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Mobile and stationary sensors currently used to measure various environmental parameters, functioning independently or as part of monitoring networks and measurement stations, provide vast amounts of data on the state and quality of the environment on the Earth. If the data is to be used effectively, they must be exchanged and shared among IT systems. Systems which offer services of searching, exchange, sharing, visualisation and analysis of dispersed and varied data resources on the widely understood environment are, for example, spatial data infrastructures.

The article presents an overview of IT technologies and standards which offer interoperability in spatial data infrastructures. It first defines interoperability and then describes the most important issues connected with spatial data infrastructures on the example of INSPIRE.

Its practical application is proposed - for description of processes of air monitoring in a spatial data infrastructure that is an element of the Polish national environmental monitoring plan.

At present, globally, there are hundreds of thousands mobile and stationary sensors, which measure various environmental parameters and function independently or are part of thousands of monitoring networks and measurement stations that monitor all elements of the environment. Additionally, over 50 environment satellites carry out their research missions.

Various observations and measurements are also made all the time, both in the field and in laboratories. These activities generate an unimaginable amount of data on the. Rogulski is. Rossa is. In order to be able to fully use these vast and varied resources, it is necessary to provide the possibility of their exchange and sharing among different IT systems.

Technological progress connected with the development of the internet has contributed to improvement of the functions of searching, exchanging, sharing, visualisation and analysis of dispersed and varied information resources on the widely understood environment.

An example of such implementation is SDI - spatial data infrastructures with geostandards as the basis of their functioning [28]. Spatial data infrastructures include spatial data, as well as services, technical means, processes and procedures connected with them.

Spatial data is information on the location determined using coordinates in a given system of reference , geometrical properties and spatial relations of objects which may be identified with reference to the Earth. The aim of this publication is an overview of IT technologies and standards which facilitate interoperability in spatial data infrastructures, presentation of a component of Sensor Web Enablement - a specification of SensorML, as an example of a language which supports interoperability and proposition of its use in a spatial data infrastructure in Poland.

Section 2 presents the concept of interoperability. Section 3 is an introduction to the subject of spatial data infrastructures. A practical application of the language with a suggestion of its use in a spatial data infrastructure in Poland is presented in section 6.

The last section contains a summary. The possibility of exchanging, sharing and automatic processing of data in IT systems is connected with their interoperability, which may be discussed in the context of interoperability of data and services. The concept of interoperability is closely linked with informatics and with IT systems in particular. Interoperability is generally described as " More precisely, the concept may be defined as " Paraphrasing [21], achieving interoperability is the condition which enables communication among systems and exchanging and using the same data in different systems.

Most systems or ways of categorisation of interoperability [10, 13, 15, 20] distinguish its three main levels:. This level is sometimes divided into two separate levels: the legal one and the organisational one. This is mainly applied when analysing interoperability in the context of tasks realised by state administration units;. Activities aimed at achieving interoperability at the formal and organisational and technical levels have for a long time been effectively solved, implemented and realised.

Great advances in this area are also visible in the fields connected with environmental studies, i. However, semantic interoperability is still being developed. Despite constant development of the capabilities of network resources to communicate, especially the development of web services, the issue is still unresolved and needs further research and analyses [21]. An example of the solutions suggested so far may be the use of methods based on ontologies and inference in the project meanInGs [23].

A way of supporting interoperability is processing data in unambiguously defined, strict schemata published in specialised web services which have individual communication protocols.

This concept for spatial data is used in spatial data infrastructures SDI , which are built on the basis of SOA Service Oriented Architecture using web service technologies [26]. To some extent, using SDI allows to automate the use of processed metadata and spatial data [17, 18, 19]. They form the basis for construction and functioning of SDI, supporting full technical interoperability, both in terms of service communication and data exchange [28]. A growing number of data and services entails the necessity to use more and more advanced IT tools and technologies.

The possibilities and perspectives of development in this field using i. In [11] there is a suggestion of enhancing standard cataloguing services in SDI with semantic elements, while in [9] - a semantic development of cataloguing services in SDI for a region in Italy. Interoperability at the formal and organisational level in INSPIRE is realised through a wide range of formal and legal solutions procedural and organisational ones , the aim of which is to ensure cooperation of all those involved in creating and processing spatial data included in INSPIRE.

Technical interoperability in spatial data infrastructures, both in terms of services and data, is effected through implementation of OGC geostandards and ISO norms; in the case of INSPIRE also through dedicated technical guidelines. It is an XML grammar for expressing geographical features and their relations. In simple terms, GML describes only their geometry and topology but not their meaning. It contains generic geographical data that contain points, curves, polygons etc.

For the purposes of data exchange within a field of knowledge and for support of interoperability at the technical schematic level, on the basis of the GML language, field dedicated languages of data exchange not formats are developed and they are its profiles simplification or applications extension [25]. The above standards are the basis for creation of other languages of data exchange dedicated to various fields. At present, there are over twenty languages of this type in the fields of: Earth sciences geology, tectonics, hydrogeology, hydrology, soil science , spatial planning, geohazards, agriculture, meteorology and climatology, hydrography and oceanography, and biology.

It is worth noting that all the above mentioned data exchange languages share general and field classes of objects, e. In INSPIRE3, only a few subjects of spatial data include data on the state and quality of the environment which are derived directly from measurements and observations.

These subjects include:. Includes spatial data based on measurements, on models or on a combination thereof and includes measurement locations. SensorML is an XML schema used to describe a model of functioning of sensors and measurement processes connected with them.

With the use of SensorML, one can describe a wide range of sensors, both mobile and stationary ones, those taking measurements on site or remotely. In addition, it allows to, for instance, describe algorithms needed to control sensors, localise observations made with sensors, and process them at a low level. Sensors covered by SensorML include: stationary ones measuring on site, e. Lidar, Doppler radar; mobile ones measuring on site, e.

Uniform encoding benefits the integration of heterogeneous sensors as it provides a standard view to the user. Thus, some of its parts are connected or enable reference to other elements of the project.

The latest version SensorML 2. A basic element of the language is a measurement process for which it is possible to determine input, output, parameters and additional information characterising the process. The user may create many types of processes concerning any environmental component, which as their basis require attributes defined in the base process. Processes may be both physical processes connected with measurements and observations, and processes other than physical ones e.

The most important abstract types of objects offered by SensorML 2. Parameters include, for instance, temperature, gravitational force, location, chemical concentration etc. Objects inheriting from this type may also describe quantities connected with phenomena which have been determined in other ways than direct measurement e.

These include many descriptive properties on general process information e. They are grouped in lists for simpler analysis. The class also has properties which enable provision of the methodology used in the process.

SensorML 2. Both have been defined as interfaces so they may be used to create web services, for instance. The functionality of SOS is mainly provision of interface enabling access to observations made with measurement sensors and to sensor description. Offered classes and methods enable, i. The SPS standard is devoted to control of sensors and measuring devices. For example, it allows to describe and download sensor parameters, send requests to sensors at different stages of their operation e.

In contrast to SOS, it does not offer access to data collected with sensors but only offers the possibility to parameterise sensors and measuring devices. Examples of application of the SWE standard along with a short description of services included in the specification may be found in [5].

In [3], the authors have described the uses of SWE also of SensorML to create a web cataloguing service based on an OGC cataloguing service, enabling localisation, access, parameters provisioning and use of sensors and algorithms describing sensors. A proposed concept also includes development of a dictionary of business transactions ebXML. Technologies and standards included in SWE have also been used to create a phenomenon-based service of obtaining spatial data on demand. In the proposed service, the user may.

In turn, [2] proposes using BPEL and process chains from SensorML, a method of creating workflows for the so-called e-science - for these areas of science that require calculations in heavily dispersed network environments or that use vast amounts of data processed in grid environments. SensorML is not the only language for standardisation of processes connected with functioning of sensors. An overview of currently developed norms and standards may be found in [32].

They also point to cooperation possibilities between these units and perspectives of development of standards. In Poland, the described standards have not been widely used yet.

They could be used when observations are made with different devices and methods and the process of collecting and processing a large number of measurements is quite developed. A good example application would be for description of processes of air monitoring. The reason is a big number of varied measuring devices and measured indicators of air quality, as well as quite a developed process of verification, analysis and processing of the data.

Air monitoring is a process conducted by voivodship inspectorates for environmental protection as part of the national environmental monitoring plan NEMP. The obligation and its extent is defined in the act Environmental Protection Law art. In accordance with the act, the aim of NEMP is support for environmental actions through systematic information of administration units and the society on, e.

At present, results of measurements of air pollution concentrations from automatic stations in some cases, along with accompanying meteorological parameters are automatically transmitted via a telecommunications network to databases maintained by voivodship inspectorates for environmental protection.

These systems also receive measurement results made with non-automatic methods. Verified data is used to: create and update reports from special zones, where there is a risk of exceeding warning levels of air pollution concentrations, to develop short-term forecasts of air quality in special zones, to create reports e.

The data is also available to the society. Currently, all 16 voivodship inspectorates present results from stations of automatic air monitoring in the voivodship on-line, on their websites.


dyrektywa INSPIRE

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