT (GA no. 688227).
MOCHA 2018 Challenge @ ESWC2018
MOCHA 2018 Challenge @ ESWC2018
Holistic Benchmarking of Big Linked Data
A presentation on the SageCite project given at the JISC MRD International Workshop in March 2011. Describes the application domain and citation challenges in SageCite.
Mduke sagecite-jisc-march11
Mduke sagecite-jisc-march11
monicaduke
RDA (Research Data Alliance) 11, poster session, at Berlin, 2018/03/21-23
Making data typing efforts or automatically detecting data types for automat...
Making data typing efforts or automatically detecting data types for automat...
National Institute of Informatics
Rachael LammeyCrossref Mary Hirsch DataCite The underlying data created and/or reused and remixed for research is becoming as crucial as the resulting text-based output. This is your opportunity to dig into the what, the why, and the how of data publication, data citation, and data sharing. Workshop hosts will cover this topic from a range of perspectives. Let’s review the best practices and case studies in data citation and data publishing, add to our collective understanding of why this is so important, and contribute to the next steps in building solutions to improving infrastructure for research data
Data, data, everywhere? Not nearly enough!
Data, data, everywhere? Not nearly enough!
UKSG: connecting the knowledge community
Presented at 11th IDCC conference in Amsterdam on Feb 24, 2016.
Dataverse: Helping Researchers Publish Their Data Through Automation