The code lists case: Identifying and linking the key parts of fiscal datasets

Filippidis, Panagiotis-Marios; Karampatakis, Sotirios; Koupidis, Kleanthis; Ioannidis, Lazaros; Bratsas, Charalampos

doi:10.1109/smap.2016.7753404

Cited by 7 publications

(4 citation statements)

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“…The transformation of the NSRF data to knowledge graph, is done by using the UnifiedViews 14 ETL tool. The main advantage of this tool is that it can extract data straight from relational databases and then transform it to RDF triples [27][28][29]. After the transformation process, the RDF files were uploaded to an OpenLink Virtuoso Server 15 .…”

Section: Nsrf Knowledge Graph and Data Retrievalmentioning

confidence: 99%

“…The object properties vfp:currentStatus, nsrf-gr:operational, nsrf-gr:location, nsrf-gr:body, nsrf-gr:thematic weren't assigned to literal terms, but instead we chose to use code lists. The code lists were semantically represented using SKOS 16 , since it's a widespread vocabulary that provides a standard way to organize knowledge using RDF and allows the hierarchical ordering of terms [28].…”

Section: Nsrf Knowledge Graph and Data Retrievalmentioning

confidence: 99%

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The Use of National Strategic Reference Framework Data in Knowledge Graphs and Data Mining to Identify Red Flags

Bratsas

Chondrokostas

Koupidis

et al. 2021

Data

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Red Flags in fiscal projects are warning signs that may indicate underlying problems with their implementation. In this paper, we present how National Strategic Reference Framework Open Data can be used to take full advantage of semantic web technologies and data mining techniques to build a knowledge-based system that identifies Red Flags. We collected the data from the Open Data API provided by the Greek Ministry of Economy and Finance. Data modeling consist of two ontologies; the Vocabulary of Fiscal Projects, describing the fiscal projects and the National Strategic Reference Framework Greece Vocabulary, illustrating the Greek National Strategic Reference Framework data. We transformed the data into RDF triples and uploaded them onto an OpenLink Virtuoso Server, so that we could retrieve them via SPARQL queries. Performance indicators were defined to assess the state of the project and Density-Based Spatial Clustering of Applications with Noise, (DBSCAN) was used to identify Red Flags. User’s demands is that rejected projects should raise Red Flags, to avoid project failure and assist the auditor to organize the monitoring process efficiently, by avoiding to examine most of the non-problematic projects. We performed a use case scenario in which an auditor has to examine NSRF projects, approximately 12 months before the end of the programming period. The system retrieved the fiscal information, calculated the performance indicators and identified the Red Flags. The last update of the projects status after the end of the programming period was retrieved and extracted the number of rejected projects, to test whether the user requirements are satisfied. Rejected projects consist of 3.8% of the total projects. The results of the use case scenario show that RedFlags platform is more likely to identify project failures and not raise Red Flags on not rejected projects. Therefore, the RedFlags platform using open data, assists the auditor to organize the monitoring process better.

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Section: Nsrf Knowledge Graph and Data Retrievalmentioning

confidence: 99%

Section: Nsrf Knowledge Graph and Data Retrievalmentioning

confidence: 99%

The Use of National Strategic Reference Framework Data in Knowledge Graphs and Data Mining to Identify Red Flags

Bratsas

Chondrokostas

Koupidis

et al. 2021

Data

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“…They are prescribed controlled vocabularies, that serve for the coding of concepts that can be expressed in many ways. In the scope of OpenBudgets.eu project, several EU or national level codelists were described using the SKOS Vocabulary, as RDF Data Cube dimension codelists as described in [2] and then linked to each other where possible. In some cases, links between codelists was provided by authoritative organizations such as the Eurostat's RAMON mappings (http://ec.europa.eu/eurostat/ramon/relations/index.cfm?…”

Section: Default Configuration Parameters Choice and Validationmentioning

confidence: 99%

“…The potential complexity and versatility of vocabularies could easily lead to incorrect links. At the same time, the appearance of many synonyms of a particular vocabulary term in another vocabulary causes a common problem for creating accurate links between them [2]. An automatic approach of linking large vocabularies leads to only partial alignments amongst them, and along with this, configuration of similarity algorithms may produce no links for a number of entities, or include false positive links [3].…”

Section: Introductionmentioning

confidence: 99%

Alignment: A Hybrid, Interactive and Collaborative Ontology and Entity Matching Service

et al. 2018

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Ontology matching is an essential problem in the world of Semantic Web and other distributed, open world applications. Heterogeneity occurs as a result of diversity in tools, knowledge, habits, language, interests and usually the level of detail. Automated applications have been developed, implementing diverse aligning techniques and similarity measures, with outstanding performance. However, there are use cases where automated linking fails and there must be involvement of the human factor in order to create, or not create, a link. In this paper we present Alignment, a collaborative, system aided, interactive ontology matching platform. Alignment offers a user-friendly environment for matching two ontologies with the aid of configurable similarity algorithms.

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Alignment: A Collaborative, System Aided, Interactive Ontology Matching Platform

Karampatakis

Bratsas

Zamazal

et al. 2017

Communications in Computer and Information Science

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The code lists case: Identifying and linking the key parts of fiscal datasets

Cited by 7 publications

References 1 publication

The Use of National Strategic Reference Framework Data in Knowledge Graphs and Data Mining to Identify Red Flags

The Use of National Strategic Reference Framework Data in Knowledge Graphs and Data Mining to Identify Red Flags

Alignment: A Hybrid, Interactive and Collaborative Ontology and Entity Matching Service

Alignment: A Collaborative, System Aided, Interactive Ontology Matching Platform

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