The SeTT ontology
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The SeTT ontology

Release: July 2025

This version:
http://purl.org/net/sett/vocab#1.0
Latest version:
http://purl.org/net/sett/vocab#
Revision:
1.0
Authors:
(1) Daniela Fernanda Milon-Flores
(2) Camille Bernard
(3) Jérôme Gensel
(4) Gregory Giuliani
License:
http://creativecommons.org/licenses/by/4.0/
Visualization:
Visualize with WebVowl
Cite as:
Cite this vocabulary as Milon-Flores, D.; Bernard, C.; Gensel, J. and Giuliani, G. The SeTT ontology 1.0
Ontology Specification Draft

Abstract

The negative impact of human activities on our planet has increased the interest of stakeholders, from policymakers to citizens, in monitoring and understanding local environmental changes. However, these data are often complex and difficult for non-experts to interpret. To address this, we introduce the SeTT (Semantic Trajectory of a Territorial Unit) ontology, which describes the environmental evolution of Territorial Units (e.g., municipalities) through different perspectives—Raw, Structured, and Thematic—making this information more synthesized, accessible, and understandable for both expert and non-expert users.
Descriptive alt text
Figure 1. The SeTT ontology main primitives.

Introduction back to ToC

This is a place holder text for the introduction. The introduction should briefly describe the ontology, its motivation, state of the art and goals.

Namespace declarations

Table 1: Namespaces used in the document
[Ontology NS Prefix]<http://purl.org/net/sett/vocab#>
dc<http://purl.org/dc/elements/1.1/>
owl<http://www.w3.org/2002/07/owl#>
qb<http://purl.org/linked-data/cube#>
rdf<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
rdfs<http://www.w3.org/2000/01/rdf-schema#>
schema<http://schema.org/>
skos<http://www.w3.org/2004/02/skos/core#>
terms<http://purl.org/dc/terms/>
xml<http://www.w3.org/XML/1998/namespace>
xsd<http://www.w3.org/2001/XMLSchema#>

The SeTT ontology: Overview back to ToC

This ontology has the following classes and properties.

Classes

Object Properties

Data Properties

The SeTT ontology: Description back to ToC

SeTT is a multi-layered ontology specifically designed to describe the semantic trajectories of Territorial Units (TUs). It models three types of trajectories: Raw, Structured, and Semantic. Together, these trajectories create a comprehensive framework for capturing, organizing, and analyzing the evolution of TUs across various thematic domains, thereby improving users' ability to interpret and understand complex data.

Cross-reference for The SeTT ontology classes, object properties and data properties back to ToC

This section provides details for each class and property defined by The SeTT ontology.

Classes

Attributec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Attribute

An Attribute provides additional descriptive information about a trajectory component. Attributes may hold a wide range of values, offering flexibility for representing various temporal or thematic aspects.
has sub-classes
External Attribute c, Intrinsic Attribute c
is in domain of
has Attribute Value dp
is in range of
has Attribute op, semantic Annotation Based On Attribute op
is disjoint with
Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

B E A S Tc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#BEAST

The Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) is a statistical algorithm used for detecting breakpoints, trends, and seasonal variations in time series data. It applies a Bayesian framework to estimate the number and location of change points, making it well-suited for analyzing environmental and remote sensing datasets.
has super-classes
Segmentation Method c, Transition Point Detection Method c

B F A S Tc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#BFAST

The Breaks For Additive Season and Trend (BFAST) algorithm is a statistical method for detecting structural changes in time series data. It decomposes a time series into seasonal, trend, and remainder components and identifies breakpoints where abrupt changes occur. BFAST is widely used in environmental monitoring and remote sensing applications to analyze long-term changes in vegetation, climate, and land cover.
has super-classes
Segmentation Method c, Transition Point Detection Method c

B F A S T Litec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#BFASTLite

The BFAST Lite algorithm is a simplified version of the BFAST framework designed for efficient detection of breakpoints, trends, and seasonal variations in large-scale time series data. Unlike the full BFAST model, which iteratively decomposes the time series, BFAST Lite focuses on detecting change points in a single-pass approach, making it computationally faster and suitable for large datasets. It is particularly useful for processing satellite-based Earth observation data and environmental monitoring at scale.
has super-classes
Segmentation Method c, Transition Point Detection Method c

B F A S T Monitorc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#BFASTMonitor

The BFAST Monitor (Breaks For Additive Season and Trend Monitor) is a statistical algorithm designed for near-real-time monitoring of breakpoints, trends, and seasonal variations in time series data. It extends the BFAST framework by continuously detecting structural changes in new observations while preserving the existing trend and seasonal components. This makes it particularly useful for analyzing environmental and remote sensing datasets, where ongoing monitoring of land cover or vegetation changes is required.
has super-classes
Segmentation Method c, Transition Point Detection Method c

Binsegc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Binseg

Binary Segmentation (Binseg) is a recursive, top-down approach that detects change points in a sequential manner. This method is less computatio ally intensive but sacrifices some level of optimality in exchange for speed. The algorithm works by splitting the time series into two parts at each iteration and testing whether there is a significant change between these two segments. If a change point is detected, the algorithm continues to split the time series recursively. It repeats this process until no further changes are detected or a predefined stopping criterion is met.
has super-classes
Segmentation Method c, Transition Point Detection Method c

Break Pointc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#BreakPoint

A Break Point is a Transition Point that marks an abrupt and significant change in the data, such as a sudden increase or decrease.
has super-classes
Transition Point c
is disjoint with
Inflexion Point c, Interruption Point c, Regime Change Point c

C C D Cc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#CCDC

The Continuous Change Detection and Classification (CCDC) algorithm is a time series analysis method designed for detecting land surface changes using satellite imagery. It continuously monitors time series data by fitting harmonic regression models to capture seasonal variations and trend changes. When significant deviations from the expected model occur, CCDC identifies them as change events. This method is widely used in remote sensing applications for land cover monitoring, forest disturbance detection, and environmental change analysis.
has super-classes
Transition Point Detection Method c

Componentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Component

A Component represents a part of a trajectory, defined by its position in the sequence and its descriptive attributes. The SeTT ontology defines three types of components: raw, structured, and thematic.
has sub-classes
Raw Component c, Structured Component c, Thematic Component c
is in domain of
has Attribute op, has External Attribute op, has Intrinsic Attribute op, has Sequence Order dp
is disjoint with
Attribute c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

Countryc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Country

A Country represents the national entity in which a Territorial Unit is located.
is in range of
country op
is disjoint with
Attribute c, Component c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

D B E S Tc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#DBEST

The DBEST (Detecting Breakpoints and Estimating Segments in Trend) algorithm is a statistical method designed for detecting breakpoints and estimating trend segments in time series data. It is particularly effective in analyzing environmental changes, such as vegetation dynamics, by decomposing time series into meaningful segments. DBEST employs a data-driven approach to identify trend shifts and estimate their magnitude, making it well-suited for applications in remote sensing and ecological monitoring.
has super-classes
Segmentation Method c, Transition Point Detection Method c

Episodec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Episode

An Episode is derived from the semantic annotation of a Segment in the Structured Trajectory. It represents a continuous period characterized by a specific behavior or condition, as defined by semantic annotations and descriptive attributes. An Episode ends when an Event occurs, marking a discontinuity in the trajectory.
has super-classes
Thematic Component c
is in domain of
episode Is Annotated From op
is in range of
has Episode op
is disjoint with
Event c

Episode Behavior Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeBehaviorAnnotation

Semantic annotation that qualifies the overall dynamic of an Episode by integrating its temporal extent (short-term, moderate-term, long-term), the magnitude and direction of change (slope), the thematic focus (e.g., vegetation, temperature, population), and its vertical position (value level). This annotation provides an integrated, syntezed and enriched view of how an Indicator changes over the course of the Episode.
has super-classes
Semantic Annotation c
is disjoint with
Episode Duration Annotation c, Episode Gradual Magnitude Annotation c, Episode Slope Annotation c, Episode Statistical Significance Annotation c, Episode Thematic Slope Annotation c, Episode Value Level Annotation c, Event Transition Annotation c

Episode Duration Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeDurationAnnotation

Semantic annotation that qualifies the temporal extent of an Episode, categorizing it as short-term, moderate-term, or long-term
has super-classes
Semantic Annotation c
is disjoint with
Episode Behavior Annotation c, Episode Gradual Magnitude Annotation c, Episode Slope Annotation c, Episode Statistical Significance Annotation c, Episode Thematic Slope Annotation c, Episode Value Level Annotation c, Event Transition Annotation c

Episode End Datec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeEndDate

Episode End Date indicates the date on which an Episode concludes.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Episode Gradual Magnitude Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeGradualMagnitudeAnnotation

Semantic annotation that qualifies the overall intensity of change throughout an Episode, based on the slope and duration of its corresponding segment. This gradual magnitude of change is computed as the product of slope magnitude and duration.
has super-classes
Semantic Annotation c
is disjoint with
Episode Behavior Annotation c, Episode Duration Annotation c, Episode Slope Annotation c, Episode Statistical Significance Annotation c, Episode Thematic Slope Annotation c, Episode Value Level Annotation c, Event Transition Annotation c

Episode Slope Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeSlopeAnnotation

Semantic annotation for an Episode based on the slope characteristics of its corresponding segment, considering both the slope direction (increase, decrease, or stable) and its magnitude.
has super-classes
Semantic Annotation c
is disjoint with
Episode Behavior Annotation c, Episode Duration Annotation c, Episode Gradual Magnitude Annotation c, Episode Statistical Significance Annotation c, Episode Thematic Slope Annotation c, Episode Value Level Annotation c, Event Transition Annotation c

Episode Start Datec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeStartDate

Episode Start Date indicates the date on which an Episode begins.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Episode Statistical Significance Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeStatisticalSignificanceAnnotation

Semantic annotation that indicates the statistical confidence in the trend observed during the Episode.
has super-classes
Semantic Annotation c
is disjoint with
Episode Behavior Annotation c, Episode Duration Annotation c, Episode Gradual Magnitude Annotation c, Episode Slope Annotation c, Episode Thematic Slope Annotation c, Episode Value Level Annotation c, Event Transition Annotation c

Episode Thematic Slope Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeThematicSlopeDirectionAnnotation

Semantic annotation that provides a theme-specific interpretation of an Episode’s slope direction—for example, Greening for vegetation, Warming for temperature, or Population Growth for population.
has super-classes
Semantic Annotation c
is disjoint with
Episode Behavior Annotation c, Episode Duration Annotation c, Episode Gradual Magnitude Annotation c, Episode Slope Annotation c, Episode Statistical Significance Annotation c, Episode Value Level Annotation c, Event Transition Annotation c

Episode Value Level Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EpisodeValueLevelAnnotation

Semantic annotation that qualifies the vertical position of an Episode’s start or end along the indicator’s value axis (i.e., the y-axis). It categorizes this position into levels such as very low, low, moderate, high, or very high.
has super-classes
Semantic Annotation c
is disjoint with
Episode Behavior Annotation c, Episode Duration Annotation c, Episode Gradual Magnitude Annotation c, Episode Slope Annotation c, Episode Statistical Significance Annotation c, Episode Thematic Slope Annotation c, Event Transition Annotation c

Eventc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Event

An Event represents a meaningful change in the trajectory that occurs at a specific moment in time, causing a discontinuity between Episodes in the Thematic Trajectory. It is derived from the semantic annotation of a Transition Point and is described through annotations and attributes that characterize the nature and significance of the transition.
has super-classes
Thematic Component c
is in domain of
event Is Annotated From op, has Explanatory Factor op
is in range of
has Event op
is disjoint with
Episode c

Event Datec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EventDate

Event Date specifies the date on which an Event took place.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Event Explanatory Factorc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EventExplanatoryFactor

An Event Explanatory Factor refers to a potential driver or context that explains a change observed at a Transition Point, such as a Breakpoint. It may consist of external sources like bibliographic references, URLs, or links to Linked Open Data repositories.
has super-classes
External Attribute c
is in range of
has Explanatory Factor op
is disjoint with
Segment Gradual Magnitude c, Segment p-value c, Transition Point Magnitude c, Transition Point Probability c

Event Transition Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#EventTransitionAnnotation

Semantic annotation that qualifies both the direction and intensity of change at the Transition Point associated with an Event.
has super-classes
Semantic Annotation c
is disjoint with
Episode Behavior Annotation c, Episode Duration Annotation c, Episode Gradual Magnitude Annotation c, Episode Slope Annotation c, Episode Statistical Significance Annotation c, Episode Thematic Slope Annotation c, Episode Value Level Annotation c

External Attributec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#ExternalAttributes

An External Attribute refers to contextual or auxiliary information that enhances the description of a trajectory component. These attributes are not intrinsic to the component itself but may be derived from external analyses, expert input, or supporting datasets.
has super-classes
Attribute c
has sub-classes
Event Explanatory Factor c, Segment Gradual Magnitude c, Segment p-value c, Transition Point Magnitude c, Transition Point Probability c
is in range of
has External Attribute op
is disjoint with
Intrinsic Attribute c

H M Mc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#HMM

Hidden Markov Models (HMM) are a powerful statistical tool used to model time-series data, particularly when the data evolves through different underlying states that are not directly observable. These "hidden" states represent distinct environmental conditions or phases, and the system transitions between these states over time. For example, in environmental studies, the hidden states might represent different trends in data such as: • Stable Trend: No significant changes in the environmental variable (e.g., temper- ature, vegetation health). • Increasing Trend: A period of gradual increase in the environmental variable (e.g., warming temperatures, growing vegetation). • Decreasing Trend: A period of gradual decline in the environmental variable (e.g., cooling temperatures, deteriorating vegetation).
has super-classes
Transition Point Detection Method c

Indicatorc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Indicator

An Indicator is defined as a quantitative measure that captures the status of a situation or its variations over time.
is in domain of
has Indicator Description dp, has Indicator Formula dp, takes Data From op
is in range of
monitors Indicator op, takes Data From op
is disjoint with
Attribute c, Component c, Country c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

Inflexion Pointc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#InflexionPoint

An Inflexion Point indicates a subtle change in the trajectory where the direction or curvature shifts gradually, rather than abruptly.
has super-classes
Transition Point c
is disjoint with
Break Point c, Interruption Point c, Regime Change Point c

Interruption Pointc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#InterruptionPoint

An Interruption Point marks a temporary disruption in the trajectory, such as a short-term deviation that is not sustained.
has super-classes
Transition Point c
is disjoint with
Break Point c, Inflexion Point c, Regime Change Point c

Intrinsic Attributec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#IntrinsicAttributes

An Intrinsic Attribute describes essential characteristics of a trajectory component that are inherent to its structure or behavior.
has super-classes
Attribute c
has sub-classes
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c
is in range of
has Intrinsic Attribute op
is disjoint with
External Attribute c

Linear Regressionc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#LinearRegression

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to the data. It is commonly used for trend analysis, forecasting, and identifying patterns in datasets. In its simplest form, simple linear regression uses a straight line (y = mx + b) to represent the relationship between two variables, where m is the slope and b is the intercept. Linear regression is widely applied in various fields, including economics, environmental studies, and machine learning, to analyze trends and make predictions.
has super-classes
Segmentation Method c

Linear Segmentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#LinearSegment

A Linear Segment is a type of Segment where the data follows a linear trend over time.
has super-classes
Segment c
is disjoint with
Non Linear Segment c, State Segment c

Non Linear Segmentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#NonLinearSegment

A Non Linear Segment is a type of Segment where the data shows a non-linear pattern over time, such as seasonal or cyclical behavior.
has super-classes
Segment c
is disjoint with
Linear Segment c, State Segment c

P E L Tc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#PELT

The PELT (Pruned Exact Linear Time Algorithm) algorithm is designed to identify the most optimal segmentation of time series data by minimizing a penalized cost function. The method is particularly effective in providing an accurate segmentation while ensuring efficient computational performance.
has super-classes
Transition Point Detection Method c

Piecewise Regressionc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#PiecewiseRegression

Piecewise Regression is a statistical technique used to model time series data by dividing it into multiple segments and fitting separate regression models to each segment. Unlike simple linear regression, which assumes a single trend across all observations, piecewise regression allows for structural changes, making it useful for detecting breakpoints and modeling non-linear trends in time series data. It is widely applied in environmental monitoring, remote sensing, and economic trend analysis.
has super-classes
Segmentation Method c

Raw Componentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#RawComponent

A Raw Component is a type of Component used to build a Raw Trajectory.
has super-classes
Component c
has sub-classes
Slice c
is disjoint with
Structured Component c, Thematic Component c

Raw Trajectoryc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#RawTrajectory

A Raw Trajectory consists of a time series that tracks changes in domain-specific indicators for a Territorial Unit (TU). The time series is integrated into the Linked Open Data (LOD) Cloud using the Slice component of the RDF Data Cube vocabulary, and is organized along Time, Space, and Indicator dimensions.
has super-classes
Trajectory c
is in domain of
has Slice op, has Total Slices dp, monitors Indicator op
is disjoint with
Structured Trajectory c, Thematic Trajectory c

Regime Change Pointc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#RegimeChangePoint

A Regime Change Point signals a transition between two distinct states or regimes in the data, characterized by long-term structural differences.
has super-classes
Transition Point c
is disjoint with
Break Point c, Inflexion Point c, Interruption Point c

Segmentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Segment

A Segment is a continuous part of a trajectory where the data follows a consistent pattern. It has attributes that enhance its description, such as init, end, and slope. A Segment may start or end at a Transition Point, depending on how the trajectory is structured.
has super-classes
Structured Component c
has sub-classes
Linear Segment c, Non Linear Segment c, State Segment c
is in domain of
segment Is Derivated From op
is in range of
episode Is Annotated From op, has Segment op
is disjoint with
Transition Point c

Segment Durationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentDuration

Segment Duration refers to the number of observations that make up a Segment, indicating how long the segment lasts in the time series.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segment End Xc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentEndX

Segment End X specifies the x-coordinate, i.e., the time value, that marks the end of a segment.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segment End Yc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentEndY

Segment End Y specifies the y-coordinate, i.e., the measured value, marking the end of a Segment.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segment Gradual Magnitudec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentGradualMagnitude

Segment Gradual Magnitude describes the overall strength of change within a segment, such as a Linear Trend. It is computed by multiplying the slope magnitude by the segment duration.
has super-classes
External Attribute c
is disjoint with
Event Explanatory Factor c, Segment p-value c, Transition Point Magnitude c, Transition Point Probability c

Segment p-valuec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentPValue

Segment p-value indicates the statistical significance of a segment’s trend, such as in a Linear Segment. It reflects the confidence level of the detected change.
has super-classes
External Attribute c
is disjoint with
Event Explanatory Factor c, Segment Gradual Magnitude c, Transition Point Magnitude c, Transition Point Probability c

Segment Slope Directionc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentSlopeDirection

Segment Slope Direction indicates whether the slope of a Trend Segment is increasing, decreasing, or flat.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segment Slope Interceptc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentSlopeIntercept

Segment Slope Intercept is the y-value at which a linear trend line intersects the y-axis, representing the expected value when x is zero.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segment Slope Magnitudec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentSlopeMagnitude

Segment Slope Magnitude represents the absolute value of the slope of a linear segment, indicating the strength of change regardless of direction.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segment Start Xc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentStartX

Segment Start X specifies the x-coordinate, i.e., the time value, that marks the start of a segment.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segment Start Yc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentStartY

Segment Start Y specifies the y-coordinate, i.e., the measured value, marking the start of a Segment.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Segmentation Methodc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SegmentationMethod

A Segmentation Method is a technique used to divide a time series into meaningful segments, typically based on patterns such as trends or value stability. These methods help identify consistent intervals within the data where the behavior remains relatively uniform.
has super-classes
Structuration Method c
has sub-classes
B E A S T c, B F A S T c, B F A S T Lite c, B F A S T Monitor c, Binseg c, D B E S T c, Linear Regression c, Piecewise Regression c
is in range of
calculated Using Segment Method op

Semantic Annotationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SemanticAnnotation

A Semantic Annotation enriches a Thematic component—such as an Episode or Event—by linking it to a meaningful concept, typically defined in a controlled vocabulary or ontology.
has sub-classes
Episode Behavior Annotation c, Episode Duration Annotation c, Episode Gradual Magnitude Annotation c, Episode Slope Annotation c, Episode Statistical Significance Annotation c, Episode Thematic Slope Annotation c, Episode Value Level Annotation c, Event Transition Annotation c
is in domain of
semantic Annotation Based On Attribute op
is in range of
defines Criteria For op, has Semantic Annotation op
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

Semantic Annotation Criteriac back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SemanticAnnotationCriteria

Semantic annotation criteria define the formal conditions and/or thresholds used to determine how specific annotations are assigned and interpreted. They may also specify the method applied to derive the annotation. These parameter selections are applied consistently across all annotations related to the thematic components—Episodes and Events—of the Thematic Trajectories.
is in domain of
defines Criteria For op, has Annotation Criteria Description dp
is in range of
has Semantic Annotation Criteria op
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

SeTTc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SeTT

A SeTT (Semantic Trajectory of a Territorial Unit) represents a collection of Thematic Trajectories describing the evolution of a Territorial Unit across one or more domains. It serves as an abstract structure capable of grouping Thematic Trajectories from different themes. A Territorial Unit may be associated with one or more SeTTs.
has super-classes
is in domain of
has Broader Theme op, has Thematic Trajectory op
is in range of
has Se T T op
is disjoint with
Attribute c, Component c, Country c, Indicator c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

Slicec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Slice

A Slice represents a portion of raw data defined as a Slice in the RDF Data Cube vocabulary. It is used to compute Segments in the Structured Trajectory.
has super-classes
Raw Component c
is in range of
has Slice op, segment Is Derivated From op, transition Point Delimit Slice op

Slice End Observationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SliceEndObservation

Slice End Observation identifies the final observation included in a Slice.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice Start Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Slice Start Observationc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SliceStartObservation

Slice Start Observation identifies the first observation included in a Slice.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Total Observations c, Transition Point X c, Transition Point Y c

Slice Total Observationsc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#SliceTotalObservations

Slice Total Observations indicates the number of observations contained in a Slice.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Transition Point X c, Transition Point Y c

State Segmentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#StateSegment

A State Segment is a type of Segment where the data remains relatively stable over time, with no significant trends or seasonal patterns. It typically represents a steady state or period of minimal change.
has super-classes
Segment c
is disjoint with
Linear Segment c, Non Linear Segment c

Structuration Methodc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#StructurationMethod

A Structuration Method is a technique used to give structure to a time series by identifying meaningful components, such as Segments and Transition Points.
has sub-classes
Segmentation Method c, Transition Point Detection Method c
is in domain of
has Structuration Method Description dp
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

Structured Componentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#StructuredComponent

A Structured Component is a type of Component used to build a Structured Trajectory.
has super-classes
Component c
has sub-classes
Segment c, Transition Point c
is disjoint with
Raw Component c, Thematic Component c

Structured Trajectoryc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#StructuredTrajectory

A Structured Trajectory results from organizing a Raw trajectory into a more structured format. It alternates between a chronologically ordered sequence of Segments and Transition Points, always concluding with a Segment. If no Transition Point is detected, the Structured Trajectory consists solely of a single Segment, indicating no transitional changes within the sequence.
has super-classes
Trajectory c
is in domain of
calculated Using Segment Method op, calculated Using Transition Point Method op, has Segment op, has Total Segments dp, has Total Transition Points dp, has Transition Point op
is disjoint with
Raw Trajectory c, Thematic Trajectory c

Study Areac back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#StudyArea

A Study Area defines the broader geographical context in which one or more Territorial Units are analyzed.
is in range of
study Area op
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

Temporal Granularityc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TemporalGranularity

Indicates how often measured values occur in a Thematic trajectory. It describes the temporal resolution of the data, such as daily, monthly, or yearly intervals.
is in range of
has Temporal Granularity op
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Scale c, Territorial Unit c, Theme c, Trajectory c

Temporal Scalec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TemporalScale

Defines the temporal coverage of a thematic trajectory by specifying the time of year it represents. Examples include Winter, Spring, Summer, Autumn or All Seasons.
is in range of
has Temporal Scale op
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Territorial Unit c, Theme c, Trajectory c

Territorial Unitc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TerritorialUnit

A Territorial Unit (TU) represents a geographically defined area, typically aligned with the lowest level of administrative division (e.g., municipalities, sub-districts, or townships). Although spatially fixed, a TU may undergo changes over time due to environmental or socioeconomic dynamics. To manage temporal variations in boundary definitions, the ontology reuses the tsn:UnitVersion class from the TSN ontology, which captures stable representations of a Territorial Unit during specific periods. Each TU is associated with one or more Semantic Trajectories of Territorial Transformation (SeTTs).
has super-classes
is in domain of
area In H An Lake dp, area In M2 dp, country op, has Se T T op, max Elevation Meters dp, max Slope Degrees dp, mean Elevation Meters dp, mean Slope Degrees dp, min Elevation Meters dp, min Slope Degrees dp, std Elevation Meters dp, std Slope Degrees dp, study Area op, total Area In M2 dp
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Theme c, Trajectory c

Thematic Componentc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#ThematicComponent

A Thematic Component is a type of Component used to build a Thematic Trajectory.
has super-classes
Component c
has sub-classes
Episode c, Event c
is in domain of
has Semantic Annotation op
is disjoint with
Raw Component c, Structured Component c

Thematic Trajectoryc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#ThematicTrajectory

A Thematic Trajectory is a semantically enriched representation of a Territorial Unit's (TU) trajectory, associated with a specific theme. It is derived from the annotation of a Structured Trajectory and alternates between a chronologically ordered sequence of Episodes and Events, always concluding with an Episode. A Thematic Trajectory consists solely of a single Episode if no Event is present.
has super-classes
Trajectory c
is in domain of
has Episode op, has Event op, has Semantic Annotation Criteria op, has Temporal Granularity op, has Temporal Scale op, has Theme op, has Total Episodes dp, has Total Events dp
is in range of
has Thematic Trajectory op
is disjoint with
Raw Trajectory c, Structured Trajectory c

Themec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Theme

A Theme characterizes the subject of a Thematic trajectory, providing a descriptive label for the whole trajectory.
is in range of
has Broader Theme op, has Theme op
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Trajectory c

Trajectoryc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#Trajectory

A Trajectory represents the synthesized temporal evolution of a Territorial Unit (TU) based on observed data. It serves as an abstract concept that underlies the Raw, Structured, and Thematic trajectories, providing a unified view of change over time.
has sub-classes
Raw Trajectory c, Structured Trajectory c, Thematic Trajectory c
is disjoint with
Attribute c, Component c, Country c, Indicator c, SeTT c, Semantic Annotation c, Semantic Annotation Criteria c, Structuration Method c, Study Area c, Temporal Granularity c, Temporal Scale c, Territorial Unit c, Theme c

Transition Pointc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TransitionPoint

A Transition Point represents a change in the trajectory that causes a discontinuity between Segments or Slices. It occurs at a specific moment in time and is described using attributes that characterize the nature of the transition.
has super-classes
Structured Component c
has sub-classes
Break Point c, Inflexion Point c, Interruption Point c, Regime Change Point c
is in domain of
transition Point Delimit Slice op
is in range of
event Is Annotated From op, has Transition Point op
is disjoint with
Segment c

Transition Point Detection Methodc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TransitionPointDetectionMethod

A Transition Point Detection Method is a technique used to detect changes in a time series by identifying Transition Points, such as Break Points or Inflexion Points. These methods analyze patterns in the data to determine when significant shifts occur.
has super-classes
Structuration Method c
has sub-classes
B E A S T c, B F A S T c, B F A S T Lite c, B F A S T Monitor c, Binseg c, C C D C c, D B E S T c, H M M c, P E L T c
is in range of
calculated Using Transition Point Method op

Transition Point Magnitudec back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TransitionPointMagnitude

Transition Point Magnitude quantifies the intensity of change at a Transition Point, such as a Breakpoint. It is computed as the difference between the value at the point and the value immediately before or after it, depending on how the segment is defined.
has super-classes
External Attribute c
is disjoint with
Event Explanatory Factor c, Segment Gradual Magnitude c, Segment p-value c, Transition Point Probability c

Transition Point Probabilityc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TransitionPointProbability

Transition Point Probability expresses the likelihood that a Transition Point has occurred, based on statistical analysis.
has super-classes
External Attribute c
is disjoint with
Event Explanatory Factor c, Segment Gradual Magnitude c, Segment p-value c, Transition Point Magnitude c

Transition Point Xc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TransitionPointX

Transition Point X denotes the x-coordinate, i.e., time value, where a Transition Point occurs in the trajectory.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point Y c

Transition Point Yc back to ToC or Class ToC

IRI: http://purl.org/net/sett/vocab#TransitionPointY

Transition Point Y denotes the y-coordinate, i.e., the measured value, at which a Transition Point occurs in the trajectory.
has super-classes
Intrinsic Attribute c
is disjoint with
Episode End Date c, Episode Start Date c, Event Date c, Segment Duration c, Segment End X c, Segment End Y c, Segment Slope Direction c, Segment Slope Intercept c, Segment Slope Magnitude c, Segment Start X c, Segment Start Y c, Slice End Observation c, Slice Start Observation c, Slice Total Observations c, Transition Point X c

Object Properties

calculated Using Segment Methodop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#calculatedUsingSegmentMethod

has domain
Structured Trajectory c
has range
Segmentation Method c
is inverse of
is Used As Segment Method For op

calculated Using Transition Point Methodop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#calculatedUsingTransitionPointMethod

has domain
Structured Trajectory c
has range
Transition Point Detection Method c
is inverse of
is Used As Transition Point Method For op

countryop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#country

has domain
Territorial Unit c
has range
Country c
is inverse of
is Country Of op

defines Criteria Forop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#definesCriteriaFor

has domain
Semantic Annotation Criteria c
has range
Semantic Annotation c
is inverse of
is Defined By Criteria op

episode Is Annotated Fromop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#episodeIsAnnotatedFrom

has domain
Episode c
has range
Segment c
is inverse of
segment Annotates Episode op

event Is Annotated Fromop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#eventIsAnnotatedFrom

has domain
Event c
has range
Transition Point c
is inverse of
transition Point Annotates Event op

gives Data Toop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#givesDataTo

is inverse of
takes Data From op

has Attributeop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasAttribute

has sub-properties
has External Attribute op, has Intrinsic Attribute op
has domain
Component c
has range
Attribute c
is inverse of
is Attribute Of op

has Broader Themeop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasBroaderTheme

has domain
SeTT c
has range
Theme c
is inverse of
is Broader Theme Of op

has Episodeop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasEpisode

has domain
Thematic Trajectory c
has range
Episode c
is inverse of
is Episode Of op

has Eventop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasEvent

has domain
Thematic Trajectory c
has range
Event c
is inverse of
Is Event Of op

has Explanatory Factorop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasExplanatoryFactor

has domain
Event c
has range
Event Explanatory Factor c
is inverse of
is Explanatory Factor Of op

has External Attributeop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasExternalAttribute

has super-properties
has Attribute op
has domain
Component c
has range
External Attribute c
is inverse of
is External Attribute Of op

has Intrinsic Attributeop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasIntrinsicAttribute

has super-properties
has Attribute op
has domain
Component c
has range
Intrinsic Attribute c
is inverse of
is Intrinsic Attribute Of op

has Se T Top back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasSeTT

has domain
Territorial Unit c
has range
SeTT c
is inverse of
is Se T T Of op

has Segmentop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasSegment

has domain
Structured Trajectory c
has range
Segment c
is inverse of
is Segment Of op

has Semantic Annotationop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasSemanticAnnotation

has domain
Thematic Component c
has range
Semantic Annotation c
is inverse of
is Semantic Annotation Of op

has Semantic Annotation Criteriaop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasSemanticAnnotationCriteria

has domain
Thematic Trajectory c
has range
Semantic Annotation Criteria c
is inverse of
is Semantic Annotation Criteria Of op

has Sliceop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasSlice

has domain
Raw Trajectory c
has range
Slice c
is inverse of
is Slice Of op

has Temporal Granularityop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasTemporalGranularity

has domain
Thematic Trajectory c
has range
Temporal Granularity c
is inverse of
is Temporal Granularity Of op

has Temporal Scaleop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasTemporalScale

has domain
Thematic Trajectory c
has range
Temporal Scale c
is inverse of
is Temporal Scale Of op

has Thematic Trajectoryop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasThematicTrajectory

has domain
SeTT c
has range
Thematic Trajectory c
is inverse of
is Thematic Trajectory Of op

has Themeop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasTheme

has domain
Thematic Trajectory c
has range
Theme c
is inverse of
is Theme Of op

has Transition Pointop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#hasTransitionPoint

has domain
Structured Trajectory c
has range
Transition Point c
is inverse of
is Transition Point Of op

indicator Monitored Byop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#indicatorMonitoredBy

is inverse of
monitors Indicator op

is Attribute Of Semantic Annotationop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#isAttributeOfSemanticAnnotation

is inverse of
semantic Annotation Based On Attribute op

Is Event Ofop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#IsEventOf

is inverse of
has Event op

is External Attribute Ofop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#isExternalAttributeOf

has super-properties
is Attribute Of op
is inverse of
has External Attribute op

is Intrinsic Attribute Ofop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#isIntrinsicAttributeOf

has super-properties
is Attribute Of op
is inverse of
has Intrinsic Attribute op

is Study Area Ofop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#isStudyAreaOf

is inverse of
study Area op

monitors Indicatorop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#monitorsIndicator

has domain
Raw Trajectory c
has range
Indicator c
is inverse of
indicator Monitored By op

segment Is Derivated Fromop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#segmentIsDerivatedFrom

has domain
Segment c
has range
Slice c
is inverse of
slice Used To Derivate Segment op

semantic Annotation Based On Attributeop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#semanticAnnotationBasedOnAttribute

has domain
Semantic Annotation c
has range
Attribute c
is inverse of
is Attribute Of Semantic Annotation op

slice Delimited Byop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#sliceDelimitedBy

is inverse of
transition Point Delimit Slice op

study Areaop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#studyArea

has domain
Territorial Unit c
has range
Study Area c
is inverse of
is Study Area Of op

takes Data Fromop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#takesDataFrom

has domain
Indicator c
has range
Indicator c
is inverse of
gives Data To op

transition Point Delimit Sliceop back to ToC or Object Property ToC

IRI: http://purl.org/net/sett/vocab#transitionPointDelimitSlice

has domain
Transition Point c
has range
Slice c
is inverse of
slice Delimited By op

Data Properties

area In H An Lakedp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#areaInHAnLake

has domain
Territorial Unit c
has range
float

area In M2dp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#areaInM2

has domain
Territorial Unit c
has range
float

has Annotation Criteria Descriptiondp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasAnnotationCriteriaDescription

Provides a description of the semantic annotations- For instance, the thresholds used to classify certain values (e.g., slight, medium, strong) based on a given attribute.
has domain
Semantic Annotation Criteria c
has range
string

has Attribute Valuedp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasAttributeValue

has domain
Attribute c
has range
Literal

has Indicator Descriptiondp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasIndicatorDescription

has domain
Indicator c
has range
string

has Indicator Formuladp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasIndicatorFormula

has domain
Indicator c
has range
string

has Sequence Orderdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasSequenceOrder

has characteristics: functional

has domain
Component c
has range
integer

has Structuration Method Descriptiondp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasStructurationMethodDescription

has domain
Structuration Method c
has range
string

has Total Episodesdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasTotalEpisodes

has domain
Thematic Trajectory c
has range
integer

has Total Eventsdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasTotalEvents

has domain
Thematic Trajectory c
has range
integer

has Total Segmentsdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasTotalSegments

has domain
Structured Trajectory c
has range
integer

has Total Slicesdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasTotalSlices

has domain
Raw Trajectory c
has range
integer

has Total Transition Pointsdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#hasTotalTransitionPoints

has domain
Structured Trajectory c
has range
integer

max Elevation Metersdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#maxElevationMeters

has domain
Territorial Unit c
has range
float

max Slope Degreesdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#maxSlopeDegrees

has domain
Territorial Unit c
has range
float

mean Elevation Metersdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#meanElevationMeters

has domain
Territorial Unit c
has range
float

mean Slope Degreesdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#meanSlopeDegrees

has domain
Territorial Unit c
has range
float

min Elevation Metersdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#minElevationMeters

has domain
Territorial Unit c
has range
float

min Slope Degreesdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#minSlopeDegrees

has domain
Territorial Unit c
has range
float

std Elevation Metersdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#stdElevationMeters

has domain
Territorial Unit c
has range
float

std Slope Degreesdp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#stdSlopeDegrees

has domain
Territorial Unit c
has range
float

total Area In M2dp back to ToC or Data Property ToC

IRI: http://purl.org/net/sett/vocab#totalAreaInM2

has domain
Territorial Unit c
has range
float

Legend back to ToC

c: Classes
op: Object Properties
dp: Data Properties

Acknowledgments back to ToC

The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.