Big Data challenges in building the Global Earth Observation System of Systems

There are many expectations and concerns about Big Data in the sector of Earth Observation. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This manuscript explores the impact of Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on the Global Earth Observation System of Systems (GEOSS) and particularly its common digital infrastructure (i.e. the GEOSS Common Infrastructure). GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the EO realm. The manuscript introduces and discusses the general GEOSS strategies to address Big Data challenges, focusing on the cloud-based discovery and access solutions. A final section reports the results of the scalability and flexibility performance tests. Display Omitted Big Data challenges for the Global Earth Observation System of Systems (GEOSS).GEOSS Common Infrastructure (GCI) solutions to address Big Data challenges.The role played by the GEO Brokering framework (GEO DAB).GEO DAB cloud configuration.Performance Tests.

[1]  Rinkle Rani,et al.  Modeling and querying data in NoSQL databases , 2013, 2013 IEEE International Conference on Big Data.

[2]  Florin Radulescu,et al.  MongoDB vs Oracle -- Database Comparison , 2012, 2012 Third International Conference on Emerging Intelligent Data and Web Technologies.

[3]  Stefano Nativi,et al.  The Brokering Approach for Multidisciplinary Interoperability: A Position Paper , 2012, Int. J. Spatial Data Infrastructures Res..

[4]  Stefano Nativi,et al.  Improve the ranking algorithm of the GEO Discovery and Access Broker through resource accessibility assessment , 2013 .

[5]  Andre B. Bondi,et al.  Characteristics of scalability and their impact on performance , 2000, WOSP '00.

[6]  Guan Le,et al.  Survey on NoSQL database , 2011, 2011 6th International Conference on Pervasive Computing and Applications.

[7]  Stefano Nativi,et al.  Integrative Research: The EuroGEOSS Experience , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[8]  Mohammad Jamshidi,et al.  System of systems engineering : innovations for the 21st century , 2008 .

[9]  Stefano Nativi,et al.  Discovery, Mediation, and Access Services for Earth Observation Data , 2009, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[10]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[11]  Paolo Mazzetti,et al.  GI-Cat: a Web service for dataset cataloguing based on ISO 19115 , 2004 .

[12]  Stefano Nativi,et al.  Earth Science Infrastructures Interoperability: The Brokering Approach , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[13]  Ben Domenico,et al.  Thematic Real-time Environmental Distributed Data Services (THREDDS): Incorporating Interactive Analysis Tools into NSDL , 2002, J. Digit. Inf..

[14]  Roberto Roncella,et al.  Towards a Brokering Framework for Business Process Execution , 2013 .

[15]  Tony Hey,et al.  The Fourth Paradigm: Data-Intensive Scientific Discovery , 2009 .

[16]  Andrew P. Sage,et al.  A Case for an International Consortium on System-of-Systems Engineering , 2007, IEEE Systems Journal.

[17]  Susan Stitt,et al.  Terrestrial essential climate variables (ECVs) at a glance , 2011 .

[18]  Wilson C. Hsieh,et al.  Bigtable: A Distributed Storage System for Structured Data , 2006, TOCS.

[19]  Stefano Nativi,et al.  Methodologies for Augmented Discovery of Geospatial Resources , 2012 .

[20]  Wumuti Naheman,et al.  Review of NoSQL databases and performance testing on HBase , 2013, Proceedings 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC).

[21]  Stefano Nativi,et al.  GI-axe: an access broker framework for the geosciences , 2012 .

[22]  George Rebovich Enterprise system of systems , 2008 .

[23]  Stefano Nativi,et al.  Environmental model access and interoperability: The GEO Model Web initiative , 2013, Environ. Model. Softw..

[24]  Stefano Nativi,et al.  Brokering Services to Evaluate, Visualize, and Analyze Terrestrial Biosphere Model Output and Observations , 2013 .

[25]  N. Pettorelli,et al.  Essential Biodiversity Variables , 2013, Science.

[26]  Ben Domenico,et al.  Unidata’s Common Data Model mapping to the ISO 19123 Data Model , 2008, Earth Sci. Informatics.

[27]  Ulf Leser,et al.  Federated Information Systems: Concepts, Terminology and Architectures , 2007 .

[28]  Ben Domenico,et al.  The Brokering Approach for Earth Science Cyberinfrastructure , 2011 .

[29]  Vijay V. Raghavan,et al.  NoSQL Systems for Big Data Management , 2014, 2014 IEEE World Congress on Services.