@InProceedings{PletschMathKörtVelá:2016:BiOpLi,
               author = "Pletsch, Mikhaela Alo{\'{\i}}sia J{\'e}ssie Santos and Matheus, 
                         R. and K{\"o}rting, Thales Sehn and Vel{\'a}zquez, V. F.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Delft 
                         University of Technology} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade de S{\~a}o Paulo (USP)}",
                title = "Big, open and linked data as a tool to real-time and history 
                         global climate observation at monitoring center of essential 
                         climate variables",
            booktitle = "P{\^o}steres",
                 year = "2016",
         organization = "Global Climate Observation: The road to the furute",
             abstract = "Currently, 50 Essential Climate Variables (ECVs) are required to 
                         support the work of the United Nations Framework Convention on 
                         Climate Change (UNFCCC) and the Intergovernmental Panel on Climate 
                         Change (IPCC). The variables were developed according to theirs 
                         techno-economic feasibility and were divided in three main 
                         domains: 1) Atmospheric (over land, sea and ice); 2) Oceanic; 3) 
                         Terrestrial. The observations refer to physical and chemical data 
                         that require expert knowledge in their specific areas of study. 
                         Those large datasets characterizes the Big, Open and Linked Data 
                         (BOLD). It means to have simultaneously a huge quantity, 
                         diversity, variety and velocity of data collection, storage and 
                         analyze of standardized and open data format. The recent computer 
                         hardware and software features and capacity enabled to deal with 
                         BOLD of ECVs. Even considering the advances, stakeholders as 
                         scientists and governments, still face issues to analyze the BOLD 
                         of ECVs. From this puzzle, this paper aims to consider the current 
                         development challenges to improve the UNFCCC and the IPCC 
                         international public policy. As an approach to reach the objective 
                         of this paper, it was conducted a scientific and practical 
                         literature review identifying gaps on: 1) ECVs data and 
                         infrastructure; 2) integration and analysis of data; 3) 
                         Decision-making and public policies. The expected results are 
                         guidelines with a set of recommendations on each aforementioned 
                         gaps with the objective of improving the data quality and 
                         collection of ECVs, creating an Information and Communications 
                         Technology (ICT) infrastructure and architecture that support 
                         sufficient computing capacity to enable BOLD work, creating a 
                         diversified team of analysis to deal with BOLD and creating an 
                         integrated and real-time Monitoring Center of ECVs. This Center 
                         aims to enable a faster and effective international, national, 
                         regional and local data analysis and decision making that will 
                         combine the identified recommendations: i) automatized data 
                         collection from huge number of sensors on Earth (Internet of 
                         Things) - requiring the installation of sensors in several points 
                         on the planet; ii) automatized storage and access (modern open 
                         data portal) of data from sensors on the planet - requiring 
                         massive computational capacity to storage, treat and process data; 
                         iii) automatized data analysis (mathematical modeling) - requiring 
                         multidisciplinary teams that deal with data analysis and with 
                         expertise on environmental public policies; and, iv) dashboards at 
                         videowall (big screens on a wall) displaying the data analysis of 
                         real-time and history of BOLD of ECVs on a business intelligence 
                         with geographical and analytical report features.",
  conference-location = "Amsterdan",
      conference-year = "2-4 Mar.",
             language = "en",
        urlaccessdate = "27 abr. 2024"
}