big data value reference modelfrom bdva (sria 4.0) … · 12/31/2019 · big data value reference...

BIGDATAVALUEREFERENCEMODEL FROMBDVA(SRIA4.0)– WITH MACHINELEARNING/AI

[email protected]

SINTEF

BDVATF6(TechnicalPriorities)leader

Agenda

2

BDVAdrivingbig datastandardisation andinteroperability priorities: 'Outcomes 2017andupdate on ISOJTC1WG9BigDataandJTC1/SC42Artificial Intelligence(RayWalshe andAbdellatif Tuoimi)

BigDataValueReferencemodel fromBDVA(SRIA4.0)– with Machine Learning/AI (ArneJ.Berre)BigDataEurope(SimonScerri)BigDataStandardsrelated toBigDataPPPprojects:(ArneJ.Berre)BigDataPPP -LargeScale Pilots: (DataBio,TransformingTransport) (ICT-15-2017)BigDataPPP- IAProjectswith Linked Data/Graph data:(EUBusinessGraph,EWShopp,QROWD, ..AEGIS,Projectson Cross-sectorial andcross-lingual dataintegration andexperimentation (ICT-14-2017)BigDataBenchmarking – DataBench projectHOBBITBenchmarking project (GayaneSedrakyan)EO/Geo BigData typestandards(CodrinaIlie)Reporton the Trans-Atlantic EU-USSymposiumon PublicPrivatePartnerships forBigData,

November20th (RayWalshe andMelissaCragin)– on BigDataIntegrationandInteroperabilityinvarious domains SmartCities,Transportation,Health,Environment,AgriFood,Energy,Water,…

Roadmap tocoordinate EuropeanBigDataStandardisation priorities (RayWalshe /All)

04-01-18 3www.bdva.eu

TF1:Programme

TF2:Impact

TF3:Community

TF4:Communication

BDVA is taking care…of many different aspects of the big data technology

TF5:Policy&

Societal

Policy&Societal

TF6:Technical(Dr. ArneJ.Berre)

TF6-SG1:DataManagement

TF6-SG2:DataProcessingArchitectures

TF6-SG3:DataAnalytics

TF6-SG4:DataProtectionandPseudonymisation

Mechanisms

TF6-SG5:AdvancedVisualisationandUser

Experience

TF6-SG6:Standardisation

TF7:Application

TF7-SG1:EmergingApplication Areas

TF7-SG2:Telecom

TF7-SG3:Healthcare

TF7-SG4:Media

TF7-SG5:Earthobservation&geospatial

TF7-SG6:SmartManufacturing

Industry

TF8:Business

TF8-SG1:Dataentrepreneurs(SMEsandstartups)

TF8-SG2:Transformingtraditional

business (LargeEnterprise)

TF8-SG3:ObservatoryonDataBusinessModels

TF9:SkillsandEducation

TF9.SG1:Skillrequirements

fromEuropeanindustries

TF9SG2:Analysisofcurrentcurricula

related todatascience

TF9.SG3:Liaison withexisting

educationalprojects


BDVReferenceModel


BigDataValue ReferenceModel

Timeseries,IoT

GeoSpatioTemp

MediaImageAudio

TextNLP.Genom

WebGraphMeta

Structdata/BI

Standards

DataProcessingArchitecturesandWorkflowsBatch,Interactive,Streaming/Real-time

DataVisualisation andUserInteraction1D,2D,3D,4D,VR/AR

DataAnalytics Descriptive,Diagnostic,Predictive,Prescriptive

MachineLearning andAI,DeepLearning, Statistics, HYBRID ANALYTICS(Optim/Simulation)

j

DataManagementCollection,Preparation,Curation,Linking,Access,Sharing–DataMarket/DataSpaces

DBtypes:SQL,NoSQL(Document,Key-Value,Column,Array,Graph,…)

CloudandHighPerformanceComputing(HPC)

BigDataPriorityTech

Areas

Applications/Solutions:Manufacturing, Health,Energy, Transport, BioEco,Media,Telco,Finance,EO,SE,…

DataProtection,Anonymisation,…

BigdataTypes&semantics

Things/Assets,SensorsandActuators(Edge,Fog,IoT,CPS)

CommunicationandConnectivity,incl.5G

CyberSecurityandTrust

Developm

ent-EngineeringandD

evOps

Datasharingplatforms.,Industrial/Personal


Latest ISO JTC1 WG9 Big Data Reference Architecture

ApplicationProviderLayer

ProcessingLayer

PlatformLayer

ResourceLayer

Multi-layerfunctions

Integration Security&Privacy

Manage-ment

Algorithms

Visualizations

WorkFlowEngine

AccessServices

Transformations

BatchFrameworks

InteractiveFrameworks

StreamingFrameworks

RelationalStorage

DocumentStorage

Key-valuestorageGraphStorage

Wide-columnarstorage

FileSystems

MessagingFrameworks Audit

Frameworks

AuthorizationFrameworks

AuthenticationFrameworks

MonitoringFrameworks

Provisioning/ConfigurationFrameworks

PackageManagementFrameworks

ResourceManagementFrameworks

IngestServices

AnonimizationFrameworks

StateManagementFrameworks

DataLifeCycleManagement

DP-AP

AP-PR

PR-PL

DC-AP

PL-RL

IN-FL

SP-FL

MG-FL

IN-SP SP-MG

IN-MG

MakeDataAvailable

Role:DataProvider Role:BigDataConsumer

ReceiveDataOutput

ResourceAbstractionandControl

PhysicalResources

Columnbasedstorage

BigDataStandardsWorkshopandISOJTC1WG9meeting,Dublin,15-22August2017(hosted byRayWalshe)


Timeseries

,IoT

GeoSpatioTemp

MediaImageAudio

TextNLP.Genom

WebGraphMeta

Structdata/BI

Standards

DataProcessingArchitecturesandWorkflowsBatch, Interactive,Streaming/Real-time

DataVisualisationandUserInteraction1D,2D,3D,4D,VR/AR

DataAnalyticsDescriptive,Diagnostic,Predictive,PrescriptiveMachine Learning andAI, Deep Learning, Statistics,

j

DataManagementCollection, Preparation, Curation,Linking,Access– DataMarket/DataSpace

DBtypes:SQL,NoSQL(Document,Key-Value,Coloum,Array,Graph, …)


BigDataPriorityTech

Areas

Applications/Solutions:Manufacturing,Health,Energy,Transport,BioEco,Media,Telco,Finance,EO,SE

DataProtection,Anonymisation, …


Things/Assets,SensorsandActuators(Edge,Fog,IoT,CPS)


CyberSecurity,Risk,Trust,DataPrivacy

Developm

ent-EngineeringandD

evOps

Marketplaces,Ecosystem

s,andInnovationsupport

ApplicationProviderLayer

ProcessingLayer

PlatformLayer

ResourceLayer

Multi-layerfunctions

Integration Security&Privacy

Manage-ment

Algorithms

Visualizations

WorkFlowEngine

AccessServices

Transformations

BatchFrameworks

InteractiveFrameworks

StreamingFrameworks

RelationalStorage

DocumentStorage

Key-valuestorageGraphStorage

Wide-columnarstorage

FileSystems

MessagingFrameworks Audit

Frameworks

AuthorizationFrameworks

AuthenticationFrameworks

MonitoringFrameworks

Provisioning/ConfigurationFrameworks

PackageManagementFrameworks

ResourceManagementFrameworks

IngestServices

AnonimizationFrameworks

StateManagementFrameworks

DataLifeCycleManagement

DP-AP

AP-PR

PR-PL

DC-AP

PL-RL

IN-FL

SP-FL

MG-FL

IN-SP SP-MG

IN-MG

MakeDataAvailable

Role:DataProvider Role:BigDataConsumer

ReceiveDataOutput

ResourceAbstractionandControl

PhysicalResources

Columnbasedstorage

BDVA Reference Model vs ISO WG9 Big Data Reference ArchitectureUpdates/changes fromthe BDVAReferenceModelwill besubmitted into the ISOprocess

July 4th, 2017EXDCI WP28

HPC

HPC, Big Data &Deep Learning Stacks

Big Data Deep Learning

Infiniband & OPA fabrics

Storage & I/O nodes, NAS

GP* CPU nodes, GPUs, FPGAs

Linux OS Variant

Containers

PFS(Lustre etc.)

MPI OpenMP, threading

Accelerator APIs

Numerical libraries

Performance & debugging

Domain-specific libraries

Conventional compiled languages (C, C++, FORTRAN)

Scripting (Python, …)

IDEs & Frameworks(PETSc, …)

Compiled in-house, commercial & OSS applications

Cluster management(OpenHPC)

Batch scheduling (SLURM …)

Linux OS Variant (some Windows)

Ethernet fabrics

Local storage

GP* CPU hyper-convergent nodes

Virtualization: hypervisor or containers (Dockers, Kubernetes, …)

VMM and container management

I/O libraries(HDF5, …)

Orchestration and RMS

Cloud service I/F Storage systems(DFS, Key/value, …)

Map-Reduce Processing(Hadoop, Spark)

Data stream processing (Storm, Spark, …)

Distributed coordination (Zookeeper, …)

Workflows combining many application elements

Compiled languages (C++)

Traditional ML(Mahout)

Scripting & WF languages (R, Python, Java, Scala, …)

Linux OS Variant (Windows?)

Ethernet‡ GP* CPU + GPU/FPGA, TPU

Local storage or NAS/SAN

Virtualization: hypervisor or containers (Dockers, Kubernetes, …)

VMM and container management

Orchestration and RMS

Neural network frameworks(Caffe, Torch, Theano, Tensorflow … )

Load distribution layer

Scripting languages (Python, …)

Inference engines(low precision)

Defined and instantiated/trained neural networks

Can be part of

Applications

Middleware& Mgmt.

System SW

Hardware

* GP: general purpose

User-space fabric access

Direct accelerator use

Numerical libraries (dense LA) Accelerator APIs

Cloud service I/F Storage systems(DFS, Key/value, …)

Red boxes: data components ‡ need for faster fabrics for training scale-out

Exclusive use of partitions


Timeseries,IoT

StructuredData/

BusinessIntelligence

GeoSpatial

Temporal

MediaImageAudio

Text,Language,Genomics

WebGraphMeta

DataProtection

DataProcessingArchitectures

DataVisualisation andUserInteraction

DataAnalytics - w/AI Cognition – learning,reasoning,creativity

DataManagement


Things/Assets,SensorsandActuators(Edge,IoT,CPS)


CyberSecurityandTrust

Datasharingplatforms.,Industrial/Personal

CoreBDVA

Key

InCollaboration

DataTypes

Standards

Development-

EngineeringandDevOps

Perception andControl

BDVReferenceModelwith AI/MachineIntelligence areashighlighted

FactsRules

Sensor Image NLP KnowledgeGraphSpeech

Cognition ->Recommendations ->Decisions

Spatial

BDVA- Analytics– Taxonomy/Classifications• Analytictypes– withApplied/Industrial/CommercialAnalytictypes(4+2groups):• Descriptive(past)(Historicalanalysis,…)• Diagnostic(now)(Anomalydetection,Frauddetection,ConditionMonitoring• Predictive(future)(Predictivemaintenance,Forecasting,…• Prescriptive(Recommendationsystems,Qualityimprovement,..• Hybridanalytics(CombiningData-DrivenanalyticswithFirst-OrderModeling–

Simulation/Optimisationetc.)- Extremeanalytics(IntegrationwithHPC,scientificcomputingforextremeperformance,..)

• Machinelearning,AI,Statistics,Algorithms/DeepLearning/DataMining/DataScience(3groups):• Supervisedlearning(Classification,Regression,AI- DeepLearning(NeuralNetworks),..• Unsupervisedlearning(Clustering,Dimensionreduction(PrincipalComponentAnalysis,

MultidimensionalScaling),Associationrules,Causalitydetection,On-linelearning(streaming)• Reinforcementlearning(Collaborativefiltering,…)• Bigdatatypeanalytics(6groups+1– inputtoabovemachinelearningandadvancedanalytics):• Structureddata(Basicmin/max/sum/averagequeries,BasicStatistics,Correlations)• TimeSeries/Sensor/IOT/Stream• Media/Image/Video/Audio(Imagerecognition,speechrecognition,…)• (Geo)Spatial(Spatio temporalanalysis,geometry/topology...)• Text/NLP(Text/Speechunderstanding/cognition,translation,Semanticsearch,Sentiment

analysis)• Graph/Network/Web/(Metadata)(LinkedData–Graphanalytics,…)• Ontologies/Taxonomies/VocabulariesforSemanticInteroperability(forallbigdatatypesand

forvariousdomains/sectors/industries)

04-01-18 11www.bdva.euFromhttps://machinelearningmastery.com/

04-01-18 12www.bdva.eu12


ACMComputingclassificationsystemhttps://www.acm.org/publications/class-2012

from2012…


Therecent AIsummerisbased onthe use of Machinelearningcombined with (Big)Data


Agenda

BDVAdrivingbig datastandardisation andinteroperability priorities: 'Outcomes 2017andupdate on ISOJTC1WG9BigDataandJTC1/SC42Artificial Intelligence(RayWalshe andAbdellatif Tuoimi)

BigDataValueReferencemodel fromBDVA(SRIA4.0)(ArneJ.Berre)BigDataEurope(SimonScerri)BigDataStandardsrelated toBigDataPPPprojects:(ArneJ.Berre)BigDataPPP -LargeScale Pilots: (DataBio,TransformingTransport) (ICT-15-2017)BigDataPPP- IAProjectswith Linked Data/Graph data:(EUBusinessGraph,EWShopp,QROWD, ..AEGIS,Projectson Cross-sectorial andcross-lingual dataintegration andexperimentation (ICT-14-2017)BigDataBenchmarking – DataBench projectHOBBITBenchmarking project (GayaneSedrakyan)EO/Geo BigData typestandards(CodrinaIlie)Reporton the Trans-Atlantic EU-USSymposiumon PublicPrivatePartnerships forBigData,

November20th (RayWalshe andMelissaCragin)– on BigDataIntegrationandInteroperabilityinvarious domains SmartCities,Transportation,Health,Environment,AgriFood,Energy,Water,…

Roadmap tocoordinate EuropeanBigDataStandardisation priorities (RayWalshe /All)

BDVREFERENCEMODEL – FORCURRENT PROJECTS– INCL.DATABIO ANDTRANSFORMINGTRANSPORT

[email protected]

SINTEF

BDVATF6(TechnicalPriorities)leader

21www.bdva.eu

BDV PPP projects (H2020-ICT-2016-2017)

22www.bdva.eu

Enabling theEuropeanBusinessGraphforInnovative DataProductsandServices

SupportingEventandWeather-basedDataAnalyticsandMarketing alongthe

Shopper Journey

UnderstandingEurope’sFashionDataUniverse

AdvancedBigDataValue ChainforPublicSafety andPersonalSecurity

Accelerating DatatoMarket

BecauseBigDataIntegration isHumanlyPossible

Exploiting OceansofDataforMaritime Applications

ScalableLinkingandIntegration ofBigPOIdata

Cross-sectorialandcross-lingualdataintegrationandexperimentation (ICT-14)

http://eubusinessgraph.eu/

http://www.ew-shopp.eu/

https://fashionbrain-project.eu/

http://www.aegis-bigdata.eu/

https://datapitch.eu/

http://qrowd-project.eu/

http://www.bigdataocean.eu/site/

http://www.slipo.eu/

Support,industrialskills,benchmarkingandevaluation(ICT-17)

www.big-data-value.eu

Support theimplementation oftheBigDataValuePPP

23www.bdva.eu

MyHealth MyData

Scalable Oblivious Data Analytics

Ethical andSocietal ImplicationsofData Sciences

Scalable Policy-awarE linkeddataarchitecture forprivacy,transparency

and compliance

Privacy-preserving bigdatatechnologies (ICT-18)

Data-driven bioeconomy

TransformingTransport

Largescalepilotactionsinsectorsbestbenefitting fromdata-driven

innovation (ICT-15)

Knowledge Complexity

EnablingresponsibleICT-relatedresearch andinnovation(ICT-35)

https://www.databio.eu/en/

http://www.transformingtransport.eu/

https://kplex-project.com/

http://www.myhealthmydata.eu/

https://www.soda-project.eu/

http://www.e-sides.eu/

https://www.specialprivacy.eu/

24www.bdva.eu

REQUESTED INPUT FROM ALL OF THE BIGDATA PPP PROJECTS (THROUGH BDV)

- Use casetemplate – filled in– forallpilots/use cases- BDVReferenceModelmapping – fortechnical components andstandardsused/proposed- Inputforproject businessresults evaluation – forBusinessKPI- Projectneeds/opportunities/requirements forbusinessandtechnology benchmarks- Inputfortechnology results evaluation – forTechnologyKPIs

25www.bdva.eu

ISO JTC1 WG9 use case template (1/2)

26www.bdva.eu

ISO JTC1 WG9 use case template (1/2)

27www.bdva.eu

DataProtection&

CyberSecurity

Engineering&DevOps Standards



DataAnalytics

DataManagement

Batch Interactive Streaming/Real-time Other

Descriptive Predictive Prescriptive

1D 2D 3D VR/AR

Collection/Ingestion

Preparation/Curation AccessLinking/

Integration

1+1D(time) 2+1D(time) 3+1D(time)

Created by your project Used by your project

Use cases,Pilots,Applications,Sectors,Domains,Solutions,….

Datasources andBigDatatypes

GraphNetworkMetadata

Text/Genome

MediaImage

StructData,

BI

IoTSensor

SpatioTemp

Diagnostic

SQL File-store

NoSQLKey-value

NoSQLDocumentStore

NoSQLColumn

NoSQLGraph

other

Classification Clustering Regression DeepLearning(ANN,CNN,RNN)

VariousAIMethods

OptimisationSimulation

other

other

Other

Template forshowing technology areas– with project use andcreation of technologies(Extended BDVAReferenceModel)

28www.bdva.eu

DataProtection&

CyberSecurity




DataAnalytics

DataManagement



1D 2D 3D VR/AR



Integration


Created/Modified by DataBio Used by DataBio fishery pilot C2

PilotC2– T3.4.2Smallpelagicmarket predictions andtraceability

Datasources andBigDatatypes


Text/Genome

MediaImage

StructData,

BI

IoTSensor

SpatioTemp

Diagnostic

SQL File-store

NoSQLKey-value

NoSQLDocumentStore

NoSQLColumn

NoSQLGraph

other


VariousAIMethods


other

other

Other

Extended BDVAReferenceModel- forshowing technology areas– with project use

1. Ratatosk (C17.01)forloggingdatafromvessel2. Hydroacoustic/sonarandweather data3. Sonar,radarandEOimages(C07.01-4)4. Pelagic auction dataandcatch reports5. Worldbankmarket data(JSON)6. GeoJSON datastore– CouchDB?7. Map feature server– WMS– GeoServer,

GeoRocket orother (C04.01-4)?8. Stim(C17.02)fordatavalidation,and

decimation/interpolation9. SWcomponent gathering datafrom4and510. Batchprocessing of historic data- Hadoop?11. Interactiveanditerativedevelopment12. Onvessel processing,ref 1,2,3,datafiltering

forfish observations.Imageclassification(C29.01,C31.01orother?)

13. Datacollation fordifferentdatasources ofhigh variety insamplingfrequency(spatial/time)andformats– FromDataBioplatform

14. MLmethods forpredictivepricemodels(C34.01,C16.02,C34.01orother)

15. Correllation/Covariance analysis16. MLoptimization of factorsaffecting fishery

revenue17. Plotof price models/time–R,matlab or

octave?18. Interactivedisplayspatio-temporalcatch and

market information- CESIUM)and/orRasdaman (C04.01,C05.01)?

19. Gluster20. Docker forsetup/job/servicerun21. DCOSw/MESOS

41 2 35

5 647

681 9

10 11 12 13

14

14

15

16

17 18

19 20 21

This document is part of a project that has received funding from the European Union’s Horizon 2020 programme under grant agreement No 732064. It is the property of the DataBio consortium and shall not be distributed or reproduced without the formal approval of the DataBio Management Committee. See www.databio.eu.

} Horizon 2020 (ICT call, Big Data)

} 48 partners from 16 countries

} Funded between 2017 and 2020 (36 months)

} Overall budget 16 mil. €(EU contribution 13 mil. €)

ThisdocumentispartofaprojectthathasreceivedfundingfromtheEuropeanUnion’sHorizon2020researchandinnovationprogrammeunderagreementNo732064.ItisthepropertyoftheDataBioconsortiumandshallnotbedistributedorreproducedwithouttheformalapprovaloftheDataBioManagementCommittee.Findusatwww.databio.eu.

30

DataBioproject info

Projecttitle:Data-DrivenBioeconomyProjecttype:H2020 InnovationAction,intopicICT-15-2016-2017 - BigDataPPP:LargeScalePilotactionsinsectorsbestbenefittingfromdata-driveninnovationDuration:1Jan.2017– 31Dec.2019(36months)Totalbudget:16,2M€Partners:48partners,70+associatedpartners


31

Projectobjectives

• Industrialdomain:bioeconomy• Improveutilizationofbestpossiblerawmaterialsfromagriculture,forestryandfishery

• Improveproductionoffood,energyandbiomaterials• Theopportunity:bioeconomycanbenefitfromBigData

• Farmmachines,fishingvessels,forestrymachineryandremoteandproximalsensorscollectlargequantitiesofdata

• Bigdatatechnologiesprocessdataandcreateknowledgethatincreasesperformanceandproductivityinasustainableway

• Projectobjectives• BuildaversatileDataBioplatformsuitablefordifferentindustriesanduserprofiles• EnsureeffectiveutilizationofBigDatadatasetsandtechnologiesinbioeconomy• OpenthepossibilitiesforEuropeanICTandEarthObservationindustriesinthebioeconomymarket


32

Combiningdriversandassets

Sector Variety Volume(TB)

Velocity(TB/Year)

Agriculture 8sources, 4types 53 197

Forestry8sources, 7types 11,39 12,12

Aerial/UAV 100GB/h

Fishery 20sources, 13types 8,82 6,27

26pilots, in3sectors x3thematicgroups


33

1. HsLayerNG3D-OLU• IntegratesCesium3D

2. HsLayerNG• JSwebmappinglibrary

3. Metaphactory• graphdatavisualization

4. D2RQ• transformsrelationalDBtovirtualRDFgraphs

5. Virtuoso• tostorethesemanticdatasets

6. Silk• fordiscoveringlinks

7. Sparql• forqueringsemanticdata

8. Farmingdatamodelandontology9. Datasets:

a. Yieldpotentialb. OpenLandUsec. SmartPOId. TerrasGauda

DataProtection&

CyberSecurity




DataAnalytics

DataManagement



1D 2D 3D VR/AR



Integration


Integrationofgeographicandlinkeddataintoa3Dwebenvironment

DatasourcesandBigDatatypes


Text/Genome

MediaImage

StructData,

BI

IoTSensor

SpatioTemp

Diagnostic

SQL File-store

NoSQLKey-value

NoSQLDocumentStore

NoSQLColumn

NoSQLGraph

other


VariousAIMethods


other

other

Other

8

76

5

4

31

2 2

Componentsusedin1(of26pilots)

D2RQ

9


34

(Existing) EOInfrastructure e.g.ESA,

VITO,e-GEOS,…

EODataManagement

EODataProcessors

EO“datapipe”

35www.bdva.eu

36www.bdva.eu

37www.bdva.eu

Example from TT – Transforming Transport (EU project)

38www.bdva.eu

Big Data PPP - IA Projects with Linked Data/Graph data: (EUBusinessGraph, EWShopp, QROWD, ..AEGIS, Projects on Cross-sectorial and cross-lingual data integration and

experimentation (ICT-14-2017)

Ref.presentations of these project inthe PPPproject session on November22nd-

Allprojects are using various aspects of linked datatechnologies (W3C++)

Suitable targetforbenchmarkingingeneralandlinked databenchmarking(HOBBIT)inparticular.

39www.bdva.eu

BENCHMARKING (REQUESTED INPUTFROM BIG DATA PPP PROJECTS)- Use casetemplate – filled in– forallpilots/use cases- BDVReferenceModelmapping – fortechnical components andstandardsused/proposed- Inputforproject businessresults evaluation – forBusinessKPI- Projectneeds/opportunities/requirements forbusinessandtechnology benchmarks- Inputfortechnology results evaluation andbenchmarking– forTechnologyKPIs

40www.bdva.eu

41www.bdva.eu

42www.bdva.eu

43www.bdva.eu

44www.bdva.eu

DataPrivacy

Timeseries,IoT

GeoSpatioTemp

MediaImageAudio

TextNLP

WebGraph

BDVAReferenceModel

Structdata/BI



DataAnalytics

DataManagement

Infrastructure

BigDataPriorityTech

Areas

Sectors:Manufacturing, Health,Energy,Media,Telco,Finance,EO,..


BigBench

Hobbit-IV

BigDataBench

ALOJA

TPC

Hobbit-II

Hobbit-II

Hobbit-I+III

LDBC-3Graphalytics

LDBC-2SocialNet

LDBC-1SemanticPub

BigBench

BigDataBench

BigBench2.0

YStreamB

DeepMark DeepBenchRIoTBench

BigBench2.0

Horizontalbenchmarks

Verticalbenchmarks

SenseMark

ABenchSparkBench

YCSBSparkBench

StreamBench

45www.bdva.eu

46www.bdva.eu

big data value reference modelfrom bdva (sria 4.0) … · 12/31/2019 · big data value reference...

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