- Understand and being able to identify the objectives of SDI’s, the different components of an SDI and the different types of SDI in place;
- Gaining insight in the geospatial standardisation process, the most important standardisation bodies and the different types of geospatial standards;
- Being able to identify existing Best Practice SDI implementations in the world.
This module is to introduce the users perspective of SDI’s. How can users of geographic information find the information/data sets required for a particular application? SDI and other information infrastructures have defined the idea of single access points making use of the basic principles of the WWW to search for data and services, and to obtain information about the data and services (metadata) in order to understand the data (e.g. where does the data come from, what are the conditions or limitations of use, what is the area covered, the validity date, etc.). Users need to evaluate whether data and services are fit for (a particular) use. Metadata are stored in metadata catalogues and can be accessed through the catalogues services which are built on top of it. Good geoportals are simple to use and provide not only data about the data (and services) but also a mechanism to visualize and browse the spatial data to find more information about its content. Users should also be able to use the data in other applications by downloading the data on the own computer or by opening the data (layer(s)) in desktop applications. This is a module with a series of exercises and can be extended with group work.
This module deals with the representation of formalized spatial and spatio-temporal reality through data models and the translation of these data models into data structures that are capable of being implemented within a computational environment (i.e., within a GIS or more likely within a spatial database). Data modelling is a crucial topic as it defines the content of a spatial database and the usefulness of this content (data) for certain applications. Data Modelling is performed using system neutral conceptual modelling languages like UML. These conceptual models have to be transferred to logical models (i.e. tables of a database). Data is stored in spatial databases which are normally organized in an object-relational way. For certain types of data specific databases are used, like triple stores, NoSQL DBs, Array DBs etc. For data modelling, quite a number of ISO standards are available for deriving the conceptual model as well as for rules for application schemas, spatial schemas, temporal schemas, quality principles, encoding, 3D modelling (CityGML) etc. Data models provide the means for formalizing the spatio-temporal conceptualizations. Data models also form the basis for using data together, e.g. in a cross-border context. Therefore they should be interoperable (semantically speaking). Data harmonization might be necessary by transforming data from one data model to a standard specification (following another but related data model), e.g. such as in INSPIRE. Extract Transform Load (ETL) processes might be required for doing so based on syntactic and semantic transformation rules.
This module brings insight into the architecture, the technological solutions and standards used to access geospatial data through the web. The major architecture patterns are explained and the Service Oriented Architecture (SOA) is explained in more detail. Different types of web services exist, including SOAP and REST(full) services. In the most simplistic way, a web service may be defined as “a Web-accessible program code which performs a task of either processing or serving some data. Although there are many other definitions in the related literature, the one in W3C (2004) seems to be quite complete and referring to also lately popular REST style Web services. It states that “…We can identify two major classes of Web services: REST-compliant Web services, in which the primary purpose of the service is to manipulate XML representations of Web resources using a uniform set of "stateless" operations; and arbitrary Web services, in which the service may expose an arbitrary set of operations. The Open Geospatial Consortium has developed a whole suite of web services to operate on geospatial data. The most prominent, such as WMS/WMTS and WFS are explained in detail and exercises are available for setting-up such services. The Catalogue Web Service (CSW) explained from the user perspective in module “SDI at work” will be explained in detail as well and exercises are available for learning how to set-up catalogues and CSW. Each service has specific capabilities and possible operations on geospatial data. An overview of other OGC web services is provided as well: e.g. Web Processing Services (WPS), Web Coverage Services (WCS) and Sensor Observation Services (SOS). Web services can be ‘combined’ by linking them to each other, by chaining them or through orchestration.
This module focusses on different aspects of ‘quality’ related to SDI (components). On the one hand, it provides insight in Quality Assurance issues and the Quality Control process that should be put in place to assess the technological components of an SDI: the metadata, data and web services. High-quality metadata are key for a good functioning SDI since it provides the first information about the data and services available, including information about their quality and conformity. The spatial datasets in an SDI should be harmonized in order to use them in a cross-border and cross-disciplinary context. QA of spatial data in SDI focus rather on whether the data conforms to agreed specifications. This type of quality control is complementary (but does not replace) QA/QC of data production and individual data products. Data quality is the degree of data usability in relation to a given objective and a particular application. The expectations for data vary between different applications. The key criteria in data quality are the amount of uncertainty in data as compared to the acceptable level of uncertainty. Appropriate metadata is inevitable for these judgements. Aspects of data quality include geometric and thematic accuracy, (in)consistencies, resolution, precision, usability and others. Assurance of data quality may be improved by following proper standards and SDI regulations for data collection and management. A system of basic data quality measures for the geospatial domain in the EN ISO 19157:2013 standard. Also for geospatial web services, quality and experience of usage are of utmost importance: service should be always available, perform well, even when used by many users at the same time. Quality aspects of an SDI also relate to how well the coordination and collaboration is set-up, and whether the SDI involves all relevant stakeholders and data/service providers, etc. From that perspective, SDI can be assessed and benchmarked, both from the technological and non-technological point of view.
This module is digging deeper into the non-technical aspects of SDI’s and how they are currently evolving. The module consists of a series of broader topics that can be developed as full modules themselves. This can especially be done when non-technical faculties are involved (law, social science). It is expected however that these topics will be covered together as part of an existing course in the form of an overview. One of the key aspects that are covered is how geospatial information and technology can be used to support decision making and e-Government processes in particular. SDI’s can be and are used by private companies, but governments are using them mainly in e-Government processes to support G2C, G2B and G2G interactions, usually by providing location enabled e-Services (applications). A work or business process can be defined as a succession of structured and interconnected activities across time and space which, starting from one or more identifiable inputs, result in one or a set of defined outputs in the form of products or services. Business (work) processes can be modelled and we can identify where and how geospatial and related data can be used to support them. Typical work processes such as ‘obtaining a building permit’, ‘evaluation of soil suitability’, ‘flood risk mapping’, etc., are discussed and examples are given from different countries in Europe on how spatial data help to solve questions/problems. A series of ongoing and upcoming developments are discussed which influence SDI implementation and how they can evolve over time: the protection of sensitive information while preserving data sharing (GDPR Directive); the handling of large amounts of (open) data; the involvement of citizens in collecting, assessing and improving geospatial information (crow sourcing); legislation that has an influence or is related to geospatial (PSI, Aarhus …), etc. The topics are well suited for developing group work.
This module, similar to the module “Non-technological Developments”, provides an overview of the main technological trends in the geospatial field or trends that influence the geospatial field. As is the case for “Non-technological developments”, the number of topics is vast, so the module aims to provide an insight/overview, rather than an in-depth elaboration of each of the topics (they can be developed as modules on their own if needed). The most important developments and trends are covered. One of the key topics is how spatial data are published and used on the web. The traditional way of searching for spatial data is based on the publish-find-bind paradigm. Currently, developments use semantic web approaches based on Linked Data technology to enhance the linking and integration of disparate web sources. Currently, more and more geospatial API’s are being developed to allow developers to build applications on top of SDI components. Another major field of development related to the shift from 2D geospatial data to 3D and even 4D data (including the time aspect). In that context, there is more and more demand to integrate traditional GIS with BIM models used to design and manage information on buildings. These developments also include Indoor Positioning. Collection of this type of detailed data, e.g. in the form of point clouds, is possible due to the development of more advanced UAVs and other technologies to gather information about our environment (which is by default 3D/4D) such as image-based mobile mapping. Other topics that might be covered are: Internet of Things and Sensor Web Enablement; Modelling, simulation and prediction and GI; big data analytics and artificial intelligence and the technical aspects of crowdsourcing. This module is conceived as a dynamic repository and choices of topics can be influenced by the specific interests of the faculty that includes them.
This module consists of several sub-modules for different fields of application. They are not described separately, but a canvas is given of what each of them can contain with some examples for particular areas. Thematic fields can be very diverse of which some are very important for the Western-Balkan region and the faculties active in the BESTSDI consortium: water and soils; geology and mining; nature and forestry; urban and spatial planning; agriculture; ... Each of the thematic fields is covered by dedicated European and national legislation in which reference is made to (administrative) work processes and (spatial) data collection: e.g. the Water Framework Directive (WFD) and the Soil Thematic Strategy. Moreover, in many application domains specific initiatives are taken to let the thematic community collaborate and to offer (technical) solutions regarding their specific data requirements and technical solutions: e.g. OneGeology and the Global Biodiversity Information Facility (GBIF). For some communities there exist very rich (geospatial) data models which go beyond what can usually be found in the basic SDI data models/specifications such as INSPIRE. The challenge is to link and integrate those data models. In some cases, metadata are treated in specific ways and more metadata elements are collected: e.g. in the air quality and meteorological world specific metadata are collected on the sensors that measure different parameters. Some communities rely on specific standards for their geospatial and other data: e.g. NetCDF (meteorological and aeronomy), Darwin Core/Ecological Metadata Language (biodiversity community) and Land Cover Classification System (LCCS) for the land/land-use community. They also often have their own platforms, systems and tools available: LPIS (agriculture), OneGeology (geology), ESDAC - European Soils Data Centre, etc.
SDI come to life when their components are used and a rich portfolio of (web) applications are built on top of them. Proper design of geospatial applications, models, and databases and the validation and verification of design activities are critical components of work in all areas related to GIS&T and SDI. Design failure can jeopardize well-intentioned efforts to apply concepts and technology to solve real-world problems. While sharing a number of concerns with general systems analysis, the specificity of geographic information provides significant additional challenges. The focus of this module is on the design of applications and, to a lesser extent, databases (the latter is part of module “SDI Data Models and Data Harmonization”) for a particular need in the context of the exploitation of SDI. Application Design addresses the development of workflows, procedures, and customized software tools for using geospatial technologies and methods to accomplish both routine and unique tasks that are inherently geographic. The design of tools and software code should be based on a thorough analysis of (functional and non-functional) user requirements and on a good insight in how the business processes in which they will be used work. Specific attention must be paid to user interfaces and how users will interact with the system. Development of programming code and testing and validation can be done in different ways, e.g. by applying a highly interactive scrum method. Special attention should be paid to geospatial Application Programming Interfaces (API) which allow for rapid software development in particular in the context of distributed systems. Examples are: Google Maps, OpenLayers, MapQuest API for OpenStreetMap, Leaflet, Esri ArcGIS REST and Mapbox. Open geospatial API’s will enhance the usability of SDI.