projectprofit.eu · 2016-07-13 · SKOS Simple Knowledge Organization System. 9, 10, 12, 18, 27, 28 XKOS An SKOS extension for representing statistical classi cations. 27 XL eXtension

HORIZON 2020ICT - INFORMATION AND COMMUNICATION TECHNOLOGIES

PRO MOTING FI NANCIAL AWARENESS AND STABILIT Y

H2020 – 687895

PROFIT CORE KNOWLEDGE MODEL

WORK PACKAGE NO. WP2 WORK PACKAGE TITLE LINKED DATA LIFE CYCLE

TASK NO. T2.2 TASK TITLE SEMANTIC DATA MODELING, LINKING AND ENRICHMENT

MILESTONE NO. 2

ORGANIZATION NAME OF LEAD CONTRACTOR FOR THIS DELIVERABLE

SWC

EDITOR ARTEM REVENKO (SWC)

REVIEWERS EIRINI KARAPISTOLI (DUTH), ANDREAS BLUMAUER (SWC)

STATUS (F: FINAL; D: DRAFT) D

NATURE R - REPORT

DISSEMINATION LEVEL PU - PUBLIC

PROJECT START DATE AND DURATION

JANUARY 2016, 36 MONTHS

DUE DATE OF DELIVERABLE:

ACTUAL SUBMISSION DATE:

JUNE 30, 2016

JUNE 30, 2016

REVISION HISTORY

VERSION DATE MODIFIED BY CHANGES

0.1 10-01-2016 A. REVENKO (SWC) FIRST VERSION OF TOC

0.1.1 13-01-2016 A. REVENKO (SWC) TOC REFINED

0.2 10-03-2016 A. REVENKO (SWC) TOC FINALISED

0.3 01-04-2016 A. REVENKO (SWC) ADDED SECTION 1




0.8 15-05-2016 A. REVENKO (SWC) FINAL OFFICIAL PRELIMINARY DRAFT VERSION OF D2.1

0.9 15-06-2016 A. REVENKO (SWC) REVISION ACCORDING TO COMMENTS FROM E. KARAPISTOLI (DUTH) AND A. BLUMAUER (SWC)

1.0 20-06-2016 A. REVENKO (SWC) FINAL REVIEW, PROOFING AND QUALITY CONTROL. READY FOR SUBMISSION

Deliverable D2.1 Dissemination level (PU) Contract N. 687895

List of Abbreviations

BBC British Broadcasting Corporation. 36, 37

CV Curiculum Vitae. 21

ESS European Statistical System. 24

EU European Union. 16, 21, 24

FIBO Financial Industry Business Ontology. 30–32

FOAF Friend of a Friend. 41

IT Information Technology. 17, 21, 30

OWL Web Ontology Language. 29, 31, 34, 36, 38, 40

RDF Resource Description Framework. 10, 12, 14, 21, 24, 37, 38

SKOS Simple Knowledge Organization System. 9, 10, 12, 18, 27, 28

XKOS An SKOS extension for representing statistical classifications. 27

XL eXtension for Labels. 9

June 3, 2016 H2020-687895 ©The PROFIT Consortium Page 3 of 71


List of Figures

1 Foundations Ontology Architecture . . . . . . . . . . . . . . . . . . . . . . 372 Provenance ontology diagram . . . . . . . . . . . . . . . . . . . . . . . . . 423 Public Contract ontology diagram . . . . . . . . . . . . . . . . . . . . . . 444 MARL ontology diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465 PROFIT User ontology diagram . . . . . . . . . . . . . . . . . . . . . . . 496 PROFIT User taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 PROFIT Finance ontology diagram . . . . . . . . . . . . . . . . . . . . . . 52



List of Tables

1 ESCO thesaurus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 STW Thesaurus for Economics statistics . . . . . . . . . . . . . . . . . . . 143 STW Thesaurus for Economics statistics per language . . . . . . . . . . . 144 Substitutions of classes in STW Economics back to SKOS . . . . . . . . . 165 EuroVoc thesaurus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 EuroVoc statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 EuroVoc statistics per language . . . . . . . . . . . . . . . . . . . . . . . . 198 ESCO thesaurus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 ESCO thesaurus statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . 2510 ESCO thesaurus statistics per language . . . . . . . . . . . . . . . . . . . 2611 NACE Rev. 2 thesaurus . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2912 NACE Rev. 2 statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2913 NACE Rev. 2 statistics per language . . . . . . . . . . . . . . . . . . . . . 3014 Custom ontology to PoolParty mappings . . . . . . . . . . . . . . . . . . . 3415 FIBO ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3516 FIBO statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3517 FIBO to PoolParty datatypes mapping . . . . . . . . . . . . . . . . . . . . 3818 Schema.org ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3919 Schema.org statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3920 Provenance ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4121 Provenance statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4122 Public Contract ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . 4323 Public Contract ontology statistics . . . . . . . . . . . . . . . . . . . . . . 4324 MARL ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4525 MARL statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4526 PROFIT User ontology statistics . . . . . . . . . . . . . . . . . . . . . . . 4827 PROFIT Finance ontology statistics . . . . . . . . . . . . . . . . . . . . . 50



Table of Contents

Executive Summary 9

1 Introduction 101.1 Scope of the document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.2 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . . . . . 101.3 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.4 Usage of PoolParty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2 Thesauri 122.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122.2 Selection of Thesauri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132.3 Mappings between Thesauri . . . . . . . . . . . . . . . . . . . . . . . . . . 132.4 STW Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.4.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 152.4.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 152.4.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152.4.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162.4.6 Import in PoolParty . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.5 EuroVoc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172.5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172.5.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 182.5.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 202.5.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202.5.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212.5.6 Import in PoolParty . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.6 ESCO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252.6.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252.6.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 252.6.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 272.6.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272.6.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272.6.6 Import in PoolParty . . . . . . . . . . . . . . . . . . . . . . . . . . 28

2.7 NACE Rev. 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282.7.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282.7.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 292.7.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 302.7.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312.7.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312.7.6 Import in PoolParty . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.8 Examples from partners . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32



3 Ontologies 333.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333.2 Mapping to PoolParty format . . . . . . . . . . . . . . . . . . . . . . . . . 333.3 FIBO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

3.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353.3.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 353.3.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 363.3.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.3.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383.3.6 Mapping to PoolParty format . . . . . . . . . . . . . . . . . . . . . 38

3.4 Schema.org . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383.4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383.4.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 393.4.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 393.4.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403.4.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403.4.6 Mapping to PoolParty format . . . . . . . . . . . . . . . . . . . . . 40

3.5 Provenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413.5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413.5.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413.5.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 423.5.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423.5.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423.5.6 Mapping to PoolParty format . . . . . . . . . . . . . . . . . . . . . 42

3.6 Public Contracts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433.6.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433.6.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 433.6.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 433.6.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443.6.5 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443.6.6 Mapping to PoolParty format . . . . . . . . . . . . . . . . . . . . . 44

3.7 MARL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453.7.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453.7.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 453.7.3 Relation to PROFIT project . . . . . . . . . . . . . . . . . . . . . 453.7.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463.7.5 Mapping to PoolParty . . . . . . . . . . . . . . . . . . . . . . . . . 46

3.8 Some further ontologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463.8.1 FISE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463.8.2 Friend of a friend . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473.8.3 Dublin Core Metadata Terms . . . . . . . . . . . . . . . . . . . . . 47

4 PROFIT Core Ontology 484.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48



4.2 User Actions Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484.2.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 484.2.3 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

4.3 Finance Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504.3.2 Objectives / Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . 504.3.3 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

5 Future Work 54

6 Conclusion 55

Appendices 58

A PROFIT User Ontology 58

B PROFIT Finance Ontology 65



Executive Summary

The deliverable represents the results of preparing PROFIT core knowledge model. Itconsists of the following results achieved in the first six months of the project:

1. Discovery, transformation and import of relevant thesauri and ontologies;

2. Preparation of two PROFIT ontologies: user related and finance related;

3. Planning of the future work.

The three main parts of this deliverable report are Section 2 about the thesauri thatwere prepared for potential usage in PROFIT project, Section 3 about the ontologiesprepared for potential usage in PROFIT project, and Section 4 about the ontologiesdeveloped in frames of D 2.1. Each of the thesauri and the ontologies as accompaniedby a description outlying its possible usage, scope, structure, and relation to PROFITproject.



1 Introduction

1.1 Scope of the document

The document describes the output of the preparation of PROFIT core knowledge model.The main activity in the process was identification of relevant ontologies and thesaurithat can be reused for the aims of the project and preparation for using them in theenvironment of the project. Moreover, based on the feedback from other members ofthe consortium and the output of other work packages two ontologies were prepared, seeSection 4.

The document describes all the thesauri and ontologies and provides some discussionabout their possible usage in the project. Moreover, the analysis of possible issuesrelated to the structure of the thesauri and ontologies is provided, the mapping of theontologies to the PoolParty format is described.

For the ontologies created in the frames of this task descriptions, visualizations andpublished reports are included.

1.2 Relation to PROFIT project

In this deliverable the work on controlled vocabularies and especially on ontologies wascarried out. These controlled vocabularies will constitute the basis of further expandingto the full blown knowledge graph in deliverable 2.4 “PROFIT knowledge graph”, duein Month 12 (December 2016).

The part of the work that is not reflected by any outcome and therefore not describedin further details in this document is the trainings and numerous discussion to enablethe partners of the consortium to even better understand and utilize the semantic tech-nologies. It was very important to elaborate a common understanding of the linked datarelated technologies in the consortium.

1.3 Goals

The goal of this deliverable is to create the core knowledge model for further extending itto a full-blown knowledge graph. The full blown knowledge graph will contain particularinstances of data, for example, data about individual users, individual news articles, datafrom particular educational materials. Therefore, it was necessary to identify the mainbuilding blocks of such data. Hence we aimed at making available a set of controlledvocabularies that would roughly cover all the potentially relevant fields of knowledge.

The actual data will be added to the data storage in course of D 2.4 “PROFIT knowledgegraph” due in Month 12, D 3.2 “Integrated Financial Educational Toolkit” due in Month24, and during the operation of the platform.



1.4 Usage of PoolParty

In PROFIT project PoolParty Semantic Suite (in what follows we use just “PoolParty”for conciseness) is used as the controlled vocabulary and linked data management tool.PoolParty supports all the widely accepted standards of semantic web technologies suchSKOS and OWL. However, in order to facilitate better consistency and convenienceof working with controlled vocabularies, some restrictions are imposed. Moreover, therestrictions on the possible set of expressions used in the controlled vocabularies assurethat the constructed thesauri and ontologies can be understood and maintained by theexperts in the field. Therefore, transformation of the discovered controlled vocabulariesto the form compatible with PoolParty was carried out, see Sections 2.4.6, 2.5.6, 2.6.6,2.7.6, 3.2, 3.3.6, 3.4.6, 3.5.6, 3.6.6, 3.7.5.

PoolParty makes language support easy and convenient. Namely, the labels of theconcepts may include variants in different languages.

In PoolParty the functionality of linking the data to the widely known source of linkeddata such as Geonames, WikiData or DBpedia is available.

In this report as well as in PoolParty often the preferred label in english (or defaultlanguage in PoolParty) is used to identify a concept.



2 Thesauri

2.1 Introduction

A thesaurus is a controlled vocabulary with a hierarchical structure, with the understand-ing that there are different definitions of a hierarchy. Concepts within a thesaurus haverelations to other concepts within the thesaurus. These relations are: parent/broaderrelation, child/narrower relation, or often both if the concept is at mid-level within ahierarchy and the “related” relation, which is not a hierarchical relation. A thesaurusmay have poly-hierarchies, i.e. a concept may have more than one broader concepts[Losee, 2007, Pastor-Sanchez et al., 2009].

The hierarchical relationship clarifies the meaning of the concept in its context; for exam-ple, the sense in which “press” is to be understood is clarified by its being subordinatedto the concept “mass media”.

The associative relationship is a relationship between two concepts which do not belongto the same hierarchical structure, although they have semantic or contextual similarities.The relationship must be made explicit because it suggests to the indexer the use of otherindexing terms with connected or similar meanings which could be used for indexing orsearches.

One of the standards for thesauri that is widely accepted is SKOS1

[Pastor-Sanchez et al., 2009, Abdul Manaf et al., 2012]. This standard defines aschema for describing concept schemes and concepts of thesauri. Namely it definesthree types of relations essential for a thesaurus: broader, narrower, and related andsome specific attributes for each concept, for example, preferred label, alternativelabels, definition. The labels may be accompanied by language tags in order to adapta thesauri for multi-lingual environment [Dejean et al., 2002, Hudon, 2001]. The labelsare used by PoolParty for finding the concepts in the documents automatically.

To make the work with labels more flexible an extension XL of SKOS is introduced.This extension allows for treating labels as resources and introducing relations betweenindividual labels and concepts.

The namespace of SKOS is https://www.w3.org/2009/08/skos-reference/skos.

html. The namespace for XL is https://www.w3.org/TR/skos-reference/skos-xl.

html.

In the specifications of SKOS one may find specific information about the propertiesof individual elements of thesauri. These properties are required by the specificationsof SKOS. In order to ensure the satisfaction of the properties PoolParty enables usersto conduct quality checks based on the qSkos component [Mader and Haslhofer, 2011].This component is able to identify, for example, if different concepts have the same labelsor if the broader/narrower relations of some concepts introduce a cycle. Such quality

1https://www.w3.org/2004/02/skos/


https://www.w3.org/2009/08/skos-reference/skos.html

https://www.w3.org/2009/08/skos-reference/skos.html

https://www.w3.org/TR/skos-reference/skos-xl.html

https://www.w3.org/TR/skos-reference/skos-xl.html

https://www.w3.org/2004/02/skos/


issues should be avoided in order to improve the performance of using thesauri.

In frames of PROFIT project the thesauri will be used to store individual instanceof data related to the scope of the project. For example, such pieces of data could beparticular banks, particular economic instance like Euro or unemployment, or a collectionof actions that could be taken by the user, like comment action or rate action. Theseinstances will be later on, in course of D 2.4 “PROFIT knowledge graph” and duringthe operation of the platform, used to describe individual documents (news articles,blog posts, educational materials) and individual users. Based on the structure of thethesaurus it will be possible to compare news articles and users even if they do not havecommon annotations (concepts from thesauri) related to them.

In the course of D 2.4 “PROFIT knowledge graph” the prepared thesauri will be fusedinto one or several thesauri specific for PROFIT project. These thesauri will reuse theexisting well-known thesauri (described in the subsequent sections) and will be extendedusing the expert knowledge from the partners in the consortium. Hence, the final thesaurirepresent an important output by itself and may be further reused outside the project.

The thesauri will be accompanied by the ontologies, which define classes of instanceswith specific relations and attributes for different classes. The ontologies enable evenmore flexibility when working with the instances, see Section 3.

2.2 Selection of Thesauri

Several thesauri were chosen as a basis for PROFIT thesaurus. The criteria were thecorrespondence to the purposes of PROFIT project. The STW Economics thesaurus is ageneral economic thesaurus. It contains a large number of concepts that could be reusedfor describing financial literacy, economic knowledge, financial textual resources. TheEuroVoc thesaurus is focused on European political and economical vocabulary. Thereare many overlaps with STW Economics, but some topics, for example the geographicalentities, are only covered in EuroVoc. Moreover, EuroVoc is translated to many Euro-pean languages, these translation could be reused. The ESCO thesaurus is an officialthesaurus of EU for describing skills and occupations. This thesaurus could be usefulfor describing labour economics and for describing skills of individual users. The NACEthesaurus could be used for describing individual branches of economics. Altogetherthese thesauri cover all the possible fields that could be needed in PROFIT project.

2.3 Mappings between Thesauri

The same concepts may appear in different thesauri. This fact becomes an importantissue when reusing those thesauri or finding common semantics in different projects.Therefore, some thesauri are accompanied by the mappings from it to other well-knownthesauri, for example, STW Economics http://zbw.eu/stw/version/9.0/mapping/.PoolParty automates the procedure of finding such mappings with its linking function-


http://zbw.eu/stw/version/9.0/mapping/


Table 1: ESCO thesaurus

Homepage http://zbw.eu/stw/version/9.0/about.en.html

Download source http://zbw.eu/stw/version/9.0/download/about.en.html

License http://creativecommons.org/licenses/by-nc-sa/3.0/

Free usage XRDF X

Table 2: STW Thesaurus for Economics statistics

Number of concepts 6521Number of broader/narrower relations 15892Number of related relations 21008

ality. During the preparation of the PROFIT thesaurus the mapping will be done (De-liverable 2.4 “PROFIT knowledge graph”, due in Month 12).

2.4 STW Economics

2.4.1 Overview

STW Thesaurus for Economics [Neubert, 2009, Borst and Neubert, 2009] is a controlled,structured vocabulary for subject indexing and retrieval of economics literature. Thevocabulary covers all economics-related subject areas and, on a broader level, the mostimportant related subjects (e.g. social sciences). In total, STW contains about 6,000descriptors (key words) and about 20,000 non-descriptors (search terms). All descriptorsare bi-lingual, German and English.

Some essential information about STW Thesaurus for Economics is presented in Table 1.The overall number of labels and relations are presented in Tables 2 and 3 respectively.Note that german labels are only present as alternative labels.

Having been developed as a general indexing and retrieval tool for economics publicationsin the ZBW catalogue ECONIS, STW can be used by other organisations for indexing

Table 3: STW Thesaurus for Economics statistics per language

Language Preferred Labels Alternative Labels

German 0 15028English 6521 3037

Total 6521 18065


http://zbw.eu/stw/version/9.0/about.en.html

http://zbw.eu/stw/version/9.0/download/about.en.html

http://creativecommons.org/licenses/by-nc-sa/3.0/


their own materials. Details for use are given on the STW online homepage.

2.4.2 Objectives / Scope

The ZBW German National Library of Economics – Leibniz Information Centre forEconomics is the worlds largest economics library. It holds more than four million mediaitems such as books, articles, journals, grey literature and databases. ZBW supports itsusers with fine-grained thematic access to these information resources. For this purposethe STW Thesaurus for Economics has been developed and applied since the 1990s. Itprovides a high-level taxonomy of subject categories, thousands of keywords (descriptors)and tens of thousands of both synonyms and links between the thesaurus concepts. Themedia items are indexed with descriptors from this thesaurus. They can be retrieved bythese descriptors through the library catalogue ECONIS.

2.4.3 Relation to PROFIT project

The STW Economics thesaurus is highly related to the field of discourse of PROFITproject. The thesaurus contains many entities for annotating the contents of financialand economic news articles, reviews, educational materials. This thesaurus will be usedas a basis for the future knowledge graph.

2.4.4 Structure

The STW thesaurus consists of seven main subject groups

A General Descriptors,

B Business Economics,

G Geographic Names,

N Related Subject Areas,

P Commodities,

V Economics,

W Economic Sectors and Industry Studies.

The group A contains a list of general terms. These terms do not belong to any specialsubject areas and therefore possess only little information value when used alone. Thesubject groupings of parts B and V follow the usual subject fields in national andinternational research. The descriptor groupings of parts P and W are mostly takenfrom the current commodity and sector classifications of Statistisches Bundesamt. Thegeographic sections of part G reflect the continental subdivisions, starting with Europe.



Table 4: Substitutions of classes in STW Economics back to SKOS

zbwext:Descriptor skos:Conceptzbwext:Thsys skos:Conceptzbwext:useInsteadNote skos:note

2.4.5 Maintenance

Exclusive responsibility for the continuous maintenance of the STW lies with ZBW. Aregular editorial team verifies and decides on changes and updates concerning vocabularyand thesaurus structure. Proposals by indexers and the current professional discussionare taken as sources for changes to be made. The STW master file has been implementedinto a thesaurus maintenance tool based on an inhouse development. The consistentmaintenance and revision is assured by carrying out plausibility checks and removingduplicate terms. Each descriptor is given an ID-number which serves as a unique andinalterable key.

2.4.6 Import in PoolParty

The STW Economics thesaurus is available in RDF. The data model is compatible withPoolParty, hence it can be imported without any further transformations.

However, some steps are needed to be taken in order to transform the thesaurus intoSKOS [Neubert, 2009]. The inheritance of classes developed by the ZBW team hasto be reversed, see Table 4. The blank nodes were discarded. The subject groupswere imported as top concepts of one general concept scheme “STW Thesaurus forEconomics”.

A special language tag “x-other” was used 84 times in order to identify the originalnames in other languages (not english nor german).

After the import the quality checks implemented in PoolParty have identified they fol-lowing issues. Two concepts: “Municipal enterprise” and “Assistance for ex-offenders”have clash in preferred label and alternative label. Several labels are used for differentconcepts (either as preferred or as alternative labels), the list of these labels:

1. Test,

2. Information Services,

3. Futures Market,

4. Handicrafts,

5. Job Design,

6. Calculation,



7. Tax Evasion,

8. Forage Crops.

The relation clash problem2 was identified in 9 groups of concepts:

1. Collective bargaining policy, Wage policy, Wage bargaining;

2. Foreign policy, Development Aid, Development cooperation;

3. Structural policy, Business policy, Industrial Policy, Innovation policy;

4. Economic policy, Government Credit Programme, Industrial promotion;

5. Portfolio management, Beta Estimate, Financial Economics, Capital asset pricingmodel;

6. Humanities, Philosophy, Science, Epistemology;

7. Employment relationship, Precarious employment, Part-time employment;

8. Philosophy of Science, Humanities, Philosophy, Science;

9. Artificial intelligence, Pattern recognition, Image processing.

2.5 EuroVoc

2.5.1 Overview

EuroVoc [Steinberger et al., 2002, Steinberger et al., 2013] is a multilingual thesauruswhich was originally built up specifically for processing the documentary information ofthe EU institutions.

It is a multi-disciplinary thesaurus covering fields which are sufficiently wide-ranging toencompass both Community and national points of view, with a certain emphasis onparliamentary activities. EuroVoc is a controlled set of vocabulary which can be usedoutside the EU institutions, particularly by parliaments.

Initially, the EuroVoc thesaurus was compiled in accordance with the two standards ofthe International Standards Organisation. Since 2008, both standards have been revised,extended and combined into a new “ISO 25964 - Thesauri and Interoperability with otherVocabularies”3.

Some essential information about EuroVoc is presented in Table 5. The overall numberof labels and relations are presented in Tables 6 and 7 respectively.

2http://www.w3.org/TR/skos-reference/#L24223http://niso.org/schemas/iso25964/


http://www.w3.org/TR/skos-reference/#L2422

http://niso.org/schemas/iso25964/


Table 5: EuroVoc thesaurus

Homepage http://eurovoc.europa.eu/drupal

Download source http://open-data.europa.eu/en/data/dataset/eurovoc

License http://eurovoc.europa.eu/drupal/?q=legalnotice

Free usage XRDF X

Table 6: EuroVoc statistics



The aim of the thesaurus is to provide the information management and disseminationservices with a coherent indexing tool for the effective management of their documen-tary resources and to enable users to carry out documentary searches using controlledvocabulary.

Another role of the thesaurus is to remove ambiguities, ensuring that each concept iscontextualised in such a way that its meaning is univocal. If the meaning is not clearenough, a note can accompany a concept to clarify its meaning or use in a specifiedlanguage.

The EuroVoc thesaurus covers all the activity fields of the European Union institutions:

• Politics,

• International Relations,

• European Communities,

• Law,

• Economics,

• Trade,

• Finance,

• Social Questions,

• Education and Communications,

• Science,

• Business and Competition,


http://eurovoc.europa.eu/drupal

http://open-data.europa.eu/en/data/dataset/eurovoc

http://eurovoc.europa.eu/drupal/?q=legalnotice


Table 7: EuroVoc statistics per language


Bulgarian 6924 1165Czech 6924 13616Danish 6924 7216German 6924 9024Greek 6924 7657English 6924 7768Spanish 6923 8380Estonian 6924 6688Finnish 6924 6237French 6924 7514Irish 6924 149Croatian 6924 6268Hungarian 6924 9150Italian 6924 10130Lithuanian 6924 6674Latvian 6924 6674Maltese 6924 819Dutch 6924 7439Polish 6924 1278Portuguese 6924 7054Romanian 6924 5646Slovak 6924 6368Slovenian 6924 1259Serbian 6924 1398Swedish 6924 7181

Total 173099 153311



• Employment and Working Conditions,

• Transport,

• Environment,

• Agriculture, Forestry and Fisheries,

• Agri-foodstuffs,

• Production, Technology and Research,

• Energy,

• Industry,

• Geography,

• International Organisations.

Some fields are more highly developed than others because they are more closely relatedto the EUs centres of interest. Thus, for example, the names of the regions of each EUMember State are in EuroVoc but not those of third countries.

The grouping of descriptors into fields is to a certain extent arbitrary. One of EuroVocsdistinctive features is the limitation of polyhierarchy. Descriptors which could fit intotwo or more subject fields are thus generally assigned only to the field which seems themost natural for users, in order to facilitate the management of the thesaurus and limitits volume.


The Eurovoc thesaurus contains a lot of concepts that are important for Europeaneconomics and may be found in the financial news articles. Some concept schemes inEurovoc contain concepts related to economical and financial sciences. Moreover, thisthesaurus contains translations of the concepts to many European languages.

2.5.4 Structure

At generic level, EuroVoc has a two-tier hierarchical classification:

1. fields, identified by two-digit numbers and titles in words;

2. microthesauri, identified by four-digit numbers – the first two digits being thosefor the field containing the microthesaurus – followed by titles in words.

The numbering of fields and microthesauri is identical in all language versions.

The hierarchical relationship allows those using a documentary system to adapt its levelof specificity by browsing in the hierarchy. They can expand or detail their question byselecting concepts with a broader meaning (for example, standardisation, or technicalregulations) or a more precise meaning (production standard, quality standard, technical



standard).

In EuroVoc, the hierarchical relationship is established on the basis of logical situations:

Generic relationship This identifies the link between a class (broader term or top term)and its constituents (specific terms).

Partitive relationship This relation concerns a limited number of situations in whichthe name of a part indicates the name of the whole, regardless of the context. Thename of the whole represents the generic concept and the name of the part thespecific term(s) of the concept.

There is no associative relationship between concepts with the same top term.

2.5.5 Maintenance

The EuroVoc thesaurus is adapted continually to take account of developments in thefields in which the European Union institutions are active and of changes in its languagearrangements.

The special feature of EuroVoc is that it aims – and is able – to meet the needs expressedby all its users while keeping in mind the objective of covering in a homogenous fashionthe fields of activity of the European Union.

The maintenance team at the Publications Office collects and examines the proposals,put forward by the national parliaments, the European institutions or agencies and theprivate users. A maintenance system has been established to deal with the administra-tion and maintenance of the thesaurus. The maintenance team coordinates the work ofthe Maintenance Committee and is responsible for IT and technical developments andfor monitoring translations.

The Maintenance Committee made up of representatives of the various EU institutions,votes on the various proposals and decides on the amendments to be made to the the-saurus.

The Steering Committee supervises the project and officially adopts each new version.


The version translated to PoolParty format is version 4.3. The lists of classes, rela-tions, and attributes presented below were defined for the EuroVoc thesaurus and theirdefinitions are contained in the dedicated namespace eu.

Classes:

• eu:Export class capturing the publication characteristics of the exported EuroVocthesaurus release. This class is discarded.

• eu:Domain defines the domains of interest. This class is substituted by



skos:ConceptScheme.

• eu:Thesaurus is a subclass of skos:ConceptScheme. This class is discarded.

• eu:MicroThesaurus is a subclass of skos:ConceptScheme. This class defines micro-thesauri. This class is substituted by skos:ConceptScheme.

• eu:ThesaurusConcept is a subclass of skos:Concept. This class defines descriptorsin micro-thesauri. This class is substituted by skos:Concept.

– eu:Country class defines countries. This class is a subclass ofeu:ThesaurusConcept. This class is substituted by skos:Concept.

• eu:ThesaurusTerm is a subclass of xl:Label and is used to represent labels. Thisclass is discarded. The SKOS attributes prefLabel, altLabel, hiddenLabel are usedinstead.

– eu:CompoundNonPreferredTerm is a subclass of eu:ThesaurusTerm. Thisclass is discarded.

– eu:PreferredTerm is a subclass of eu:ThesaurusTerm. This class is discarded.

– eu:SimpleNonPreferredTerm is a subclass of eu:ThesaurusTerm. This class isdiscarded.

• eu:EquivalenceRelationship is the set of associations establishing the relationshipbetween a preferred term and a simple non preferred term. This class is discarded.

• eu:CompoundEquivalence is the set of associations establishing the relationshipbetween one compound non preferred term and its component terms. This classis discarded.

• eu:Language is the set of system specific description of languages. This class isdiscarded.

Relations (Object Properties):

• eu:exportedThesaurus. Domain: eu:Export, range: eu:Thesaurus. The referencedsubject provides the publishing details of the EUROVOC thesaurus denoted bythe object value. This relation is discarded.

• eu:inDomain Domain: skos:Concept, range: eu:Thesaurus. The property declaresthe subject resource to participate in the domain denoted by the object value. Thisrelation is discarded.

• eu:domain Domain: eu:microThesaurus, range: eu:Domain. A functional propertydepicting the domain of a micro-thesaurus.

• eu:microThesaurus inverse of eu:domain. Discarded.

• eu:supportedLanguage Domain eu:Thesaurus, range: eu:Language. Denotes a de-scription of the languages supported by the EUROVOC thesaurus. Discarded.

• eu:reference Domain: eu:ThesaurusConcept, range: dcterms:reference. The rela-



tion typically may be used in a ’definition’ or a ’scope note’ about a concept or alabel. Discarded.

• eu:useInstead Domain: eu:ThesaurusConcept, range: eu:ThesaurusConcept. Therelation applies to EuroVoc concepts that are obsolete as from a date mentionedin the scope note of the obsolete concept. Discarded.

• eu:acronym Domain: eu:ThesaurusTerm, range: eu:ThesaurusTerm. sub-relationof xl:labelRelation. Provides acronyms. Discarded.

• eu:fullName Domain: eu:ThesaurusTerm, range: eu:ThesaurusTerm. sub-relationof xl:labelRelation. Provides full names. Discarded.

• eu:shortName Domain: eu:ThesaurusTerm, range: eu:ThesaurusTerm. sub-relation of xl:labelRelation. Provides short names. Discarded.

• eu:translationOf Domain: eu:ThesaurusTerm, range: eu:ThesaurusTerm. sub-relation of xl:labelRelation. Provides translation. Discarded.

• eu:compoundNonPreferredTerm Domain: eu:CompoundEquivalence, range:eu:CompoundNonPreferredTerm. he value references the compound non preferredterm denoted by the subject. Discarded.

• eu:preferredTermComponent Domain: eu:CompoundEquivalence, range:eu:PreferredTerm. The value references a preferred term denoted by thesubject. Each of these preferred terms captures a semantic component of thecompound non preferred term referenced by their common compound equivalencerelationship. Discarded.

• eu:UF Domain: eu:EquivalenceRelationship, range: eu:SimpleNonPreferredTerm.UF stands for ’Used For’. Discarded.

• eu:USE Domain: eu:EquivalenceRelationship, range: eu:PreferredTerm. Dis-carded.

Attributes (Data Properties):

• eu:exportDate Domain: eu:Export, range: dateTime. The system date and timeat which the described EuroVoc thesaurus release is published. Discarded.

• eu:exportVersion Domain: eu:Export, range: string. The release number is theversion identifier of the published EuroVoc thesaurus.

• eu:intermediateRelease Domain: eu:Export, range: boolean. If true a release in-cluding the terms and concepts that were approved for the next full release. Dis-carded.

• eu:hasPolyhierarchy Domain: eu:Domain, skos:ConceptScheme, range: boolean.Indicates whether the EuroVoc thesaurus, micro-thesaurus or domain supportspoly-hierarchy. Discarded.

• eu:approvedForRelease Domain: eu:Domain, eu:MicroThesaurus,



eu:ThesaurusConcept, range: string. The value provides the expected releasenumber for the official release of a new or modified concept. Discarded.

• eu:toBeTranslated Domain: eu:Domain, eu:MicroThesaurus, eu:ThesaurusTerm.The range value must have: language (the language for which translation is re-quired); for a term this must be the language of the term; for a micro-thesaurusor domain this may be a comma separated list of languages. Discarded.

• eu:relevantURL Domain: eu:ThesaurusConcept, eu:PreferredTerm, range: URI. Aweb site that is relevant for the subject. Discarded.

• eu:status Domain: eu:ThesaurusConcept, eu:ThesaurusTerm, range: Three states:’valid’: for released terms and concepts; to be translated’: a term requiring furthertranslation; ’in maintenance’: a concept or term in maintenance. Discarded.

• eu:permutedLiteralForm Domain: xl:Label. Discarded.

• eu:qualifier Domain: eu:ThesaurusTerm, range: string. Label qualifier discriminat-ing the SKOS-XL label from other homographs in a specific language. Discarded.

• eu:termReleasedWithVersion Domain: eu:ThesaurusTerm, range: string. Thenumber of the EuroVoc release that introduced the term. Discarded.

• eu:eurLexReference Domain: any, range: URI. A direct hyperlink from a SKOSconcept, label or note to an Official Journal documents in the EUR-Lex database.Discarded.

• eu:isoCountryCode Domain: eu:country, range: string. The property value is anISO country code. Discarded.

• eu:language Domain: any, range: language. Identify a language of a resource.Discarded.

• eu:noteLiteral Domain: any, range: XMLLiteral. The property value is an XMLliteral which is structured as an xhtml.body.type content type. The schema anno-tation property allows content validation. Discarded.

The quality check has identified two concepts with overlapping preferred and alternativelabels:

1. European Association for Cooperation: in Serbian both labels are “EAC”.

2. Rio Group: in Estonian both labels are “Rio ruhm”.

Moreover, 27 different concepts have overlapping labels (with each other, not inside oneconcept).



Table 8: ESCO thesaurus

Homepage http://ec.europa.eu/esco/portal/home

Download source http://ec.europa.eu/esco/portal/download

License http://ec.europa.eu/geninfo/legal_notices_en.htm

Free usage XRDF X

Table 9: ESCO thesaurus statistics


2.6 ESCO

2.6.1 Overview

ESCO [De Smedt et al., 2015, le Vrang et al., 2014] is the multilingual classification ofEuropean Skills, Competences, Qualifications and Occupations. It identifies and cate-gorises skills and competences, qualifications and occupations relevant for the EU labourmarket and education and training, in 22 European languages. The system provides oc-cupational profiles showing the relationships between occupations, skills, competencesand qualifications. ESCO has been developed in an open IT format and is available foreveryone to use free of charge.

Some essential information about ESCO thesaurus is presented in Table 8. The overallnumber of labels and relations are presented in Tables 9 and 10 respectively.

The ESCO thesaurus is provided in a SKOS + SKOS-XL model in one data file.


ESCO aims at facilitating the following activities:

1. Bridging the communication gap between education and work;

2. Enabling easier matching of people to jobs;

3. Enabling mobility through translation of CVs and job descriptions;

4. Supporting education and training in the shift to learning outcomes;

5. Supporting skills intelligence and statistics.

ESCO can serve as a basis for other types of research, such as benchmarking and cross-


http://ec.europa.eu/esco/portal/home

http://ec.europa.eu/esco/portal/download

http://ec.europa.eu/geninfo/legal_notices_en.htm


Table 10: ESCO thesaurus statistics per language


Czech 10260 3600Danish 10260 5330German 10264 7647Greek 10260 5344English 11185 10636Spanish 10261 7423Estonian 10260 3406Finnish 10260 4069French 10263 8165Hungarian 10261 5368Italian 10261 4824Lithuanian 10260 5382Latvian 10260 3728Maltese 10260 6097Dutch 10265 5388Polish 10261 8393Portuguese 10261 5005Romanian 10261 7345Slovak 10261 5139Slovenian 10263 5637Swedish 10263 4860

Total 216408 122786



country comparison.


The ESCO thesaurus may be used for describing different skills required for some activ-ities in the economic space. For example, it can be used for describing the users of theplatform and for describing requirements for different educational materials.

2.6.4 Structure

The labour market is constantly evolving. The specific occupations, skills, competencesand qualifications that people need change over time, as does their description. To copewith this, effective communication and dialogue between the labour market and theeducation and training sector is vital. To facilitate this dialogue, ESCO is structuredon the basis of three pillars representing a searchable database in all ESCO languages.These pillars are:

• Occupations,

• Skills/competences, and

• Qualifications.

More importantly, the pillars are interlinked to show the relationships between them.Occupational profiles show whether skills and competences are essential or optional andwhat qualifications are relevant for each ESCO occupation. Alternatively, the user canidentify a specific skill and see which occupation or qualification this skill is relevant to.

2.6.5 Maintenance

DG Employment, Social Affairs and Inclusion supported by the European Centre for theDevelopment of Vocational Training (Cedefop) and by external stakeholders coordinatesthe development of ESCO.

Shaping ESCO into an up-to-date, practical tool can only be done from the bottomup, through the active involvement of people from the education and training sector aswell as from the labour market. Stakeholders contributing to the development of theclassification include:

• employers’ organisations

• trade unions

• employment services

• education institutions

• training organisations



• statistical organisations

• European and national sector skills councils and networks


The ESCO thesaurus is available in RDF. The data model is compatible with PoolParty,hence it can be imported without any further transformations.

After the import the quality checks implemented in PoolParty have identified that 25concepts are not included in any hierarchy (do not have broader concepts and are nottop concepts of any scheme). At least 10496 concepts have overlapping labels, hence,word sense disambiguation is needed to be able to extract correct concepts from a text.

2.7 NACE Rev. 2

2.7.1 Overview

The statistical classification of economic activities in the European Community[Kromhout et al., 2003, Schnabl and Zenker, 2013], abbreviated as NACE, is the clas-sification of economic activities in the EU; the term NACE is derived from the French“Nomenclature statistique des activites economiques dans la Communaute europeenne”.

NACE is a four-digit classification providing the framework for collecting and presentinga large range of statistical data according to economic activity in the fields of economicstatistics (e.g. production, employment and national accounts) and in other statisticaldomains developed within ESS.

NACE Rev. 2, a revised classification, was adopted at the end of 2006 and, in 2007, itsimplementation began. The first reference year for NACE Rev. 2 compatible statisticsis 2008, after which NACE Rev. 2 will be consistently applied to all relevant statisticaldomains.

Statistics produced on the basis of NACE are comparable at European and, in general,at world level. The use of NACE is mandatory within ESS.

Some essential information about NACE is presented in Table 11. The overall numberof labels and relations are presented in Tables 12 and 13 respectively. Note that germanlabels are only present as alternative labels.

4http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:NACE5http://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=LST_CLS_DLD&

StrNom=NACE_REV2&StrLanguageCode=EN&StrLayoutCode=HIERARCHIC#


http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:NACE

http://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=LST_CLS_DLD&StrNom=NACE_REV2&StrLanguageCode=EN&StrLayoutCode=HIERARCHIC#

http://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=LST_CLS_DLD&StrNom=NACE_REV2&StrLanguageCode=EN&StrLayoutCode=HIERARCHIC#


Table 11: NACE Rev. 2 thesaurus

Homepage 4

Download source 5

License http://creativecommons.org/licenses/by/4.0/

Free usage XRDF

⊗

Table 12: NACE Rev. 2 statistics



NACE presents the universe of economic activities partitioned in such a way that aNACE code can be associated with a statistical unit carrying them out.

All observations that are to be described in terms of statistics require systematic clas-sification. Classifications partition the universe of statistical observations according tosets that are as homogeneous as possible with respect to the characteristics of the objectof the statistical survey.

Statistical classifications are characterised by:

• exhaustive coverage of the observed universe;

• mutually exclusive categories: each element should be classified in only one cate-gory of the classification;

• methodological principles which allow the consistent allocation of the elements tothe various categories of the classification.

• NACE is the European standard classification of productive economic activities.

An economic activity takes place when resources such as capital goods, labour, manu-facturing techniques or intermediary products are combined to produce specific goodsor services. Thus, an economic activity is characterised by an input of resources, aproduction process and an output of products (goods or services).

An activity as defined here may consist of one simple process (for example weaving), butmay also cover a whole range of sub-processes, each mentioned in different categories ofthe classification (for example, the manufacturing of a car consists of specific activitiessuch as casting, forging, welding, assembling, painting, etc.). If the production processis organised as an integrated series of elementary activities within the same statisticalunit, the whole combination is regarded as one activity.


http://creativecommons.org/licenses/by/4.0/


Table 13: NACE Rev. 2 statistics per language


German 0 15028English 6521 3037

Total 6521 18065

NACE does not draw distinctions according to the kind of ownership of a production unitor its type of legal organisation or mode of operation, because such criteria do not relateto the characteristics of the activity itself. Units engaged in the same kind of economicactivity are classified in the same category of NACE, irrespective of whether they are(part of) incorporated enterprises, individual proprietors or government, whether or notthe parent enterprise is a foreign entity and whether or not the unit consists of more thanone establishment. Therefore, there is no link between NACE and the Classification ofInstitutional Units in the System of National Accounts (SNA) or in the European Systemof Accounts (ESA).

The manufacturing activities are described independently of whether the work is per-formed by power-driven machinery or by hand, or whether it is done in a factory or ina household. Modern versus traditional is not a criterion for NACE.

NACE does not distinguish between formal and informal or between legal and illegalproduction. Classifications according to kind of legal ownership, kind of organisation ormode of operation may be constructed independently. Cross-classification with NACEcould provide useful extra information.

In general, NACE does not differentiate between market and non-market activities, asdefined in the SNA/ESA, even if this distinction is an important feature of the SNA/ESA.A breakdown of economic activities according to this principle is useful in any case wheredata are collected for activities that take place on both a market and a non-marketbasis. This criterion should then be cross-classified with the categories of NACE. Non-market services in NACE are only provided by government organisations or non-profitinstitutions serving households, mostly in the field of education, health, social work, etc.


The thesaurus contains a detailed classification of different field of economy. This the-saurus may be useful for describing the economic situation in general and for annotatingthe articles about particular economic activities, for example, articles about manufac-turing or trading activities.



2.7.4 Structure

NACE consists of a hierarchical structure (as established in the NACE Regulation), theintroductory guidelines and the explanatory notes. The structure of NACE is describedin the NACE Regulation6 as follows:

1. a first level consisting of headings identified by an alphabetical code (sections),

2. a second level consisting of headings identified by a two-digit numerical code (di-visions),

3. a third level consisting of headings identified by a three-digit numerical code(groups),

4. a fourth level consisting of headings identified by a four-digit numerical code(classes).

The code for the section level is not integrated in the NACE code that identifies thedivision, the group and the class describing a specific activity. For example, the activityManufacture of glues is identified by the code 20.52, where 20 is the code for the division,20.5 is the code for the group and 20.52 is the code of the class; section C, to which thisclass belongs, does not appear in the code itself.

The divisions are coded consecutively. However, some “gaps” have been provided toallow the introduction of additional divisions without a complete change of the NACEcoding. These gaps have been introduced in sections that are most likely to prompt theneed for additional divisions. For this purpose, the following division code numbers havebeen left unused in NACE Rev. 2: 04, 34, 40, 44, 48, 54, 57, 67, 76, 83 and 89.

In cases where a given level of the classification is not divided further down in the classi-fication, 0 is used in the code position for the next more detailed level. For example, thecode for the class Veterinary activities is 75.00 because the division Veterinary activities(code 75) is divided neither into groups nor into classes. The class Manufacture of beeris coded as 11.05 since the division Manufacture of beverages (code 11) is not dividedinto several groups but the group Manufacture of beverages (code 11.0) is divided intoclasses.

Whenever possible, residual groups or classes of the type “others” and/or n.e.c. (notelsewhere classified) are characterised by the digit 9 (for instance group 08.9 Mining andquarrying n.e.c. and class 08.99 Other mining and quarrying n.e.c.).

2.7.5 Maintenance

The Commission, in cooperation with the Member States, shall ensure the dissemination,maintenance and promotion of NACE Rev. 2, in particular by:

• drafting, updating and publishing explanatory notes for NACE Rev. 2;

6http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:393:0001:0039:EN:PDF


http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:393:0001:0039:EN:PDF


• drawing up and publishing guidelines for classifying statistical units in accordancewith NACE Rev. 2;

• publishing correspondence tables between NACE Rev. 1.1 and NACE Rev. 2 andbetween NACE Rev. 2 and NACE Rev. 1.1; and

• working to improve consistency with other social and economic classifications.

The Commission shall be assisted by the Statistical Programme Committee, establishedby Decision 89/382/EEC, Euratom.


The classification NACE Rev. 2 is originally distributed in XKOS7 format, whichis a special extension of SKOS for managing statistical data. However, this exten-sion is backwards compatible, i.e. it is possible to translate an XKOS taxonomy intoSKOS taxonomy. For this purpose the hierarchical relations were explicitly written inbroader/narrower SKOS relations. The inherited properties of such transformation isthat there are no poly-hierarchies and no related relations.

No issues were identified by the quality check.

2.8 Examples from partners

Several sources of concepts were suggested by partners.

Glossaries from educational books about personal finances were suggested by Universityof Glasgow. After processing to a machine readable format the resulting three lists ofconcepts contained 18, 67, and 180 concepts respectively. An analysis has shown that atleast half of the concepts in the lists are present in the imported thesauri STW Economicsand Eurovoc. The concepts require further revision from the financial experts and will beintegrated (if identified as useful) in the process of creating PROFIT knowledge graph.

A hierarchy of classes, concepts, and relations was supplied by DUTH. This data wasused to identify if the imported thesauri and ontologies may be used for describing thefield of interest. It was identified that STW Economics has a good coverage, however, notall concept schemes are useful. On the other hand, the useful concept schemes requireextension. This work will be performed in the process of creating PROFIT knowledgegraph and will be supported by a relevant corpus to identify potential gaps and usefulconcepts. This work will be report in Month 12 in D 2.4 “PROFIT knowledge graph”.

7http://rdf-vocabulary.ddialliance.org/xkos.html


http://rdf-vocabulary.ddialliance.org/xkos.html


3 Ontologies

3.1 Introduction

The ontologies allow for describing resources via custom relations and attributes. Therelations and attributes may themself have additional properties [Baader et al., 2010].For this purpose classes of instances are defined in ontologies and to each classes a setof custom relations and attributes is associated. If a concept is assigned to belong to aspecific class then the custom relations and attributes become available for it.

Having a well structured ontology and a thesaurus where the classes and relations of theontology are used enables one to perform even more complicated mechanism to revealthe semantic connections between individual pieces of data. For example, an ontology fordescribing users allows for describing individual facts about the activity of different usersrelated to particular content. Later on these facts may be used to extract the preferencesand, probably, the knowledge of individual users to be able to better recommend himinteresting content.

The construction of an ontology in a domain is a very complex task in general. Luckily,in frames of PROFIT there is a particular goal defined for the ontologies: they shouldfacilitate a more detailed description of particular resources in order to improve thematching mechanisms (which will be used for the recommendation engine). Hence it isnecessary to be able to describe individual pieces of data up to the level where they areclearly distinguishable from each other (if the distinctions exist).

In order to make the resulting ontologies available for reusage and understand-able to the linked data community it is essential to reuse the existing ontologies[Gomez-Perez and Benjamins, 1999, Cuenca Grau et al., 2008]. Therefore this sectionis devoted to describing existing ontologies and their usage in PoolParty.

3.2 Mapping to PoolParty format

One of the most popular specifications for describing ontologies is OWL8. In PoolPartynot all the expressive capabilities of OWL are supported. Although PoolParty does notcapture many expressive capabilities of OWL it is usually sufficient for modelling ap-plications. The advantage of shrinking the expressiveness is the extended sustainabilityand speed of working with the ontology. Moreover, a constrained language is much easierfor understanding and interpretation.

For some elements of OWL PoolParty defines own elements. The mappings betweendifferent formats is presented in Table 14. The corresponding substitutions are done foreach ontology imported into PoolParty.

Some elements are not supported in PoolParty, hence all of its occurrences are deleted

8http://www.w3.org/TR/owl2-overview/


http://www.w3.org/TR/owl2-overview/


Table 14: Custom ontology to PoolParty mappings

Standard Ontology PoolParty Ontology

owl:ObjectProperty swcs:DirectedPropertyowl:DatatypeProperty swcs:AttributePropertyowl:Class rdfs:Class:subject a owl:FunctionalProperty :subject swcs:unique true:subject owl:inverseOf :object {:subject a swcs:PropertyWithInverse;

owl:inverseOf :object.}rdfs:domain swcs:domainrdfs:range swcs:range or

swcs:valueRestrictionrdfs:subClassof rdfs:subClassOfxsd:string Literalxsd:decimal Floatxsd:language Literalxsd:anyURI URIxsd:boolean Booleanxsd:dateTime, xsd:Date, xsd:dateTimeStamp Datexsd:integer Integer

in all the imported ontologies. The most important and frequent ones are listed below:

1. blank nodes,

2. rdfs:subPropertyOf,

3. owl:disjointWith,

4. owl:unionOf,

5. owl:intersectionOf,

6. owl:Restriction,

7. owl:minQualifiedCardinality,

8. owl:maxQualifiedCardinality,

9. owl:equivalentClass,

10. owl:equivalentProperty.



Table 15: FIBO ontology

Homepage http://www.edmcouncil.org/financialbusiness

Download source http://www.omg.org/hot-topics/finance.htm

License not clear9

Free usage XOWL X

Table 16: FIBO statistics

Number of classes 152Number of relations 112Number of attributes 33

3.3 FIBO

3.3.1 Overview

FIBO [Bennett, 2014, Bennett, 2013] is a modularized formal model of the concepts rep-resented by finance industry terms as used in official financial organization documentssuch as contracts, product/service specifications and governance and regulatory compli-ance documents. This is referred to as a Business Conceptual Model as distinct frommodels or descriptions of data or IT implementations. The scope of finance industry en-compasses a broad range of organizations that manage money, including credit unions,banks, credit card companies, insurance companies, consumer finance companies, stockbrokerages, investment funds and some government sponsored enterprises.

At this moment only the Foundations module of FIBO is finalized. This module containsmost general and widely used class and attributes. These classes are probably mostappropriate to be used in frames of PROFIT project since they describe the financialconcepts without too many details. Since PROFIT is not tailored towards a specificexpert audience, these classes and attributes should lay a sufficient basis.

Some essential information about FIBO is presented in Table 15. The overall number ofclasses, relations, and attributes after the transformation are presented in Table 16.


The Foundations module of FIBO is a set of business concepts which are intended tosupport the financial industry terms semantics presented in other FIBO specifications(like “Business Entities” or “Indices and Indicators”). Foundations is itself segmented

9Some information can be found in http://www.omg.org/spec/EDMC-FIBO/FND/1.0/PDF/index.htm


http://www.edmcouncil.org/financialbusiness

http://www.omg.org/hot-topics/finance.htm

http://www.omg.org/spec/EDMC-FIBO/FND/1.0/PDF/index.htm


into a number of models or ontologies. The FIBO Foundations models define generalconcepts that are not unique to the financial industry, but needed to help define thefinancial concepts. FIBO Foundations therefore includes a number of basic legal, con-tractual and organizational concepts, among others. Concepts which are available inother industry standards are not included, but in some cases a “proxy” concept is in-cluded for reference, for example for address and country concepts. The rationale forincluding these is two-fold:

• Concepts in the financial industry are generally specializations of more general,non-financial concepts such as contracts, commitments, transactions, organizationsand so on, These are included in FIBO Foundations so that specializations of themmay be defined in other FIBO specifications.

• Properties of financial industry concepts frequently need to be framed in terms ofrelationships to non-financial concepts such as countries, jurisdictions, addressesand the like. These are included in FIBO Foundations so that properties in otherFIBO specifications may make reference to them.

One of the key benefits of FIBO with respect to data, message, or reasoning metamodelsis that it can provide a semantic anchor firmly rooted in the concepts as understood andused by people in the finance industry. FIBO enables the creation of logical data modelssuch that those logical models derive their formal semantics from FIBO.

FIBO supports the derivation of ontologies to support semantic reasoning and queryingapplications. Since FIBO itself is framed using the formal constructs of the OWL lan-guage, such operational ontologies may be derived directly from the FIBO conceptualontologies, with adaptation as necessary to support any application specific constraints.

FIBO allows disambiguation of new and existing regulation. To the extent that regu-latory requirements reference the formal concepts in FIBO, terms referred to in theseregulatory requirements, or in reports that are mandated, would be semantically unam-biguous.

One important goal of FIBO is for the formal business definitions to be used in legaldocuments such as contracts, terms and conditions of sales and payment, IP protec-tion, compliance reports; and to underpin less formal language used in advertising andcustomer-facing websites.

The business terms and definitions in this specification may be used as a reference modelto which firms would tie their own proprietary models (semantic models or ontologies);and also as a catalogue for all of the relevant data models.


The FIBO ontology may become a new standard vocabulary in the financial and eco-nomical areas. Since the linked data should be made rediscoverable usage of such aprominent ontology may add a lot of value to the final knowledge graph. However, so



Figure 1: Foundations Ontology Architecture

far the work on FIBO is ongoing and only a small portion of FIBO is available. Partnershave claimed that many necessary classes are not yet available in FIBO Fundamentals,hence, only some parts of this ontology may be reused.

3.3.4 Structure

An approach to the foundational terminology that provides very high-level, abstractconceptual knowledge designed to facilitate mapping is an important design goal ofFIBO Foundations.

Proxy concepts for Goal, Objective, Address, and Country, for example, that are in-cluded in the Foundations with little embellishment, are designed to provide hooks formapping to the OMGs Business Motivation Model, ISO standards for Country coderepresentations, US Publication 28 and other national postal addressing standards, andso forth. The basic building blocks for the Foundations Ontology are shown in Figure 1.

As shown in the diagram, the Foundations ontologies are divided up into a numberof modules. For example, the Utilities module includes: a general purpose Busi-nessTypes.owl ontology, a general Relations.owl ontology, and an AnnotationVocabu-lary.owl ontology that captures FIBO-specific annotations. The Foundations moduleswill ultimately depend on (1) Basic Terminology and Ontology Metadata (in light grayin the figure), and (2) a number of external modules, representing concepts for NaturalLanguage, Geopolitical Entities (for example ISO 3166 Country codes, regional, andmunicipal designations), Postal Addressing (from standards such as US Publication 28),and concepts defining dates, times, calendars, and schedules. A sample set of theseanticipated external resources are given in the dark gray layer in the figure.



Table 17: FIBO to PoolParty datatypes mapping

FIBO Ontology PoolParty Ontology

bt:text Literalfd:dateValue Literalfd:durationValue Literalbt:yesOrNo Booleanbt:basicPoints Integerbt:wholeNumber Integerbt:negativeWholeNumber Integerbt:nonNegativeWholeNumber Integerbt:positiveWholeNumber Integerbt:postivieInteger Integerbt:integer Integerbt:number Floatbt:nonNegativeNumber Floatbt:percentageValue Floatbt:restrictedPercentageValue Float

3.3.5 Maintenance

FIBO is developed and maintained by the members of the EDM Council10.

3.3.6 Mapping to PoolParty format

Different sub-ontologies of Foundations are collected in one ontology. In the Foundationsown datatypes are defined. These datatypes are mapped to PoolParty datatypes, seeTable 17.

3.4 Schema.org

3.4.1 Overview

Schema.org [Mika and Potter, 2012, Patel-Schneider, 2014] is a collaborative, commu-nity activity with a mission to create, maintain, and promote schemas for structureddata on the Internet, on web pages, in email messages, and beyond.

Schema.org vocabulary can be used with many different encodings, including RDFa, Mi-crodata and JSON-LD. These vocabularies cover entities, relationships between entitiesand actions, and can easily be extended through a well-documented extension model.Over 10 million sites use Schema.org to markup their web pages and email messages.

10http://www.edmcouncil.org/financialbusiness


http://www.edmcouncil.org/financialbusiness


Table 18: Schema.org ontology

Homepage https://schema.org/

Download source 11

License 12

Free usage XOWL

⊗

Table 19: Schema.org statistics


Many applications from Google, Microsoft, Pinterest, Yandex and others already usethese vocabularies to power rich, extensible experiences.

Schema.org is sponsored by Google, Microsoft, Yahoo and Yandex. The vocabulariesare developed by an open community process.

A shared vocabulary makes it easier for webmasters and developers to decide on a schemaand get the maximum benefit for their efforts. It is in this spirit that the sponsors,together with the larger community have come together, to provide a shared collectionof schemas.

Some essential information about Schema.org is presented in Table 18. The overallnumber of classes, relations, and attributes after the transformation are presented inTable 19.


Schema.org provides a collection of shared vocabularies webmasters can use to markup their pages in ways that can be understood by the major search engines: Google,Microsoft, Yandex and Yahoo!


The ontology is simple to use and understand and at the same time well structuredand comprising a lot of generic classes. For example, subclasses of “Product” and “In-tangible” and these classes themselves have been identified by partners (DUTH and

11https://raw.githubusercontent.com/schemaorg/schemaorg/sdo-deimos/data/releases/2.2/

schema.nt12https://github.com/schemaorg/schemaorg/blob/sdo-deimos/LICENSE


https://schema.org/

https://raw.githubusercontent.com/schemaorg/schemaorg/sdo-deimos/data/releases/2.2/schema.nt

https://raw.githubusercontent.com/schemaorg/schemaorg/sdo-deimos/data/releases/2.2/schema.nt

https://github.com/schemaorg/schemaorg/blob/sdo-deimos/LICENSE


University of Glasgow) to be useful. The final ontologies of the PROFIT knowledgegraph may reuse parts of Schema.org.

3.4.4 Structure

The schemas are a set of ’types’, each associated with a set of properties. The types arearranged in a hierarchy.

The top level of the hierarchy consists of the following types: “Product”, “Person”,“Place”, “Organization”, “MedicalEntity”, “Intangible”, “Event”, “CreativeWork”, and“Action”. Each of these types have further subtypes (except of “Person”).

3.4.5 Maintenance

Schema.org is organized via two groups: a small Steering Group responsible for highlevel oversight of the project (including approval of new releases), and a larger Commu-nity Group which handles the day to day activity of schema evolution, discussion andintegration. Schema.org’s Community Group prepares releases for the approval of theSteering Group.

The Schema.org Steering Group is chaired by R.V. Guha. The regular Steering Groupinclude participants from Yahoo, Yandex, Microsoft, Google. In April 2015 the SteeringGroup unanimously agreed to expand its membership to include Stphane Corlosquetand Martin Hepp, and to offer a seat to a representative from W3C. The Steering Grouphas a mailing list - mostly used for scheduling periodic phone/skype/etc calls, whosenotes are posted to public GitHub13.

The Schema.org Community Group is chaired by Dan Brickley. It is open to any inter-ested parties who have agreed to the W3C Community Contributor License Agreement.The role of the Community Group is to propose, discuss, prepare and review changesto schema.org, for final review and publication by the Steering Group. The CommunityGroup also serves as a hub for discussion with other related communities, at W3C andelsewhere. The schema.org GitHub repository is considered a tool of the CommunityGroup, and is currently the main focus for community discussion.


Schema.org ontology contains special enumeration types. These are not supported byPoolParty and are discarded in the transformation process.

PoolParty makes a distinction between relations and attributes, there is no such dis-tinction in Schema.org. This distinction was introduced in the transformation processresulting in 480 relations and 510 attributes.

13https://github.com/schemaorg/schemaorg


https://github.com/schemaorg/schemaorg


Table 20: Provenance ontology

Homepage http://www.bbc.co.uk/ontologies/provenance

Download source http://www.bbc.co.uk/ontologies/provenance/1.9.ttl


Free usage XOWL X

Table 21: Provenance statistics


3.5 Provenance

3.5.1 Overview

The provenance ontology supports data management and auditing tasks. It is used todefine the different types of named graphs we used in the store (quad store) and enablestheir association with metadata that allow BBC to manage, validate and expose data toBBC services.

Some essential information about Provenance is presented in Table 20. The overallnumber of classes, relations, and attributes after the transformation are presented inTable 21.

As an alternative to the provenance ontology there exists the ontology prov-o https:

//www.w3.org/TR/prov-o/. The two ontologies serve the same purpose. Since thepartners from CERTH have suggested the provenance ontology and they have experiencewith this ontology it was decided to import it and not the prov-o ontology.

3.5.2 Objectives

An ontology to capture data about the provenance of data in an RDF Triple Store. Thisprovenance is focused on the immediate providers and not the ultimate source, so forexample, this would record that geodata was provided by the BBC Locator team, andnot geonames.


http://www.bbc.co.uk/ontologies/provenance

http://www.bbc.co.uk/ontologies/provenance/1.9.ttl


https://www.w3.org/TR/prov-o/

https://www.w3.org/TR/prov-o/


Figure 2: Provenance ontology diagram


The ontology was suggested by the partners from CERTH. The ontology may be use-ful for describing different versions of content in the PROFIT platform, for example,educational resources.

3.5.4 Structure

The diagram of the Provenance ontology is presented in Figure 2.

3.5.5 Maintenance

The ontology is produced and maintained by BBC.


Though the original ontology is quite small, it makes use of other ontologies developedby BBC. Therefore, these ontologies have to be imported as well. Except for the Taggingontology, which is not available (probably, broken link), all the necessary ontologies wereimported, for example, the product and cms ontologies. All the restrictions containingclasses from Tagging ontologies were eliminated.



Table 22: Public Contract ontology

Homepage https://github.com/opendatacz/public-contracts-ontology

Download source https://github.com/opendatacz/public-contracts-ontology


Free usage XOWL X

Table 23: Public Contract ontology statistics


3.6 Public Contracts

3.6.1 Overview

The Public Contracts Ontology serves to express structured data about public contractsin RDF.

Some essential information about Public Contracts ontology is presented in Table 22.The overall number of classes, relations, and attributes after the transformation arepresented in Table 23.


The design of the Public Contracts ontology was informed by the work of others, bothontologies and vocabularies of RDF and non-RDF origin. Its design strives to align itwith other related projects, for example, in adopting established terminology for namingor re-using existing components.

The ontology builds on top of another ontology: GoodRelations. GoodRelations is usedfor description of business entities, such as cities publishing public procurement tendersor commercial companies applying for them. The specification of prices is based on thesame vocabulary.


The ontology extends the Schema.org ontology with some classes related to contractnegotiations. These classes with corresponding relations and attributes may be used


https://github.com/opendatacz/public-contracts-ontology

https://github.com/opendatacz/public-contracts-ontology



Figure 3: Public Contract ontology diagram

in the description of some financial agents and their agreements. For example, somecontracts where the users of PROFIT or the ethical banks participate.

3.6.4 Structure

The diagram of the Public Contracts ontology is presented in Figure 3.

3.6.5 Maintenance

The ontology is developed and maintained by the Czech OpenData.cz initiative.


The Public Contract ontology uses external ontologies such as goodrelation, c4n, loted,payment, qb, vann. These ontologies are not modelled in PoolParty and are not identi-fied for usage in PROFIT project, therefore mentions of these ontologies were eliminated.These mentions were used for describing range and domain restrictions of some proper-ties; now these ranges and domains are not constrained.



Table 24: MARL ontology

Homepage http://marl.gi2mo.org/?page_id=1

Download source http://marl.gi2mo.org/0.2/ns.owl


Free usage XOWL X

Table 25: MARL statistics


3.7 MARL

3.7.1 Overview

Marl is a standardised data schema (also referred as ”ontology” or ”vocabulary”) de-signed to annotate and describe subjective opinions expressed on the web or in particularInformation Systems.


The goals of the Marl ontology are:

• enable to publish raw data about opinions and the sentiments expressed in them,

• deliver schema that will allow to compare opinions coming from different systems(polarity, topics, features),

• interconnect opinions by linking them to contextual information expressed withconcepts from other popular ontologies or specialised domain ontologies.


The ontology was suggested by the partners from CERTH. The ontology may be usedto describe opinions of the users of the platform about particular pieces of information,for example, news articles or posts by other users. This description may be used in theprocess of sentiment analysis or during the discovery of users’ preferences.


http://marl.gi2mo.org/?page_id=1

http://marl.gi2mo.org/0.2/ns.owl



Figure 4: MARL ontology diagram

3.7.4 Structure

The diagram of the MARL ontology is presented in Figure 4.

3.7.5 Mapping to PoolParty

For the attributes in the MARL ontology no ranges were defined. As ranges are requiredin PoolParty the value restriction “Literal”, “Float”, and “Integer” were added accordingto the description of the original ontology.

3.8 Some further ontologies

3.8.1 FISE

The FISE ontology is developed to support text annotation. The ontology is maintainedby the Apache foundation and is open for free usage. The ontology provides a structurefor describing annotations. Though the ontology was imported in PoolParty it will mostlikely not be used since PoolParty makes use of its own ontology for this purpose.



3.8.2 Friend of a friend

The FOAF ontology is a well established ontology and is widely used. This ontology isdevoted to linking people and information using the Web. The ontology is well suitablefor describing persons, their data like phone numbers and webpages, and their relationsto each other. This ontology is available as a default ontology in PoolParty and may beused in future to describe relations between different users of the PROFIT platform.

3.8.3 Dublin Core Metadata Terms

The Dublin Core metadata terms are a set of vocabulary terms which can be used todescribe resources for the purposes of discovery. The ontology contains such elementsas Title, Creator, Subject, Description, Publisher, Contributor, Date, Type, Format,Identifier, Source, Language, Relation, Coverage, Rights. This is a standard ontologywidely used on the web. The ontology is available in PoolParty as a default ontology.



Table 26: PROFIT User ontology statistics


4 PROFIT Core Ontology

4.1 Introduction

We present two ontologies created for PROFIT project and based on the reusage (whenpossible) classes for the existing ontologies. This ontologies define the core structure ofthe knowledge model and are specifically designed to offer a possibility for extension ifneeded. The ontologies capture the most high level classes and relations and are tailoredto be useful for the widest ranges of concepts from the discourse of the PROFIT project.

4.2 User Actions Ontology

4.2.1 Overview

The ontology will be used to describe the interaction of the users with the platform. Thekey numbers are presented in Table 26.


The ontology is designed to be able to capture the main acts of interaction with theplatform as determined in the requirements engineering process in WP1:

• User follow other users;

• User may take different actions: create, rate, comment, etc.;

• User may leave feedback on their own content, content created by other users,content uploaded by platform creators;

• User may express their opinion;

• User may initiate and take part in interactive content: polls, assessment tests.

4.2.3 Structure

The diagram of the PROFIT User ontology is presented in Figure 5.

The users are represented by the “Person” class taken from Schema.org ontology. The



Figure 5: PROFIT User ontology diagram



Table 27: PROFIT Finance ontology statistics


actions that may be taken by users fall into “Action” and “InteractAction” classes takenfrom Schema.org as well. These actions are connected to different subclasses of Cre-ativeWork: “EducationalMaterial”, “InteractiveCreativeWork”, and “InteractiveEdu-cationalMaterial”. Further on, users may express “Opinion” (taken from the MARLontology). Multiple opinions may be collected in AggregatedOpinion in order to analysethe reputation of a certain CreativeWork instance. This ontology is accompanied by arelated taxonomy of users, actions, and creative works, see Figure 6. This taxonomymay be extended by further actions and creative work items.

4.3 Finance Ontology

4.3.1 Overview

The ontology will be used to classify the main financial instances that will be foundin news articles, user input (blogs, comments), and in educational materials. The keynumbers are presented in Table 27.


The ontology enables the partners in the consortium to describe the high-level contentof the objects they deal with. For example, news articles may be described by theeconomic agents mentioned in the article and the financial objects mentioned there andthe relation between these objects.

4.3.3 Structure

The diagram of the PROFIT Finance ontology is presented in Figure 7.

The most important classes are “EconomicAgent”, “EconomicFactor”, “EconomicOrga-nization”, “EconomicSector”, “EconomicVariable”, “FinancialInstitution”, “Financial-System”, “FinancialObject”, “Product”, “country”. These classes constitute a high levelstructure for the description of the contents of financial materials. Some helper classesand relations are taken from other ontologies: Dublin Core Metadata, FIBO Founda-tions, and Schema.org. The ontology is well suited to capture the main features withoutfurther details, therefore offering a broad range of usages. On the later stages of the



Figure 6: PROFIT User taxonomy



Figure 7: PROFIT Finance ontology diagram



project when the educational materials are ready the ontology could be extended inorder to described more detailed differences between different materials.

This ontology in contrast to the user ontology is not accompanied by a thesaurus. Thisaccompanying financial thesaurus will be developed in course of D 2.4 “PROFIT knowl-edge graph”, due in Month 12.



5 Future Work

The existing thesauri or their parts will be fused into one or several PROFIT thesauri.The PROFIT thesauri will then be extended depending on the needs of the experts. Inorder to do this a semi-automatic procedure will be implemented. The procedure willmake use of a relevant corpus identified by experts, for example, specific parts of thearchive from http://investing.com related to crude oil. The annotations found in thecorpus will indicate which parts of the thesauri are relevant and should be reused. Onthe other hand, some poorly annotated documents will be presented to the expert witha list of possible new concepts for their annotation. These new concepts will be addedto the thesauri and the procedure will be repeated until all the relevant documents willbe well annotated from the expert’s point of view.

The ontology will be further extended mainly by hand. A graphical representation ofontologies will be used to facilitate the efforts of the experts.


http://investing.com


6 Conclusion

The deliverable represents the results of preparation of PROFIT core knowledge model.In the course of this activity the following was done:

1. A dedicated server http://profit.poolparty.biz was setup and a correspondingtraining was conducted. PoolParty runs at the server, the server has a dedicatedNoSQL data storage.

2. Related thesauri were identified and imported into PoolParty. For most importantthesauri were imported: STW Economics, EuroVoc, ESCO, NACE Rev. 2.

3. Important parts of thesauri were identified in the communication with the part-ners. This information will be used in the forthcoming D 2.4 “PROFIT knowledgegraph”. The process of preparing PROFIT thesaurus will start from reusing STWEconomics thesaurus.

4. Related ontologies were identified and imported into PoolParty: FIBO,Schema.org, MARL, Public Contracts, Provenance.

5. Two PROFIT ontologies were prepared; the ontologies incorporate the data fromthe imported ontologies and the outcome of multiple discussions with the partners;these ontologies will be further extended when the results of WP3 and WP4 areready.

6. Concrete tasks for future work (D 2.4) were agreed: analysis of related corpora,reusage and extension of the existing thesauri.


http://profit.poolparty.biz


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[Patel-Schneider, 2014] Patel-Schneider, P. F. (2014). The Semantic Web – ISWC 2014:13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23,2014. Proceedings, Part I, chapter Analyzing Schema.org, pages 261–276. SpringerInternational Publishing, Cham.

[Schnabl and Zenker, 2013] Schnabl, E. and Zenker, A. (2013). Statistical classificationof knowledge-intensive business services (KIBS) with NACE Rev. 2. Fraunhofer ISI.

[Steinberger et al., 2013] Steinberger, R., Ebrahim, M., and Turchi, M. (2013). JRCeurovoc indexer JEX - A freely available multi-label categorisation tool. CoRR,abs/1309.5223.

[Steinberger et al., 2002] Steinberger, R., Pouliquen, B., and Hagman, J. (2002). Com-putational Linguistics and Intelligent Text Processing: Third International Confer-ence, CICLing 2002 Mexico City, Mexico, February 17–23, 2002 Proceedings, chap-ter Cross-Lingual Document Similarity Calculation Using the Multilingual ThesaurusEUROVOC, pages 415–424. Springer Berlin Heidelberg, Berlin, Heidelberg.



Appendices

A PROFIT User Ontology

In this appendix a copy of the published version of the PROFIT user ontology is pre-sented. The published version of the PROFIT user ontology is available at http:

//profit.poolparty.biz/PROFIT-User.html.


http://profit.poolparty.biz/PROFIT-User.html

http://profit.poolparty.biz/PROFIT-User.html

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Custom Ontology PROFIT User

Navigation Panel

Classes (17) Moderator

Relations (15)

⇒ Directed (2) subsribedTo

⇒ Symmetric (1) inContactWith

⇒ With Inverse (12) mentionedIn

Attributes (10) firstName

Scheme description

http://profit.poolparty.biz/PROFIT‐User (rdf:type ‐ http://schema.semantic‐web.at/ppt/CustomOntology)

dcterms:description n/a

Classes

Moderator (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Moderator

rdfs:subClassOf User

InteractiveCreativeWork (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label InteractiveCreativeWork

rdfs:subClassOf CreativeWork

ModeratorAction (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label ModeratorAction

rdfs:subClassOf Action

InteractiveUserCreativeWork (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label InteractiveUserCreativeWork

rdfs:subClassOf UserCreativeWork

rdfs:subClassOf InteractiveCreativeWork

User (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label User

rdfs:subClassOf Person

EducationalWork (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label EducationalMaterial


UserCreativeWork (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label UserCreativeWork


InteractiveEducationalMaterial (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label InteractiveEducationalMaterial

rdfs:subClassOf InteractiveCreativeWork

rdfs:subClassOf EducationalWork

Report (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Report

rdfs:subClassOf Article





Opinion (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Opinion

InteractAction (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label InteractAction

rdfs:subClassOf Action

Action (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Action

rdfs:subClassOf Thing

AggregatedOpinion (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label AggregatedOpinion

rdfs:subClassOf Opinion

Thing (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Thing

Person (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Person


Article (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Article


CreativeWork (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label CreativeWork


Relations

Directed

subsribedTo (rdf:type ‐ http://schema.semantic‐web.at/ppt/DirectedProperty)

rdfs:label subsribedTo

Domain [http://schema.org/Person]

SKOS Domain Concept

Range [http://schema.org/Person]

SKOS Range Concept

Unique false

follows (rdf:type ‐ http://schema.semantic‐web.at/ppt/DirectedProperty)

rdfs:label follows


SKOS Domain Concept


SKOS Range Concept

Unique false

Symmetric

inContactWith (rdf:type ‐ http://www.w3.org/2002/07/owl#SymmetricProperty)

rdfs:label inContactWith


SKOS Domain Concept






SKOS Range Concept

Unique false

With Inverse

mentionedIn (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label mentionedIn

SKOS Domain Concept

Range [http://purl.org/marl/ns#Opinion, http://schema.org/Report]

SKOS Range Concept

Unique false

owl:inverseof isAbout

madeBy (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label madeBy

Domain [http://schema.org/Action]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof makes

takenBy (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label takenBy

Domain [http://profit.poolparty.biz/PROFIT‐User/ModeratorAction]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐User/Moderator]

SKOS Range Concept

Unique false

owl:inverseof takes

isFavouriteOf (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isFavouriteOf

Domain [http://schema.org/CreativeWork]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof addedToFavourites

affectedBy (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label affectedBy

Domain [http://schema.org/CreativeWork]

SKOS Domain Concept

Range [http://schema.org/Action]

SKOS Range Concept

Unique false

owl:inverseof affects

addedToFavourites (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label addedToFavourites






SKOS Domain Concept

Range [http://schema.org/CreativeWork]

SKOS Range Concept

Unique false

owl:inverseof isFavouriteOf

makes (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label makes


SKOS Domain Concept

Range [http://schema.org/Action]

SKOS Range Concept

Unique false

owl:inverseof madeBy

affects (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label affects

Domain [http://schema.org/Action]

SKOS Domain Concept

Range [http://schema.org/CreativeWork]

SKOS Range Concept

Unique false

owl:inverseof affectedBy

takes (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label takes

Domain [http://profit.poolparty.biz/PROFIT‐User/Moderator]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐User/ModeratorAction]

SKOS Range Concept

Unique false

owl:inverseof takenBy

isAbout (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isAbout

Domain [http://purl.org/marl/ns#Opinion, http://schema.org/Report]

SKOS Domain Concept

SKOS Range Concept

Unique false

owl:inverseof mentionedIn

extractedFrom (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label extractedFrom

Domain [http://purl.org/marl/ns#Opinion]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof hasOpinion





hasOpinion (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label hasOpinion


SKOS Domain Concept

Range [http://purl.org/marl/ns#Opinion]

SKOS Range Concept

Unique false

owl:inverseof extractedFrom

Attributes

firstName (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label fullName


SKOS Domain Concept

Valuerestriction Label

Unique true

email (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label email


SKOS Domain Concept

Valuerestriction Literal

Unique false

gender (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label gender


SKOS Domain Concept

Valuerestriction Label

Unique false

birthDate (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label birthDate


SKOS Domain Concept

Valuerestriction Date

Unique true

negativeOpinionCount (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label negativeOpinionCount

Domain [http://purl.org/marl/ns#AggregatedOpinion]

SKOS Domain Concept

Valuerestriction Integer

Unique false

opinionText (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label opinionText


SKOS Domain Concept

Valuerestriction Literal

Unique false

positiveOpinionsCount (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label positiveOpinionCount






SKOS Domain Concept


Unique false

polarityValue (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label polarityValue


SKOS Domain Concept

Valuerestriction Float

Unique false

opinionCount (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label opinionCount


SKOS Domain Concept


Unique false

neutralOpinionCount (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label neutralOpinionCount


SKOS Domain Concept


Unique false

contact | about




B PROFIT Finance Ontology

In this appendix a copy of the published version of the PROFIT finance ontology ispresented. The published version of the PROFIT finance ontology is available at http://profit.poolparty.biz/PROFIT-Finance.html.


http://profit.poolparty.biz/PROFIT-Finance.html

http://profit.poolparty.biz/PROFIT-Finance.html

5/17/2016 profit.poolparty.biz/PROFIT-Finance.html

http://profit.poolparty.biz/PROFIT-Finance.html 1/6

Custom Ontology PROFIT_Finance

Navigation Panel

Classes (19) FinancialObject

Relations (21)

⇒ Directed (3) relatedTo_2

⇒ Symmetric (0)

⇒ With Inverse (18) isOwnedBy

Attributes (4) hasExpectedValue

Scheme description

http://profit.poolparty.biz/PROFIT‐Finance (rdf:type ‐ http://schema.semantic‐web.at/ppt/CustomOntology)

dcterms:description

Classes

FinancialObject (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label FinancialObject

FinancialSystem (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label FinancialSystem

EconomicOrganization (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label EconomicOrganization

rdfs:subClassOf Organization

EconomicAgent (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label EconomicAgent

rdfs:subClassOf Agent

PoliticalOrganization (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label PoliticalOrganization

rdfs:subClassOf Organization

EconomicVariable (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label EconomicVariable

EconomicFacto (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label EconomicFactor

Region (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Region

rdfs:subClassOf Country

IndustrialOrganization (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Company

EconomicSector (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label EconomicSector

FinancialInstitution (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label FinancialInstitution

rdfs:subClassOf EconomicAgent

Agent (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)





rdfs:label Agent

Product (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Product


PhysicalLocation (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label physical location

rdfs:subClassOf Location

Location (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label location

Thing (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Thing

Country (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label country

rdfs:subClassOf GeopoliticalEntity

Organization (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label Organization


GeopoliticalEntity (rdf:type ‐ http://www.w3.org/2000/01/rdf‐schema#Class)

rdfs:label geopolitical entity

rdfs:subClassOf PhysicalLocation

Relations

Directed

relatedTo_2 (rdf:type ‐ http://schema.semantic‐web.at/ppt/DirectedProperty)

rdfs:label relatedTo

Domain [http://schema.org/Product]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/EconomicSector]

SKOS Range Concept

Unique false

isEmployedBy (rdf:type ‐ http://schema.semantic‐web.at/ppt/DirectedProperty)

rdfs:label isEmployedBy

Domain [http://profit.poolparty.biz/PROFIT‐Finance/EconomicAgent]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/IndustrialOrganization]

SKOS Range Concept

Unique false

hasInfluenceOn (rdf:type ‐ http://schema.semantic‐web.at/ppt/DirectedProperty)

rdfs:label hasInfluenceOn

Domain [http://profit.poolparty.biz/PROFIT‐Finance/EconomicFacto]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/EconomicVariable]

SKOS Range Concept

Unique false

With Inverse





isOwnedBy (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isOwnedBy

Domain [http://profit.poolparty.biz/PROFIT‐Finance/FinancialObject]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/EconomicAgent]

SKOS Range Concept

Unique false

owl:inverseof owns

isRegulatedBy (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isRegulatedBy

Domain [http://profit.poolparty.biz/PROFIT‐Finance/EconomicSector]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/FinancialSystem]

SKOS Range Concept

Unique false

owl:inverseof regulates

isRepresentedIn (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isRepresentedIn

Domain [http://profit.poolparty.biz/PROFIT‐Finance/IndustrialOrganization]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/FinancialSystem]

SKOS Range Concept

Unique false

owl:inverseof hasRepresentationOf

regulates (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label regulates

Domain [http://profit.poolparty.biz/PROFIT‐Finance/FinancialSystem]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof isRegulatedBy

hasProjectionIN (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label hasProjectionIn

Domain [http://schema.org/Organization]

SKOS Domain Concept

Range [http://www.omg.org/spec/EDMC‐FIBO/FND/Places/Countries/Country]

SKOS Range Concept

Unique false

owl:inverseof hasProjectionOf

isPartOf (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isPartOf

Domain [http://profit.poolparty.biz/PROFIT‐Finance/Region]

SKOS Domain Concept






SKOS Range Concept

Unique false

owl:inverseof hasPart

hasPart (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label hasPart

Domain [http://www.omg.org/spec/EDMC‐FIBO/FND/Places/Countries/Country]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/Region]

SKOS Range Concept

Unique false

owl:inverseof isPartOf

participatesIn (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label participatesIn

Domain[http://profit.poolparty.biz/PROFIT‐Finance/PoliticalOrganization, http://profit.poolparty.biz/PROFIT‐Finance/EconomicOrganization]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof isMemeberOF

isActiveAt (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isActiveIn


SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof hasMember

hasRelatedVariable (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label hasRelatedVariable


SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/EconomicVariable]

SKOS Range Concept

Unique false

owl:inverseof relatedTo

owns (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label owns

Domain [http://profit.poolparty.biz/PROFIT‐Finance/EconomicAgent]

SKOS Domain Concept

Range [http://profit.poolparty.biz/PROFIT‐Finance/FinancialObject]

SKOS Range Concept

Unique false

owl:inverseof isOwnedBy

produces (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)





rdfs:label produces


SKOS Domain Concept

Range [http://schema.org/Product]

SKOS Range Concept

Unique false

owl:inverseof isProducedBy

hasMember (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label hasMember

Domain [http://profit.poolparty.biz/PROFIT‐Finance/EconomicSector]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof isActiveAt

isMemeberOF (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isMemberOf


SKOS Domain Concept

Range[http://profit.poolparty.biz/PROFIT‐Finance/PoliticalOrganization, http://profit.poolparty.biz/PROFIT‐Finance/EconomicOrganization]

SKOS Range Concept

Unique false

owl:inverseof participatesIn

isProducedBy (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label isProducedBy

Domain [http://schema.org/Product]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof produces

hasProjectionOf (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label hasProjectionOf


SKOS Domain Concept

Range [http://schema.org/Organization]

SKOS Range Concept

Unique false

owl:inverseof hasProjectionIN

hasRepresentationOf (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label hasRepresentationOf

Domain [http://profit.poolparty.biz/PROFIT‐Finance/FinancialSystem]

SKOS Domain Concept


SKOS Range Concept





Unique false

owl:inverseof isRepresentedIn

relatedTo (rdf:type ‐ http://schema.semantic‐web.at/ppt/PropertyWithInverse)

rdfs:label relatedTo

Domain [http://profit.poolparty.biz/PROFIT‐Finance/EconomicVariable]

SKOS Domain Concept


SKOS Range Concept

Unique false

owl:inverseof hasRelatedVariable

Attributes

hasExpectedValue (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label hasExpectedValue

Domain [http://schema.org/Product, http://profit.poolparty.biz/PROFIT‐Finance/FinancialObject]

SKOS Domain Concept


Unique true

hasValue_2 (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label hasValue

Domain [http://profit.poolparty.biz/PROFIT‐Finance/FinancialObject, http://schema.org/Product]

SKOS Domain Concept


Unique true

hasMinimalPrice (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label hasMinimalPrice

Domain [http://schema.org/Product, http://profit.poolparty.biz/PROFIT‐Finance/FinancialObject]

SKOS Domain Concept


Unique true

hasMaximalPrice (rdf:type ‐ http://schema.semantic‐web.at/ppt/AttributeProperty)

rdfs:label hasMaximalPrice

Domain [http://profit.poolparty.biz/PROFIT‐Finance/FinancialObject, http://schema.org/Product]

SKOS Domain Concept


Unique true

contact | about



Documents

projectprofit.eu · 2016-07-13 · SKOS Simple Knowledge Organization System. 9, 10, 12, 18, 27, 28 XKOS An SKOS extension for representing statistical classi cations. 27 XL eXtension