Accuracy expresses the quality of individual data. Parameters such as detection limit or measuring range are required to describe the accuracy.

Follows.

An aggregation level is a regulation for the formation of time series based on a calculation step.

An aggregation rule is a successive chain of aggregation levels. The chain finally leads to the formation of the target aggregation. Aggregation rules are used to define column values in the AquisNet reporting and for calculating collection lists.

Application functions realise the processing of the actual software configuration task (SWCU task).

AquisNet is a licensed product of Kisters AG and the successor product of LUQS.

AquisNet DB AquisNet product module

The AquisNet database consists of a uniform database schema that is used system-wide.

AquisNet product module. The AquisNet data forwarding module is used to forward data or files to system components or persons/groups of persons.

AquisNet product module. AquisNet DEC is a Windows client program for expert use. Users can perform administrative and configuration tasks that are valid system-wide in AquisNet. It is also used to monitor the quality of imported measurement data.

AquisNet product module. The evaluation module is designed as a web application. Here you can access comprehensive evaluation and reporting functionalities.

AquisNet product module. The business layer combines calculation processes, plausibility checks and other centralised functions relating to time series.

The sum of a series of values x, x, ..., x divided by their number n.

Attributes are descriptive properties of entities. They are defined by a set of permissible attribute values. An attribute has no other attributes.

The attribute values are the elements of a set of permissible values of the attribute.

Proportion of valid measured values of a data collective.

Time grid of the averaging.

Basic data is usually recorded once and is then statically available in a long-term data storage. It is mainly used to define structures and interrelationships, such as the monitoring networks. The basic data can be divided into different groups. Here, the station-related (descriptive) data and the identifying data for accessing the measuring series are mentioned.

Basic production time series are time series that have not been created by aggregation but have been entered into the system by import. Basic production time series are the basic object for the derivation of further time series with the same measurement location and measurement component. Basic production time series can be changed manually.

Time grid of the import time series of a parameter.

Benzene, toluene, xylene.

See Component group

Program to search for and retrieve data and documents on the WorldWideWeb and display them on the workstation computer.

Follows.

Possible on the same computer

Combination of measuring method and substance. The component represents the variable that is used in evaluations and in the parameterisation of stations to identify the subject.

Combining several components into one group to enable filter functions and easier access in the evaluation software. ✇ "BeToXy", "Meteorology", "Pollutants"

The compression of data serves to generate more compact and thus clearer time series. A fixed sequence of data is summarised using summation or arithmetic mean value generation. In the new time series with the higher (compressed) time base, some information from the original time series is lost. It therefore makes sense to include some characteristic values in the new time series, such as maximum and minimum with time or information about data gaps.

By combining different time series, new subjects are created. Typical examples of concatenations are vectorial wind averages and pollutant roses, which are created by accounting for pollutant concentration, wind direction and wind speed.

Tables in the AquisNet database contain measurement data and error codes.

Control functions realise the control and monitoring of the function call.

The value range of an examined characteristic is divided into k classes. The frequency value of a class reflects the proportion of the values in the total number of measured values. The (relative percentage) sum frequency of a class k consists of the sum of the (relative percentage) frequencies of classes 1 to k.

See Frequency.

Data exchange of the countries

Origin time series of a logical measuring device; combination of measured value and status.

Handling of observational data until they are in a form ready to be used for a specific purpose.

Follows.

Extensive, interrelated files for specific applications, usually with direct access options.

Central data archive that provides data.

German caesium radio clock (time standard).

Descriptive data protocol.

Direct data connections.

Derived values are not directly changeable (time series). They are created by condensation and/or linkage.

Functions of this class are used to request additional data input from the user during an operation (e.g. time selection).

Sizes that can be converted into each other, i.e. have the same physical meaning. This combines units into groups.

Detection limit.

See Accuracy.

Driver functions realise the operation of the information interfaces.

An entity is a set of similarly composed, uniquely identifiable objects and is described by (several) attributes. For each object, an attribute value is assigned to the attributes.

Quality attribute of a measured value, internal use,

Network protocol

Data transfer with the MURL's data information system as part of the evaluations.

Data transfer with the European Union as part of the evaluations.

Year indicator values as part of the evaluations.

Measurement network description (see Measurement network), which are available at LUA-NRW as metadata of the stations and the center in an MS Access database.

Monthly indicators as part of the evaluations.

1 for summarised values: This specifies how many valid measured values (½-h values) must be available in an averaging interval for a mean value calculation (compression) to take place. For 24-h values, for example, these are 32 valid ½-h values. 2 for indicator values: This specifies how many valid aggregated values must be available in the evaluation period for the indicator values to be calculated (e.g. 50% as a margin for annual reports).

1 absolute representation: Specification of the number of values that exceed the specified thresholds. 2 relative representation: Specification of the percentage of values that exceed the specified thresholds in relation to the total number of available values per period and station. 3 time part: Specification of the exceeding time in hours.

See Mean value generation.

Follows.

Program for transferring quality attributes to systems and for checking the validity of values.

Functions of this class are directly displayed in a form (e.g. recording and editing of basic data). The contents of the forms can usually be derived from the associated entities. Furthermore, tabular displays of data are assigned to the form functions.

The value range of an examined characteristic is divided into k classes. The frequency value of a class reflects the proportion of the values in the total number of values.

Server for file transfer protocol.

Gas chromatograph.

Functions of this class allow the representation of values in graphical form. The display of a complex report can also be a graph function.

See Mean value generation.

Data taken over from a predecessor system.

Half-hourly mean values.

See Mean value generation.

In addition to other criteria, immission measurements can be divided into individual measurements (random samples) and time series according to the temporal course of the measurement.

Individual measurements (samples) taken at predetermined locations in a random sequence. By selecting a suitable local grid, a comprehensive statement of the immission situation can be made over a longer time range (e.g. 1 year). The data must be treated using statistical methods.

The time over which values are summed up during mean value generation or the sampling duration ("length of the time range from which values are taken"). For simple arithmetic mean values, this is of the same duration as the time grid. See Moving mean value generation.

In-house network that is not accessible to the public (internet) from the outside.

A key is a user-assigned identification number for a record. Keys are subject to a system to be described by the user.

In a key directory, basic data (e.g. measuring stations, units,...) are listed according to a special key (criterion). These keys have been randomly assigned once according to an agreed scheme. A key directory can be kept as a value set.

See EU templates

Data that are not continuously recorded in the measuring stations on site, but are manually imported from the laboratory data storage at irregular intervals. This data enters the system in (*.csv) format.

Manual data import in larger (possibly irregular) time intervals of (*csv) files. See main menu entry "Lab data import"

AquisNet is a licensed product of KISTERS AG.

Thresholds are not characteristics of the time series themselves, but are specified externally, e.g. by regulations or by impact-relevant findings. They are used to assess the measuring results.

Follows.

Follows.

Sum of all values over a time range divided by their number.

See Mean value.

See Mean value.

Measured variable converted for further processing according to the specifications of the measured parameter.

In a broader sense, a measurement network is understood to include all measurement and transmission equipment as well as the IT equipment required for the maintenance, further processing and evaluation of the data obtained.

A measurement object is the collective term for similar data channels and a part of a measurement program (e.g. a specific pollutant).

Data parameters for defining the data channels.

Measurements with fixed time grid, time resolution smaller than the integration time.

Measurements that are not based on a fixed (time) grid (e.g. laboratory data import).

Measurements with a fixed time grid, time resolution greater than or equal to the integration time.

Measurements with time gaps. The time intervals between the measurements vary. (Marked points time series).

The physical measuring device is part of the physical measuring station. See Default measuring device.

The measurement method not only determines the accuracy of measurement data, but also the dynamic properties of time series (e.g. due to the inertia of the sensor). Measurement methods are only distinguished from each other in AquisNet because they do not provide directly comparable results. If non-comparability is due solely to the parameters "time grid" or the "integration time", these do not constitute a separate measurement method.

A measuring program is understood to be a sequence of measurement actions or measurement events in a measurement network that relate to specific measurement parameters (quality) and defined measurement locations.

A measuring station is a facility for recording measured values at a specific location. It has a measuring station computer and one or more measuring stations. The measuring station in AquisNet is named after the site.

A measuring station accepts commands and parameters. It provides one or more (1-n) data channels. A measuring station is a unit consisting of a measuring device and, if applicable, a processing unit.

50 percentile value. See percentile value.

Measuring device interface I (serial Hesse-Bavaria protocol) for continuously operating measuring devices.

Measuring device interface II, serial protocol for quasi-continuously operating measuring devices.

This part of the help is currently being revised.

With moving mean value generation, the integration time is not equal to the time grid. An integration time that is either smaller or larger than the time grid is possible.

1. Integration time smaller than time grid: Based on the time stamp of the calculated mean value, a mean value generation is carried out with values from the past. The next furthest back time stamp is not reached because the integration time is shorter than the time grid.

2. Integration time greater than time grid: A mean value is calculated from n values (with n>0). The number n results from dividing the integration time by the time grid.

See also Mean Value Generation.

Measuring station computer.

1 Non-moving mean value generation means that the mean value is calculated every n hours over the past n hours: Example for "3 h non-moving":

Value: Integration time from 0:00 to 3:00, assignment to 3:00

Value: Integration time from 3:00 to 6:00, assignment to 6:00 [...] This form of mean value generation is used for the half-hourly MW in the measuring station (✇ Evaluations, availability) 2 Moving mean value generation means that the mean value is calculated every half hour over the past n hours. Example for "3 h moving":

Value: Integration time from 21:30 of the previous day to 0:30, assignment of the value to 0:30.

Value: Integration time from 22:00 of the previous day to 1:00, assignment of the value to 1:00 [...].

48. Value: Integration time from 21:00 to 24:00, assignment of the value to 24:00.

In contrast to temporal aggregation, non-temporal aggregation takes place over a geographical area. This area includes one or more stations that have been combined into a station group. The aim here is to obtain values over the geographical area. The result is, for example, a single annual multi-maximum of all stations from all annual maxima of the stations in a station group. Here, the time grid information is retained – in contrast to temporal aggregation, where you calculate an annual maximum from a monthly maximum, for example.

An object is a real or conceptually existing object with a fixed, known set of properties (attributes). Similar objects are manifestations of an entity. They are described by values of the attributes of the associated entity.

Open Database Connectivity.

An offset time interval represents a subset within a larger time set. An example is the period of 8 hours (subset) within a larger/overarching 12-hour period. The creation of such a time interval is possible during the process of aggregating a time series with the settings "Integration time < time grid" and specification of a "Time offset" in the "Origin-specific parameters" section.

Origins contain information on how time series are derived from other (source) time series.

Original time series contain data at the import time. These are read-only and are used for data control purposes.

Spontaneous connection of a station to the center.

Quantities that influence the recording, processing and evaluation of other quantities (e.g. measured values).

Explanation using an example: The 98 percentile value of a measured value series is the value below which 98% of all measured values lie.

Part of a measuring station that carries out the actual implementation of the measurement.

Automatic checking of the values using configurable check criteria. The check is carried out against one or more reference values.

Part of the attributes of each entity must be suitable as an "identifiable key" to uniquely address each object of the entity.

This is understood to be a print-ready file with layout information such as headings, print date, header and footer, etc.

Follows.

Functions of this class (e.g. mean value generation) can be called by other functions and do not require interaction with the user.

Quality.

Follows.

A relation can exist between objects if a relation type is defined between the associated entities. The relation is described by linked enumeration of the values of the identifying keys of the related objects.

A relation type is a set of relations and exists only between entities. A relation is an instance of a relation type.

A report based on a predefined evaluation.

Follows.

See MGS-I and MGS-II.

The server provides the client with data that only the client can access.

Here, either a point in a coordinate system, or, as a substitute, a station name is used. See Measuring station.

Structured Query Language.

Standardised language for configuration, also query of relational databases.

"Abstracted" measuring device that has a standardised range of functions. Standard measuring devices can all be controlled in the same way. Special functions are not available.

See Measuring station and Site.

Follows.

Description of the state of an entity.

Status message of a measuring device.

Error codes communicate quality information of measurement data.

This term does not exist in the AquisNet software. Instead, the terms substance and/or parameter are used

Substances in the sense of AquisNet are chemical compounds and physical quantities. They do not include a unit, a measuring method, a site or a time reference. This is not the term substance in the chemical sense; in AquisNet, it also includes meteorological variables, for example. Examples: Sulphur dioxide, wind, suspended dust, soot.

A subtype is an entity that extends the general properties of the associated supertype.

Time series derived from import time series with a smaller time grid (e.g. daily average or half-hourly values).

Software configuration unit.

Software maintenance and software change.

Text elements are used as static text in dispatch orders (Forwarding module). Text elements consist of a specific type.

The threshold represents a limit value against which all measured values are to be checked for exceeding or falling below.

The time grid indicates the time interval of the equidistant sampling. See Integration time and Mean value generation.

A time interval represents a subset within a larger time set. An example is the period of 8 hours (subset) within a larger/overarching 12-hour period.

See Offset time interval.

Time profiles define so-called "active time stamps" and are used in this way to execute report jobs and data forwarding tasks. At the time, the active time stamps call up assigned tasks.

The time series is a chronologically sorted sequence of measured values of the same subject with the same location reference. Time series can be related to other time series via origins.

Time series definition are regulations for constructing a first level time series. It is a summary of time series properties such as component, integration time, time series type and unit. Time series definitions do not contain source information.

Follows.

Equivalent to the calculation type, such as mean, maximum, minimum, sum, percentile, exceedance, etc.

A time slice is a time series property. The integration time is shifted backwards or forwards from the time stamp (00:00:00) by the time offset. The term time slice is therefore used to describe a period of 24 hours, which, however, deviates from the regular "daily limits": Such a time slice is, for example, the period from "01.04.2001 10:03:37" to "02.04.2001 10:03:36". This time range covers 24 hours, but exceeds the day time stamp at 00:00:00 on the first day by 10 hours, 3 minutes, and 36 seconds, i.e. by a total time offset of 36,216 seconds. A time series whose integration time is 24 hours but differs from the time stamp by the time offset is therefore a time slice. This special property of a time series can only be determined by means of the list of origin-specific parameters and is not part of the regular identifier.

A time stamp represents the recording of a value in a defined format at a specific time.

List of changes to time series data, also containing a name, an internal identifier and a comment.

Follows.

A transducer is a technical measuring device (e.g. a pulse transmitter for precipitation) which transforms a natural subject into a processable measurement signal.

Structure bar for clear and quick working and navigation, for example in a data structure with several layers.

Number of measured values combined into a tuple.

German Environment Agency (Umweltbundesamt – UBA).

The unit is the measuring unit of a subject or substance. The entity "unit" contains a name and a reference to the "dimension" (SI base unit) and a conversion factor compared to this SI base unit ("default unit").

Members of an institution or organisational unit who use computer systems to perform their professional tasks.

Persons who directly use a computer system and operate it themselves

Functions of this class can be activated by the authorised user via a dialog element of the user interface.

Interface at which the user communicates with the system via a dialog.

With user queries, you can send queries to the AquisNet database via SQL statement to read out data or data records. User queries are entered via AquisNet AUS and are only permitted to authorised and trained users.

Interactive check and setting to "valid" or "invalid" and, if necessary, change of measured values.

A value range is a set of values from which one or more attributes take their current values.

See Value sets.

Value sets can contain norm and standard texts, parameters and special entries.

▪Norm texts describe technical contexts.

▪Standard texts are centrally or decentrally defined texts for describing a subject matter, usually comprising a longer text (e.g. in the sense of a text module).

▪Parameters in value sets describe chemical-physical indicator values such as concentrations of individual substances, but also water quantities, levels, stages and temperatures. Units and unit groups also belong in this environment.

See Dimension.

Also http server.

Follows.

Follows.

See EU templates.