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Open Data from Earth Observation: from Big Data to Linked Open Data, through INSPIRE

机译：地球观测的开放数据：通过INSPIRE从大数据到链接的开放数据

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The increasing availability of Earth Observation and geographic data implies great opportunities for those capable to efficiently address the problems arising from the management of this huge amount of data. An efficient management of these data means to respond to the paradigm of the 4 V that usually applies to the problem of the Big Data: Volume - the sheer size of the “data at rest”, Velocity - the speed of new data arriving, Variety - the different manifold, and Veracity - trustworthiness and issues of provenance. The problem of Big Data is not only in the geospatial realm of Earth observation data, but in general in all the location-based data which basically are the main contributors to the deluge of big data. In addition to the need of managing (store, search & find when needed) these data efficiently, the problem arises from the analysis of these data. They need to be quickly processed in order to quickly extract the information content, then they must be analysed in conjunction with other data sources in order to express their real value in the construction of new knowledge. These processes are hastened by the advent of an increasing machine-to-machine communication. The automation of the data analysis requires standardized and linked data so that they can be processed by machines without human intervention. The problem with the standardization of geospatial data is solved by simply observing not only the best practices shared at European level, but mainly the regulatory scenario dictated by the INSPIRE Directive . The publication of spatial data as Linked Open Data may then leverage the reuse of common ontologies and vocabularies that allow the connection of geospatial data with other heterogeneous information. This way new scenarios and business opportunities may arise, as in the case of the real estate market that is mentioned in this article. This contribution aims to identify some business opportunities, related to Linked Open Data and arising from the imminent availability of the Sentinel satellite data, with the European program Copernicus, for companies operating in the so-called downstream services of Earth observation. Citation Zotti, M. & La Mantia, C. (2014). Open Data from Earth Observation: from Big Data to Linked Open Data, through INSPIRE. Journal of e-Learning and Knowledge Society, 10 (2),. Italian e-Learning Association. ? 2014 SIEL.
机译：对地观测和地理数据的可用性不断提高，对于那些能够有效解决因管理大量数据而引起的问题的人们来说，这是一个巨大的机会。对这些数据的有效管理意味着应对通常适用于大数据问题的4 V范式：体积-“静止数据”的绝对大小，速度-新数据到达的速度，种类-不同的多样性和真实性-可信度和出处问题。大数据的问题不仅存在于地球观测数据的地理空间领域，而且总的来说，在所有基于位置的数据中，这些基本上是造成大数据泛滥的主要原因。除了需要有效地管理（在需要时存储，搜索和查找）这些数据之外，问题还来自对这些数据的分析。为了快速提取信息内容，需要对其进行快速处理，然后必须与其他数据源一起对其进行分析，以表达其在构建新知识中的实际价值。随着越来越多的机器对机器通信的出现，加快了这些过程。数据分析的自动化需要标准化和链接的数据，以便可以由机器处理它们而无需人工干预。地理空间数据标准化的问题不仅可以通过简单地观察欧洲一级共享的最佳实践来解决，而且可以主要观察INSPIRE指令所规定的监管情况。然后，将空间数据发布为“链接的开放数据”可以利用通用本体和词汇的重用，从而允许将地理空间数据与其他异构信息相连接。这样，就可能出现新的情况和商机，就像本文提到的房地产市场一样。该贡献旨在为与欧洲计划Copernicus合作的公司提供服务，这些业务机会与链接的开放数据有关，并且与Sentinel卫星数据的即将来临有关，这些业务机会是为从事所谓的地球观测下游服务的公司提供的。引用文献：Zotti，M.＆La Mantia，C.（2014）。地球观测的开放数据：通过INSPIRE从大数据到链接的开放数据。电子学习与知识社会杂志，10（2）,。意大利电子学习协会。 ？ 2014 SIEL。

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