Analysis of quality metadata in the GEOSS Clearinghouse

The Global Earth Observation System of Systems (GEOSS) Clearinghouse is part of the GEOSS Common Infrastructure (GCI) that supports the discovery of the data made available by the Group on Earth Observations (GEO) members and participant organizations in GEOSS. It also acts as a unified metadata catalogue that stores complete metadata records, not only about datasets but also for other kinds of components and services. By exploring these records, users often try to find the fit-for-use data. Quality indicators and provenance are included in the metadata and are potentially useful variables that allow users to make an informed decision avoiding to download and to assess the data themselves. However, no previous studies have been made on the completeness and correctness of the metadata records in the Clearinghouse. The objective of this paper is to analyze the data quality information distributed by the GEOSS Clearinghouse. The aim is to quantify its completeness and to provide clues on how the current status of the Clearinghouse could be improved and how useful quality aware tools could be. The methodology used in the current analysis consists in first harvesting of the Clearinghouse and then quantify the quality information found in 97203 metadata records, by using a semi-automatic approach. The results reveal that the inclusion of quality information on metadata records is not rare: 19.66% of the metadata records contain some quality element. However, this is not general enough and several aspects could be improved. For instance, 77.78% of quantitative measures lack measure units. When quality indicators are not sufficient, the lineage metadata information could be used to mitigate this situation by analysing the process steps and sources used to create a dataset. However, even though lineage is reported in 15.55% of the records, only 1.27% of the cases return a complete list of process steps with sources. This paper also provides indications on what is lacking in the current producer metadata model and, detected a gap in usage or user feedback metadata in GEOSS. Moreover, information extracted from GeoViQua interviews with users indicates that they value informal comments and user feedback on datasets as a complement of the more formal producer-oriented metadata description of the data. Although, many efforts within the scientific community and the Quality Assurance Framework for Earth Observation (QA4EO) group have been invested in describing how to parameterize data quality and uncertainty, we conclude that still extra work can be done to provide complete quality information in the metadata catalogues. In brief, since the GEOSS Clearinghouse references data from the most important agencies and research organizations, the results presented in this paper provide a perspective on how well quality is disseminated in the Earth observation community in general

Benefit of GEOSS Interoperability in Assessment of Environmental Impacts Illustrated by the Case of Photovoltaic Systems

International audienceAssessment of environmental impacts of a power system exploiting a renewable energy needs a large number of geographically-dependent data and of technological data. These data are located in various sources and available in various formats. To avoid the burden of data collection and reformatting, we exploit the interoperability capabilities set up in GEOSS and combine them with other GEOSS-compliant components proposed by projects funded by the European Commission. This is illustrated by the case of photovoltaic systems. A Web-based tool links the various sources of data and executes several models to offer various impacts factors in different areas: human health, climate change, primary energy, ecosystems

D4.1. Observation inventory requirements, database schema and queryable fields

Report on the observation inventory requirements, database schema and queryable fields to be adopted during the project. The observation inventory will be based on GCI Information, DAB, and Copernicus services catalogues

Sitting of a solar power plant: Development of Web service based on GEOSS data and guidance

International audienceRenewable energy sources such as solar and wind energy offer a large untapped potential for electricity production. The exploitation of these energies requires accurate knowledge of the resources and of their availability (in space and time) as well as accurate forecasts in the different phases of an energy system life cycle. For instance, the site selection process for development of large solar systems, such as photovoltaic on open land, require data on time-averaged values of solar irradiance from which basic economic assessments of a plant concept can be made. The paper illustrates the exploitation of Earth Observation data in this context. It describes the approach of setting-up a series of Web services that implement key features in Earth Observation data exploitation and illustrate their use through a complex application in the sitting of a solar power plant. The scenario is built on GEOSS interoperability and standard guidance

Exploring the depths of the global earth observation system of systems

Big Earth Data-Cube infrastructures are becoming more and more popular to provide Analysis Ready Data, especially for managing satellite time series. These infrastructures build on the concept of multidimensional data model (data hypercube) and are complex systems engaging different disciplines and expertise. For this reason, their interoperability capacity has become a challenge in the Global Change and Earth System science domains. To address this challenge, there is a pressing need in the community to reach a widely agreed definition of Data-Cube infrastructures and their key features. In this respect, a discussion has started recently about the definition of the possible facets characterizing a Data-Cube in the Earth Observation domain. This manuscript contributes to such debate by introducing a view-based model of Earth Data-Cube systems to design its infrastructural architecture and content schemas, with the final goal of enabling and facilitating interoperability. It introduces six modeling views, each of them is described according to: its main concerns, principal stakeholders, and possible patterns to be used. The manuscript considers the Business Intelligence experience with Data Warehouse and multidimensional "cubes" along with the more recent and analogous development in the Earth Observation domain, and puts forward a set of interoperability recommendations based on the modeling views

Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.Comment: 24 pages; 15 figure

Geospatial data quality indicators

Indicators which summarise the characteristics of spatiotemporal data coverages significantly simplify quality evaluation, decision making and justification processes by providing a number of quality cues that are easy to manage and avoiding information overflow. Criteria which are commonly prioritised in evaluating spatial data quality and assessing a dataset’s fitness for use include lineage, completeness, logical consistency, positional accuracy, temporal and attribute accuracy. However, user requirements may go far beyond these broadlyaccepted spatial quality metrics, to incorporate specific and complex factors which are less easily measured. This paper discusses the results of a study of high level user requirements in geospatial data selection and data quality evaluation. It reports on the geospatial data quality indicators which were identified as user priorities, and which can potentially be standardised to enable intercomparison of datasets against user requirements. We briefly describe the implications for tools and standards to support the communication and intercomparison of data quality, and the ways in which these can contribute to the generation of a GEO label

An integrated view of data quality in Earth observation

Data quality is a difficult notion to define precisely, and different communities have different views and understandings of the subject. This causes confusion, a lack of harmonization of data across communities and omission of vital quality information. For some existing data infrastructures, data quality standards cannot address the problem adequately and cannot fulfil all user needs or cover all concepts of data quality. In this study, we discuss some philosophical issues on data quality. We identify actual user needs on data quality, review existing standards and specifications on data quality, and propose an integrated model for data quality in the field of Earth observation (EO). We also propose a practical mechanism for applying the integrated quality information model to a large number of datasets through metadata inheritance. While our data quality management approach is in the domain of EO, we believe that the ideas and methodologies for data quality management can be applied to wider domains and disciplines to facilitate quality-enabled scientific research

Advances in Spatial Data Infrastructure, Acquisition, Analysis, Archiving and Dissemination

The authors review recent contributions to the state-of-thescience and benign proliferation of satellite remote sensing, spatial data infrastructure, near-real-time data acquisition, analysis on high performance computing platforms, sapient archiving, multi-modal dissemination and utilization for a wide array of scientific applications. The authors also address advances in Geoinformatics and its growing ubiquity, as evidenced by its inclusion as a focus area within the American Geophysical Union (AGU), European Geosciences Union (EGU), as well as by the evolution of the IEEE Geoscience and Remote Sensing Society's (GRSS) Data Archiving and Distribution Technical Committee (DAD TC)

Approach to Facilitating Geospatial Data and Metadata Publication Using a Standard Geoservice

Nowadays, the existence of metadata is one of the most important aspects of effective discovery of geospatial data published in Spatial Data Infrastructures (SDIs). However, due to lack of efficient mechanisms integrated in the data workflow, to assist users in metadata generation, a lot of low quality and outdated metadata are stored in the catalogues. This paper presents a mechanism for generating and publishing metadata through a publication service. This mechanism is provided as a web service implemented with a standard interface called a web processing service, which improves interoperability between other SDI components. This work extends previous research, in which a publication service has been designed in the framework of the European Directive Infrastructure for Spatial Information in Europe (INSPIRE) as a solution to assist users in automatically publishing geospatial data and metadata in order to improve, among other aspects, SDI maintenance and usability. Also, this work adds more extra features in order to support more geospatial formats, such as sensor data.Sergio Trilles has been funded by the postdoctoral programme Vali+d (GVA) (grant number APOSTD/2016/058). This work has been funded by the European Commission through the GEO-C project (H2020-MSCA-ITN-2014, Grant Agreement number 642332, http://www.geo-c.eu/)