INSPIRE
Infrastructure for Spatial Information in Europe
Data quality in INSPIRE: from requirements to
metadata
Discussion paper
Title
Data quality in INSPIRE: from requirements to metadata - Discussion paper
Creator
European Commission
Date
2010-05-11
Subject
Data quality and metadata
Publisher
European Commission
Type
Text
Description
The aim of this discussion paper is to outline the process of addressing the topic of
data quality, to provide background information for the discussion, and to invite the
INSPIRE (Data Quality) Member States Points of Contact to answer a number of
questions which will help structuring the discussion.
Contributor
Katalin Tóth, Robert Tomas, Vanda Nunes de Lima, Paul Smits, Antti Jakobsson,
Gilles Troispoux, Carol Aigus
Format
MS Word (doc)
Source
Rights
INSPIRE Member States Contact Points
Identifier
INSPIRE_DQ_MD_v1 8
Language
En
Relation
n/a
Coverage
Project duration
Data quality in INSPIRE: from requirements to metadata
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Table of contents
Foreword .................................................................................................................................. 3
1
Introduction....................................................................................................................... 4
1.1
References and Further Readings ........................................................................... 5
2
Objectives and process ................................................................................................... 6
3
Two faces of data quality: quality requirements and metadata .................................. 7
4
Experience of INSPIRE Annex I data specification process ...................................... 10
4.1
4.2
5
Data Quality Requirements / Recommendations ................................................... 12
Metadata on data quality ........................................................................................ 12
Points for discussion ..................................................................................................... 15
List of Abbreviations
DQ
EC
GCM
INSPIRE
ISO
MD
NMCA
SDI
TWG
Data Quality
European Commission
Generic Conceptual Model
Infrastructure for Spatial Information in Europe
International Standards Organisation
Metadata
National Mapping and Cadastre Agencies
Spatial Data Infrastructure
Thematic Working Group
Data quality in INSPIRE: from requirements to metadata
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Foreword
In the process of the development and adoption of the draft INSPIRE Implementing Rules for
interoperability of spatial data sets and services, it became apparent that further discussion is
needed to better understand and address the aspects of data quality in the context of
INSPIRE. The Commission agreed to initiate and lead this discussion.
At the meeting of the INSPIRE Member States Contact Points on 10 March 2010, the contact
points were requested to inform the Commission as to who will represent the countries in the
discussion on data quality. The discussion with the data quality experts will take place on 22
June 2010 in Krakow, Poland.
The aim of this discussion paper is to outline the process of addressing the topic of data
quality, to provide background information for the discussion, and to invite the INSPIRE (Data
Quality) Member States Points of Contact to answer a number of questions which will help
structuring the discussion.
The document will be publicly available as a ‘non-paper’, as it does not represent an official
position of the Commission, and as such can not be invoked in the context of legal
procedures.
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Introduction
On 14 December 20009 the INSPIRE Committee approved unanimously the draft Regulation
on Interoperability of Data Sets and Services for INSPIRE Annex I data themes. In the
process of developing this draft Regulation, which is based on the INSPIRE data specification
guidelines developed by the Thematic Working Groups (TWGs), the question of data quality
was a re-occurring issue, both during the data specifications development and the
consultations.
During the above mentioned INSPIRE Committee meeting and following a discussion during
the presentation of the proposal for a regulation on Interoperability of Data Sets and Services
for INSPIRE Annex I data themes, the European Commission committed to organize a large
consultation with the Member States on data quality.
This interest can be explained by the fact that quality is one of the data harmonisation
components underpinning interoperability. The peculiarity of the discussion was the widely
diverging of opinions, ranging from introducing strict data quality requirements for all data
included in the infrastructure, to complete omission of requirements.
During the discussions it became clear that the a-priori data quality requirements need to be
carefully distinguished from metadata.
The draft data specifications of each Annex I theme (v 2.0) have been consulted with
stakeholders’ communities. The comments related to data quality and metadata parts have
been addressed by the Thematic Working Groups responsible for the specification process.
The results have been incorporated in v 3.0 that has been used as technical basis of the draft
Regulation on Interoperability of spatial data sets and services. The draft Regulation has been
distributed to the members of the INSPIRE Committee, where two concerns have been
raised:
-
How is the comparability of information derived from different spatial data sets
ensured in the draft Regulation? The answer of the Commission pointed out the
rigorous and common data modelling principles addressed all interoperability/ data
harmonisation components of the Generic Conceptual Model (GCM). It was agreed
that the parts related to data quality and metadata have to be reviewed.
-
The recommendation to apply a minimal absolute geometric accuracy (to be less then
2/1000 of the distance resolution). The Commission did not accept this general
approach. The agreement was that the issue should be further explored in relation to
the different data themes.
Following these concerns, the EC INSPIRE Team agreed to initiate and lead this discussion.
This paper prepares and guides the discussions on the above two topics, clarifying the details
and giving an initial position to stimulate the exchange of views. It is expected that the results
of the discussions can be useful for the process of development of data specifications of
Annex I, II and III data themes, and that they will be considered in future updates of other
INSPIRE documents.
The remainder of this paper is organized as follows. Section 2 gives an overview of the main
objectives of and the process for the discussions. Section 3 introduces the topic of data
quality and metadata. Section 4 reports on previous experience on data quality in INSPIRE,
followed by the discussion points (section 5).
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1.1 References and Further Readings
INSPIRE Directive
INSPIRE Generic Conceptual Model
INSPIRE Methodology
INSPIRE Data Specifications – Guidelines
In order to facilitate discussion on the data quality and metadata here are some references
from different theme communities:
GEO Task DA-09-01 Data Management Subtask a.: GEOSS Quality Assurance Strategy:
http://www.grouponearthobservations.org/cdb/geoss_imp.php
World Meteorological Organisation:
www.wmo.int/pages/prog/www/WDM/wdm.html
Global Spatial Data Infrastructure Association:
www.gsdi.org/gsdiconf/gsdi11/papers/pdf/283.pdf
Quality Assurance Framework for Earth Observation:
http://lpvs.gsfc.nasa.gov/PDF/qa4eo_guide.pdf
http://qa4eo.org/documentation.html
INSPIRE, Data Quality and SDIs:
www.directionsmag.com/article.php?article_id=3380
Q-KEN - EuroGeographics WG on quality:
www.eurogeographics.org/about/quality
ESDIN – EU eContentPlus project:
www.esdin.eu
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2 Objectives and process
The INSPIRE data quality and metadata discussions are expected to reach the following
objectives:
1. Find evidence whether specifying data quality requirements are appropriate for
INSPIRE;
2. If yes, propose data quality elements, measures, and target values;
3. Fix how metadata on data quality has to be presented;
4. Provide guidance on DQ requirements and Metadata for Annex I, II and III
5. Formulate proposals amending the INSPIRE data specification template, if
appropriate
6. Raise awareness about the role of data quality and metadata in spatial data
infrastructures.
For reaching these objectives it is necessary to channel information exchange through a few
steps, which are expected to reach agreements in a bottom up manner:
1. Drafting the discussion paper
The discussion paper is expected to scope the subjects, clarify the terminology,
review the initiative already in place and propose an initial position on the subject.
The discussion paper is developed by the European Commission supported by a
small group of experts.
2. Consultations in the Member States (Until 11 June 2010)
The discussion paper will be sent for consultation in the Members States via their
nominated data quality contact points, who are kindly invited to organise the review to
reach an agreed and consolidated position in their countries. In order to reach a
structured result, specific questions will be asked. The DQ contact points are
expected to send back to the Commission the answers to these questions as well
comments to this document and if necessary propose additional issues to be
considered.
3. Analysis of the results of the consultation (14-18 June 2010)
The answers received by the Commission will be analyzed. The outcome of this step
will be a draft report, which will be prepared by the drafting group of the discussion
paper. Wherever possible, it will synthesise the responses, but it will also highlight the
issues where further discussions are needed. The draft report will be sent back to the
national DQ contact points.
4. Face-to-face discussion (22 June 2010)
The DQ contact points will be invited to the workshop in Krakow on 22 June 2010,
back to back with the annual INSPIRE Conference. They will represent the official
position of their countries, and may be asked, as part of preparation to the meeting, to
give a presentation.
5. Final report
The draft report will be updated with the results of the Krakow DQ workshop and will
be disseminated to a wider public. It will provide recommendations for possible
updates of INSPIRE documents and how data quality and metadata should be
addressed in spatial data infrastructures in general. In may also involve creating a
discussion platform that will help to keep the recommendations of the report up to
date.
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3 Two faces of data quality: quality requirements and
metadata
INSPIRE, like any Spatial Data Infrastructure, will result in data from different providers being
consumed by multiple users and applications through the INSPIRE infrastructure. The
INSPIRE Directive applies to spatial data held by or on behalf of public authorities and to the
use of spatial data by public authorities in the performance of their public tasks. Therefore, the
aspects of quality trust and confidence in the data made available through the infrastructure is
touching many different data producers, transformers, and users.
One may therefore expect that the data affected by INSPIRE is linked to existing formal or
informal data quality requirements at national or sub-national (or supra-national) levels. These
data quality requirements, which are normally the basis for the production of the data, the
quality control, the quality evaluation and the conformance testing, are ideally reported as
metadata.
Before starting discussing data quality requirements and metadata in the context of INSPIRE
it is necessary to clarify their role in spatial data/information infrastructures in general. The
SDI provides the technical and legal framework for accessing and reusing spatial data
produced in a defined geographical zone (global, national, and sub-national), or thematic
field. It is assumed that SDIs are initially built on existing data that are produced by different
data providers. The flow of data from the data producers to their provision within an SDI is
shown in Figure 1.
Data is being produced to fulfil specific use-cases, i.e. to satisfy the requirements of users
connected to well-defined tasks. These requirements are optimally formalised in data product
specification, which is the basis for data production. As a rule they contain specific parts
related to a priori requirements on data quality to be followed during the production process.
Frequently standards or other regulations drive the data specification and production
processes giving strict target values for selected quality measures. Metadata gives a
posteriori statement about the data quality based on the de-facto measurements or specific
aggregation rules applied to the data set. In summary, in data production process ideally both
data quality requirements and metadata are present.
Conformance statements are also given as part of metadata. They are important part in the
context of data semantics and structures; however do not fully replace metadata on
evaluation and use. Conformance statements are mainly useful to expert users that know the
content of the data product specification used for data production.
An SDI should provide access to data in interoperable way, i.e. without the need for specific
ad-hoc interaction of humans or machines after the data is retrieved from the infrastructure.
The interoperability target that has to be reached before the data is provided to the users is
set in data specifications that have a similar structure to the data product specifications.
However the role of a priori data quality requirements in SDI is different.
When establishing the data component of an SDI, two aspects need to be balanced:
1. Giving access to the widest selection of data;
2. Achieving interoperability at pan-European and cross-border levels.
The background of the first aspect is that the final decision whether a data set is useful is
made by the users. This might lead to data being provided to the infrastructure without the
minimal a priori requirements for the data quality. The underlying principle of this approach is
that any data is better than no data.
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Data flow in Spatial Data Infrastructures
Data production
User
requirements
analysis
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SDI implementation
Definition of the
scope of the
infrastructure
Data product
specification
development
Metadata creation
and maintenance
Data production
and maintenance
Interoperability
target
specification
development
Decision about
including data in
the infrastructure
Data
transformation
(if necessary)
Publication of
(updated)
metadata
Publication of
data
(conformant to
the target
specification)
Figure 1: Data flow in spatial data infrastructures
The second condition, promoting interoperability, implies that data from disparate sources can
be combined without specific efforts. However, when the quality of data is very different, some
data harmonisation measures, for example edge-matching, become meaningless and the
integrated use of data is jeopardised. In addition, SDIs are expected to provide the future
coherent basis for the development of new applications. From these points of view minimal a
priori requirements on data quality are relevant.
Requirements on data quality are usually more stringent for reference data1 especially in
terms of positional accuracy, as the geometries of reference data a frequently used for object
referencing. In addition, in thematic SDIs some fundamental use-cases may also justify such
requirements; otherwise the infrastructure does not reach its objective.
In summary, data quality requirements may play a discriminative role when deciding about
including a specific data set in an SDI. Balancing the wide spread publication of data sets with
requirements against the quality of data is a delicate decision in defining the specifications for
1
Data that can be used for linking other types of (thematic) information.
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interoperability. Consequently data quality requirements may be completely absent from the
target specifications if the main purpose of infrastructure is to make available every existing
data set.
Naturally users have to be informed about the quality of the data that they retrieve from the
infrastructure. Contrary to data quality requirements, metadata on data quality is an
indispensable content of every SDI. The original metadata generated during/after the data
production can be used as the starting point for the infrastructure; however it may need
updating because of the eventual deterioration of data quality due to the transformations
necessary for reaching the interoperability target specifications.
Updating the values of different metadata elements might be cumbersome. In topographic
data production, for example, it can be based on calculations or on quality inspection
models2. For many cases, a practical alternative could be to use the original metadata with
information on the process step describing the transformation methods and the possible
associated errors, expressed in the MD_Lineage element.3
Interoperability also requires that data quality is measured and reported in an agreed way,
otherwise it is not possible to compare the metadata associated to different datasets.
Therefore the metadata part of the interoperability target data specification has to fix the data
quality elements and measures to be used in a data theme. If possible, this needs to be
harmonised across the data themes as well.
From the usability point of view, the significance of the same DQ element is different. As said
before, positional accuracy is more important for reference data than for other thematic data,
while thematic classification correctness is prime importance for some coverage data (e.g.
land cover). Therefore specific attention should be paid in the data specification development
process as to which are the most meaningful or expressive elements to describe the quality of
data.
When a data specification contains DQ measures to express requirements or
recommendations, the same measures should be used in the metadata; therefore the Data
quality and the Metadata clauses of data specifications must be consistent.
The next section reports on the data quality-related experience to-date in the context of
INSPIRE.
2
A model based on ISO data sampling methods is proposed by the ESDIN project.
Report or lineage role metadata element is mandatory when the scope of the DQ element is the
dataset (ISO 19115)
3
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4 Experience of INSPIRE Annex I data specification
process
Apart from logical consistency4, the INSPIRE Directive does not directly spell out
requirements for data quality. However combining spatial data from different sources across
the Community in a consistent way and share them between several users and applications
represents a strong data quality demand. These requirements are supported by the
consequent application of the data modelling elements and other provisions of the INSPIRE
Generic Conceptual Model (GCM). Logical consistency can be established by different
modelling methods like object referencing and constraints. In addition, the GCM lists data
quality among the data harmonisation elements, but no specific details are given.
The draft Regulation on Interoperability of Spatial Data Sets and Services sets a requirement
stating that all updates of data shall be made available in INSPIRE at the latest 6 months after
the change was applied in the source data set 5.
Based on the discussions within and across the TWGs during the process of developing
Annex I data specifications it was decided not to introduce uniform mandatory minimum data
quality requirements. This approach is in compliance with the recommendation of “D2.6
Methodology for development of data specifications” INSPIRE framework document. However
based on the specific requirements of the data theme each TWG has included and described
how data quality has to be presented (see 4.1 and Table 1). In the majority of cases, data
quality information is required at dataset level6 (see 4.2 and Table 1). These
recommendations that are focused on enhancing the interoperability and informing about the
fitness for use of the datasets are based on the analyses of user requirements, use cases and
especially on good practices.
Due to the natural diversity of the data themes, the user requirements, and no common
approach, each TWG proposed slightly different data quality elements and MD elements. At
the end of the process an effort harmonising the proposed MD elements and DQ
recommendations took place. The of this exercise is presented in the Table1 below.
4
Art. 8(4) and Clause 20 of the GCM
Article 6(2)
6 In Cadastral parcels data specification positional accuracy may be also described as an attribute of
spatial objects.However this is fundamentally different to evaluation type of metadata.
5
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Table 1: Summary table of data quality information and related MD elements described/used in Annex I data specification
Data quality element
completeness
Logical consistency
Positional accuracy
Temporal accuracy
Thematic accuracy
Data quality sub-element
Metadata element
AD
AU
CP
GN
commission
omission
conceptual consistency
domain consistency
format consistency
topological consistency
absolute or external accuracy
relative or internal accuracy
temporal consistency
classification correctness
non-quantitative
attribute
correctness
quantitative attribute accuracy
DQ_CompletenessCommission
DQ_CompletenessOmission
DQ_ConceptualConsistency
DQ_DomainConsistency
DQ_FormatConsistency
DQ_TopologicalConsistency
DQ_AbsoluteExternalPositionalAccuracy
DQ_RelativeInternalPositionalAccuracy
DQ_TemporalConsistency
DQ_ThematicClassificationCorrectness
DQ_NonQuantitativeAttributeAccuracy
X
X
X
X
X
X
X
X
X
2X
X
3X**
X
X
2X
HY
PS
TN
X
X
X
X
X
X
2X
X
X
X
X
6X
X
9X
X
X
2X
X
X
X
X
X
DQ_QuantitativeAttributeAccuracy
X
MD_MaintenanceInformation
Maintenance*
3X
3X
3X
3X
3X
3X
3X
* The reason for inclusion of Maintenance information is the fact that information about the update frequency and the scope is related to the temporal
accuracy of a resource. Thus, it is related to the data quality of a dataset in general.
** It is only expressed as recommendations without given corresponding MD-DQ element/measure (Lineage template)
Legend:
X
data quality measure used in a data quality sub-element / Nr. of measures
X
mandatory MD element (only one measure)
AD
Addresses TWG
AU
Administrative units TWG
CP
Cadastral parcels TWG
GN
Geographical names TWG
HY
Hydrography TWG
PS
Protected sites TWG
TN
Transport networks TWG
4.1 Data Quality Requirements / Recommendations
Recommendations related to data quality information that applies to all Annex I data themes has
been taken from D2.6 “Methodology for Data Specification Developments”. It states that ideally the
data quality information has to be collected at the level of spatial object types and has to be
aggregated to the dataset (series) level metadata7
Apart from the list of data quality elements and related MD elements (Table 1) each TWG adopted
several requirements and/or recommendations related to data quality and use of MD elements that are
listed below.
Cadastral parcels:
- Rate of missing items should be 0% for cadastral parcels and cadastral zonings (if any).
- Mean value of positional uncertainties should be 1 meter or better in urban areas and 2,5 meters
or better in rural/agricultural areas. Cadastral data may be less accurate in unexploited areas.
- Edge-matching between cadastral parcels in adjacent data sets should be done. Ideally, there
should be no topological gaps or topological overlaps between cadastral parcels in adjacent data
sets. Status of edge-matching should be reported as metadata, under lineage element
- There should be no topological overlaps between cadastral parcels.
- There should be no topological gaps between cadastral parcels.
Transport networks:
- Guarantee that a continuous transport network can be built from the elements provided in the
transport network datasets, by assessing their conformance to some basic topological
consistency rules aimed at ensure at least clean connections between features.
This specification is compliant with EN ISO 19113 and EN ISO 19114, but it does not fix any concrete
conformance criteria for the data quality information proposed, since it should be valid for a wide range
of European transport network datasets, with very different levels of detail and quality requirements.
4.2 Metadata on data quality
There are two specific requirements related to metadata on data quality from the Directive:
- Article 5(2): MD shall include information on data quality and validity of spatial data sets
- Article 11(2): Network services (Discovery) shall include searching functionality on quality and
validity of spatial data sets.
The scope of Regulation 1205/2008/EC on metadata is to set out the requirements for the creation
and maintenance of metadata for spatial data sets, spatial data set series and spatial data services
corresponding to the themes listed in Annexes I, II and III to Directive 2007/2/EC. This, together with
the discovery services and an INSPIRE geo-portal, will help in searching for existing spatial data or
establishing whether they may be used for a particular purpose.
The newly published Regulation 268/2010/EC on data and service sharing requires (Article 6 –
Transparency) the Member States to make available, upon request, information for evaluation and
use, on the mechanisms for collecting, processing, producing, quality control and obtaining access to
the spatial data sets and services, where that additional information is available and it is reasonable to
extract and deliver it. This legal requirement gives a clear evidence of the importance of reaching the
common understanding among the Member States about data quality Metadata elements and their
use in INSPIRE.
When additional metadata (for instance on data quality) are supplied it is possible to display them
providing additional information to the users. However, it is not clear if and how these additional
metadata elements can be searched (cf. Art. 11(2)). It is expected that further harmonisation between
Data, Metadata, and Network services components of INSPIRE may take place upon completing their
technical drafting.
For a better understanding the original text “Aggregated data quality information should ideally be collected at
the level of spatial object types and included in the dataset (series) metadata” has been paraphrased
7
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During the Annex I data specification development all themes included the mandatory list of
elements, required by Regulation 1205/2008/EC, in their specifications. In addition new mandatory
metadata elements were introduced and accepted. These are:
- Coordinate Reference System
- Temporal Reference System (Mandatory, if the data set or one of its feature types contains
temporal information that does not refer to the Gregorian Calendar or the Coordinated Universal
Time)
- Encoding
- Character Encoding (Mandatory, if a non-XML-based encoding is used that does not support
UTF-8)
- Data Quality/Logical Consistency/Topological Consistency (Mandatory, if the data set do not
assure centerline topology (connectivity of centerlines) for transport network – applies only to
Hydrography and Transport networks themes)
The list of recommended data quality metadata elements that are currently in the Guidelines of Annex
I themes is presented in the Table 1. The table also presents the result of the harmonisation effort that
took place at the end of the data specification development process.
The Recommendations related to using metadata elements of Regulation 1205/2008/EC that are
relevant to the data quality and that apply to all themes are listed bellow:
-
-
-
Conformity. In order to report conceptual consistency with this INSPIRE data specification, the
Conformity metadata element should be used. The value of Conformant should be used for the
Degree element only if the dataset passes all the requirements described in the abstract test
suite. The Specification element should be given as follows:
o title: “INSPIRE Data Specification on Transport Networks – Guidelines”
o date:
o dateType: publication
o date:
Lineage.8 part from describing the process history, if feasible within a free text, the overall quality
of the dataset (series) should be included in the Lineage metadata element. This statement
should contain any quality information required for interoperability and/or valuable for use and
evaluation of the data set (series).
Temporal reference. If feasible, the date of the last revision of a spatial data set should be
reported using the Date of last revision metadata element.
Theme specific recommendations on the use of Metadata elements:
Cadastral parcels:
- Lineage. Main specificities of cadastral data should be published in the element “description of a
data set”, using the relevant template.
- Maintenance. Frequency with which changes are made for INSPIRE should be as close as
possible to the frequency with which changes are made in a national cadastral register or
equivalent. Moreover, frequency with which changes are made for INSPIRE should be one year
or better.
- Positional Accuracy. A cadastral data provider may give information about absolute accuracy:
o at spatial object level, as attribute “estimatedAccuracy”on CadastralZoning or on
CadastralBoundary
o at spatial object type, as metadata element “positional accuracy”.
In case none of these solutions are feasible, the cadastral data provider should give information about
positional accuracy under the “lineage” metadata element. This may occur, for instance, if the
information about positional accuracy does not provide from quality measures but is just estimated
from the knowledge of source data and of production processes. More generally, absolute positional
accuracy should be function of the density of human activities. This recommendation may be adapted
to the specific context of each Member State).
8
This use of lineage is in conflict with ISO 19115 and ISO 19114. Quality results should be reported by using
appropriate quality elements that are described in ISO 19115.
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Hydrography:
- For evaluation purpose the Data quality measure and Metadata element Rate of missing items
(Completeness Omission) should be included for all spatial object types apart from the following
list of types: HydroPointOfInterest and ManMadeObjects.
- Keywords should be taken from the GEMET – General Multilingual Environmental Thesaurus
where possible.
- When publishing metadata for any dataset conforming to this specification; it shall have the topic
category ‘Inland Waters’ for the corresponding metadata element (requirement).
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5 Points for discussion
In order to propose a balanced and agreed way how DQ requirements and Metadata need to be
approached in INSPIRE, we invite the (DQ) Contact Points of the Member States to organise national
discussions and provide agreed and consolidated answers to the questions bellow.
1. Is there a need to include a priori data quality targets (elements, measures, and values) in
INSPIRE data specifications?
Yes, for each dataset addressing the same set of requirements
Yes, but only for those datasets where achieving interoperability requires so
No
If no, please go to question 4. If yes, please answer questions 2 and 3.
2. Please indicate the theme and whether these targets should be addresses by mandatory
requirements (M) or recommendations (R)? Please include justification if necessary.
Name of the data theme
Condition M/R
Justification / Comments
(Extend table if required.)
3. Please indicate the data quality elements, measures, and the target values to be used (add as
many lines as needed). Please fill a separate table for each data theme to which a priori DQ
requirements/recommendation apply.
Name of the data theme
DQ element
DQ measure
Target value
Comments
(Extend table if required.)
4. Do you recommend to specify mandatory metadata elements in INSPIRE when no a priori
data quality requirements have been specified, or to complement those specified in the DQ
section to inform users about the fitness for purpose?
Yes
No
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5. What is the best way to generate DQ metadata about the data that has been made
conformant to the INSPIRE data specifications (i.e. after the necessary data transformations?)
Keep the original metadata
Generate new metadata based on calculations or quality inspection by appropriate
sampling
Keep the original metadata and described as process step in MD_lineage
(transformations performed with their possible effect on data quality)
6. Do you recommend to introduce theme-specific conformity levels (in addition to conformant,
non conformant, not evaluated) in the INSPIRE Annex II-III data specifications development?
Yes
No
7. Would there be value in adding theme-specific conformity levels (apart from conformant, non
conformant, not evaluated) to INSPIRE Annex I data specifications?
Name of the data
theme
Yes/No
Justification/comments
(Extend table if required.)