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

Abstract

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.

Hierarchical Strategies for Building Multiethnic Communities from the Perspective of Data Mining Analysis

“…The following situations can be considered. The cultural form will change with the development and change of the economy, and various places in a city will also produce different cultural forms [4].…”

“…My country has been a unified multi-ethnic country for a long time in human history, and it has created an excellent external environment for us [4]. In China's long-term feudal society, due to the fact that the exchanges and unions within China's various ethnic groups were at a relatively spontaneous stage, and due to the ethnic contradictions caused by the mutual oppression of ethnic groups, there was no ethnic community consciousness (national consciousness) among the various ethnic groups.…”

“…In China's long-term feudal society, due to the fact that the exchanges and unions within China's various ethnic groups were at a relatively spontaneous stage, and due to the ethnic contradictions caused by the mutual oppression of ethnic groups, there was no ethnic community consciousness (national consciousness) among the various ethnic groups. Under the external threat of genocide brought about by China's imminent national subjugation and imperialist invasion, all ethnic minorities in China are united unprecedentedly under the unified leadership of the CCP, and their national consciousness has awakened [5]. Table 1 shows the regional distribution of some ethnic minorities in my country.…”

Knowledge Graph based Representation to Extract Value from Open Government Data

“…Authors in [20] propose the construction of a knowledge graph to support the supervision and analysis of fiscal projects funded by the European Union. The proposed approach collects data from the Open Data API provided by the Greek Ministry of Economy and Finance.…”

Doc2KG

“…At the same time, other methods focused on how to publish a DMS as linked data and making it interoperable. Towards having high-quality data, Penteado et al (2021) Similarly, Bratsas et al (2021) defined an RDF vocabulary to convert data from a relational database into a knowledge graph. Then, they used this knowledge graph for facilitating ETL (Extract Transform Load) processes and trained a clustering model for identifying red flags in fiscal projects.…”