Encompasses dimensions related to the ability to access to and retrieve the dataset required for a particular use case
Refers to dimensions that are independent of the user's context and that measure the correctness, succinctness and consistency of the dataset
Dimensions belonging to this group focus on the perceived trustworthiness of the dataset and its sources
Dimensions in this category provide information about how current is the data (i.e. its freshness over time) and how frequently it changes
Comprises dimensions that highly depend on the context of the task to be performed
Groups dimensions related to the design of the data, which provide information about how the chosen representation of the data affect its quality
Reputation dimensions related to the reputation of the data, which provide information about how the reputable the data is based on its providers and host
Metrics in this dimension measure the extent to which information (or some portion of it) is present, obtainable and ready for use
Indicates whether consumers of the dataset are explicitly granted permissions to use it, under defined conditions (if any)
Refers to the extent to which data is protected against illegal alteration and it's authenticity can be guaranteed and to the confidentiality of the communication between a source and its consumers
Assesses the efficiency with which a system can bind to the dataset and get access to the information contained into it
Refers to the degree to which entities that represent the same concept are linked to each other, be it within or between two or more data sources.
Extent to which data is correct. The degree to which the dataset correctly represents the real world and how much it is free of syntax errors. Classified in: Syntactic accuracy (the degree to which data values are close to their definition domain) and Semantic accuracy (the degree to which data values correctly represent the actual real world values)
Refers to how appropriate the quantity and volume of data is for the task at hand. The amount of data should be enough to approximate the true scenario precisely
Consistency means that a knowledge base is free of (logical/formal) contradictions with respect to particular knowledge representation and inference mechanisms
Refers to the redundancy of entities, be it at the schema or the data level
Measures the extent to which the representation of data is compact, clear and well formatted
Provides a measure of the degree to which information is up to date and how promptly the data is updated
Refers to the frequency with which data varies in time
Indicates how up-to-date the data is, relative to the specific task at hand
Refers to the easy with which data can be compreshended without ambiguity and used by a human data consumer
Checks whether the server (endpoint) is reachable and responds to a SPARQL query
Availability of the SPARQL end-point metric
Upon request of an RDF dump, checks whether it is provided as result
Determines whether requesting a resource, identified by a URI, results in an error code being returned (e.g. 4xx: client error or 5xx: server error), or in a broken link
Detects dead links or URIs without any supporting RDF metadata or no redirection using the status code 303
Detects all local in-links or back-links (locally available triples with the resource URI appearing as object, in the dereferenced document returned for the resource)
Detects all forward links (locally known triples where the local URI is mentioned in the subject)
Dereferenceability of forward-links metric
Checks whether the content is suitable for consumption and if such content should be accessed
Verifies that the resource is annotated with a machine-readable indication of the license (e.g. a VoID description or dcterms:license property)
Machine-readable indication of a license metric
Verifies whether a human-readable text, stating the licensing model attributed to the resource, has been provided as part of the dataset
Human-readable indication of a license metric
Detects whether the work is attributed by the author under a CopyLeft license, which guarantees that free access to the resource and any modified versions of it, will always be provided
Measures the delay between the submission of a request to the data source and the reception of the respective response (or the first part of it)
Measures the number of answered HTTP requests responsed by the source of the dataset, per second
Determines whether the time required to answer a set of N requests divided by N, is not longer than the time it takes to answer a single request
Determines whether the extent to which hash URIs are used instead of slash URIs, as the latter usually imply that 303 redirects must be performed to gather all the elements described in the dataset
Detects ill-typed literals, which do not abide by the lexical syntax of their respective datatypes
Detects literals incompatible with range data type
Detects outliers or conflicts of literal datatypes. Since it is meant to measure the homogeneity and not the validity possible rdfs:range restrictions are not evaluated
Find resources that are - defined as a property but also appear on subject or object positions in other triples (except cases like ex:prop rdf:type rdfs:Property, ex:prop rds:subPropetyOf) - defined as a class but also appear on predicate position in other triples. The metric is computed as a ratio of misplaced classes and properties
Detect properties that are defined as a owl:datatype property but is used as object property and properties defined as a owl:object property and used as datatype property The metric is computed as a ratio of misused properties
Misuse Owl datatype or object properties metric
Detects the redefinition by third parties of external classes/properties such that reasoning over data using those external terms is affected
Counts the total number of triples present in the dataset
the ratio of entities described as members of disjoint classes (here: classes explicitly known as disjoint) to the total number of entities described in the dataset
Entities as members of disjoint classes metric
Provides a measure of the redundancy of the dataset at the schema level, computed as the ratio of the Number of Unique Attributes (Properties) to the Total Number of Attributes in the target schema
Provides a measure of the redundancy of the dataset at the data level, computed as the ratio of the Number of Unique Subjects to the Total Number of Subjects
Provides a measure of the redundancy of entities at the data level (ratio of entities that violate the uniqueness rule)
Detects the use of short URIs (and the avoidance of query parameters), which suggests that information is compactly represented and favors readability
Compares the time when the data was observed with the time when the data (document as a whole and individual triples) were last modified, thereby providing a measure of how current the dataset is
Provides a measure of the degree to which information is up to date, by comparing the current time with the time when the data was last modified
Provides a measure of the degree to which information is up to date, by comparing the total number of resources, described by the dataset, versus the number of those that are recognized to be outdated
Measures the frequency with which data varies over time, by calculating the length of the time interval during which data remains valid.
Assesses the difference between the last modified time of the original data source and the last modified time of the semantic web source, thereby indicating if the resource is outdated
Assesses the percentage of entities having an rdfs:label or rdfs:comment
EmptyAnnotationValue consider the following widely used annotation properties (labels, comments, notes, etc.) and identifies triples whose property is from a pre-configured list of annotation properties, and whose object is an empty string
Labels using capitals identifies triples whose property is from a pre-configured list of label properties, and whose object uses a bad style of capitalization
Whitespace in annotation consider the following widely used annotation properties (labels, comments, notes, etc.) and identifies triples whose property is from a pre-configured list of annotation properties, and whose object value has leading or ending white space in string.
Detects non reputable resources by retrieving URI of resources from data sets and comparing them with URI found in reputable resources.
This is a complex metric that detects good quality interlinks by measuring the (i) interlink degree; (ii) clustering coefficient; (iii) centrality; (iv) open sameAs chains; (v) sameAs description richness
Measures the degree to which the resource is linked to external data providers, that is, refers to the detection of links that connect the resource to external data provided by another data sources
Existence of links to external data providers
Links Accessibility Category with Availability Dimension
Accessibility has availability dimension
Links Availability Dimension with Endpoint Availability Metric (Endpoint Availability Metric belongs to the Availability Dimension)
Availability has end-point availability metric
Links Availability Dimension with RDF Availability Metric (RDF Availability Metric belongs to the Availability Dimension)
Availability has RDF availability metric
Links Availability Dimension with Dereferenceability Metric (Dereferenceability Metric belongs to the Availability Dimension)
Availability has dereferenceability metric
Links Availability Dimension with Unstructured Data Metric (Unstructured Data Metric belongs to the Availability Dimension)
Availability has no structured data available metric
Links Availability Dimension with Dereferenceability of Back-links Metric (Dereferenceability of Back-links Metric belongs to the Availability Dimension)
Availability has Dereferenceability of back-links metric
Links Availability Dimension with Dereferenceability of Forward-links Metric (Dereferenceability of Forward-links Metric belongs to the Availability Dimension)
Availability has Dereferenceability of forward-links metric
Links Availability Dimension with Misreported Content Types Metric (Misreported Content Types Metric belongs to the Availability Dimension)
Availability has misreported content types metric
Links Accessibility Category with Licensing Dimension
Links Licensing Dimension with Machine-readable Indication of a License Metric (Machine-readable Indication of a License Metric belongs to the Licensing Dimension)
Licensing has machine-readable indication of a license metric
Links Licensing Dimension with Human-readable Indication of a License Metric (Human-readable Indication of a License Metric belongs to the Licensing Dimension)
Licensing has human-readable indication of a license metric
Links Licensing Dimension with Indication of Attribution CopyLeft Metric (Indication of Attribution CopyLeft Metric belongs to the Licensing Dimension)
Licensing has indication of attribution CopyLeft metric
Links Accessibility Category with Security Dimension
Links Accessibility Category with Performance Dimension
Links the Performance Dimension with Low Latency Metric (Low Latency Metric belongs to the Performance Dimension)
Links Performance Dimension with High Throughput Metric (High Throughput Metric belongs to the Performance Dimension)
Links Performance Dimension with Scalability of a Data Source Metric (Scalability of a Data Source Metric belongs to the Performance Dimension)
Performance has scalability of a data source metric
Links Performance Dimension with No Usage of Slash URIs Metric (No Usage of Slash URIs Metric belongs to the Performance Dimension)
Performance has no usage of slash URIs metric
Links Accessibility Category with Interlink Dimension
Links the Interlinking Dimension with Existence of Links to External Data Providers Metric (Existence of Links to External Data Providers Metric belongs to the Interlinking Dimension)
Interlink has existence of links to external data providers metric
Links Intrinsic Category with Accuracy Dimension
Links Accuracy Dimension with Malformed Data Type Literals Metric (Malformed Data Type Literals Metric belongs to the Accuracy Dimension)
Accuracy has malformed data type literals metric
Links Accuracy Dimension with Incompatible Datatype Range Metric
Links Consistency Dimension with Homogeneous data types Metric
Links Consistency Dimension with Undefined classes metric
Links Consistency Dimension with Undefined properties metric
Links Consistency Dimension with Misuse Owl- datatype or object properties metric
Links Consistency Dimension with misplaced classes or properties metric
Links Contextual Category with Amount of Data Dimension
Links Amount of Data Dimension with Amount of Triples Metric (Amount of Triples Metric belongs to the Amount of Data Dimension)
Amount of Data has amount of triples metric
Links Intrinsic Category with Consistency Dimension
Links Consistency Dimension with ‘entities as members of disjoint classes’ Metric (Entities as Members of Disjoint Classes Metric belongs to the Consistency Dimension)
Consistency has entities as members of disjoint classes metric
Links Intrinsic Category with Conciseness Dimension
Links Conciseness Dimension with Intensional Conciseness Metric (Intensional Conciseness Metric belongs to the Conciseness Dimension)
Conciseness has intensional conciseness metric
Links Conciseness Dimension with Extensional Conciseness Metric (Extensional Conciseness Metric belongs to the Conciseness Dimension)
Conciseness has extensional conciseness metric
Links Conciseness Dimension with Duplicate Instance Metric (Duplicate Instance Metric belongs to the Conciseness Dimension)
Conciseness has duplicate instance metric
Links Representational Category with Representational-Conciseness Dimension
Representational has representational conciseness dimension
Links Representational-Conciseness Dimension with Keeping URIs Short Metric (Keeping URIs Short Metric belongs to the Representational-Conciseness Dimension)
Representational conciseness has short URIs metric
Links Representational Category with Understandability Dimension
Links Understandability Dimension with Human Readable Labelling Metric (Human Readable Labelling belongs to the Understandability Dimension)
Links Understandability Dimension with Empty annotation value metric
Understandability has empty annotation value metric
Links Understandability Dimension with labels using capitals metric
Understandability has labels using capitals metric
Links Understandability Dimension with Whitespace in annotation
Understandability has whitespace in annotation
Links the Dynamicity Category with the Currency Dimension
Links the Currency Dimension with the Currency of Document/Statements Metric (Currency of Document/Statements Metric belongs to the Currency Dimension)
Currency has currency of document/statements metric
Links the Currency Dimension with the Time Since Modification Metric (Time Since Modification Metric belongs to the Currency Dimension)
Currency has time since modification metric
Links the Currency Dimension with the Exclusion of Outdated Data Metric (Exclusion of Outdated Data Metric belongs to the Currency Dimension)
Currency has exclusion of outdated data metric
Links the Dynamicity Category with the Volatility Dimension
Links the Volatility Dimension with the Time Validity Interval Metric (Time Validity Interval Metric belongs to the Volatility Dimension)
Volatility has time validity interval metric
Links the Dynamicity Category with the Timeliness Dimension
Links the Timeliness Dimension with the Timeliness of the Resource Metric (Timeliness of the Resource Metric belongs to the Timeliness Dimension)
Timeliness has timeliness of resource metric
Links Reputation category with Reputation of dataset metric
Reputation category has reputation of dataset metric
Links Conciseness Dimension with Ontology Versioning Conciseness Metric
Provides a measure for checking singleton instances of the use-case specific defined owl:ontologyVersion property
Links Understandability Dimension with Low Blank Nodes Usage Metric
Understandability has low blank nodes usage metric
Provides a measure for the usage of blank nodes in a dataset
Links Consistency Dimension with Obsolete Concepts In Ontology Metric
Understandability has obsolete concepts in ontology metric
Provides a measure for the number of classes and properties in an ontology which are marked as depricated. If an ontology is making lots of obsolete concepts between different versions, then this is an indicator that the ontology is going through a lot of changes, and is potentially in a state of poor quality
Links Accuracy Dimension with Synonym Usage Metric
Measures the number of classes which has a synonym <efo:alternative_term> described.
Links Accuracy Dimension with POBO Definition Usage Metric
Accuracy has POBO definition usage metric
Provides a measure for an Ontology checking the usage of <pobo:def> in defined classes.
Accuracy has defined ontology author metric
Checks whether the creator <efo:creator> is defined in the ontology.
Verifies if access to the dataset is performed through a sound, HTTPS/SSL connection and thus, connection is confidential
Links security dimension with access to data through HTTPS metric
Security has access to data through HTTPS metric
Links Reputation category with OBO foundry metric
Reputation category has OBO foundry metric