Graph databases and their application to the Italian Business Register for efficient search of relationships among companies

We studied and tested three of the major graph databases, and we compared them with a relational database. We worked on a dataset representing equity participations among companies, and we found out that the strong points of graph databases are: the purposely designed storage techniques; and their query languages. The main performance increments have been obtained when heavy graph situations are queried; for simpler situations and queries, a relational database performs equally wellope

Pacioli 16 : changing agricultural markets: consequences for FADN

The PACIOLI network explores the need for and feasibility of innovation in farm accounting and its consequences for data gathering for policy analysis in Farm Accountancy Data Networks (FADNs). PACIOLI 16 took place in Zagreb, Croatia in June 2008. The theme of the workshop was 'Changing agricultural markets: Consequences for FADN'

Virtual Knowledge Graphs: An Overview of Systems and Use Cases

In this paper, we present the virtual knowledge graph (VKG) paradigm for data integration and access, also known in the literature as Ontology-based Data Access. Instead of structuring the integration layer as a collection of relational tables, the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virtual and embed domain knowledge. We explain the main notions of this paradigm, its tooling ecosystem and significant use cases in a wide range of applications. Finally, we discuss future research directions

Production and production over-supply in construction: estimating unsold stock in Italy

PurposeThe aim of the article is to identify the limitations and critical issues in the way information in the real estate sector in Italy is currently managed, and propose the principles of a method that would provide information and comparison of the phenomenon of over-supply and non-rational land use. This study is based on a series of assumptions, the first of which is a definition of ???unsold???, deemed to mean ???the amount of new housing units neither occupied nor sold nor rented???. In effect, unsold stock can be considered as over-supply of construction. Design/methodology/approachThe article identifies the critical aspects in the determination of unsold real estate in Italy, starting from the available data and research already carried out; the results are often contradictory. The comparison with programming systems of building production adopted in other countries allows identification of the guidelines can be used to better understand and combat the phenomenon. FindingsThe assessment of the state of the art provides a clear picture of the shortcomings and potential of the tools used to date to meet the need of studying a complex phenomenon with many obscure points. Following the empirical analysis comes out a picture of inefficiencies due to the poor quality of 'information as well as the reluctance of data sharing and integration procedures by the institutional and market players. Research limitations/implicationsThe research produces solutions addressed to the Italian situation, but it identifies systems and methods used in other countries. Practical implicationsThe article suggests the collection systems and management information that can be used for a more accurate knowledge of unsold real estate. Originality/valueThe article seeks to provide the necessary answers to those who must understand the reasons of harmful effects for the market, such as overproduction; besides some models focused on three areas - the procedures, the organization, the market - are also proposed

Research Evaluation as a Policy Design Tool: Mapping Approaches across a Set of Case Studies

This paper provides an overview of research evaluation practices across countries. The main aim is to investigate whether research assessment is implemented and to see to what extent its results are used to revise policy strategies, identify new research priorities, allocate financial resources or enhance public understanding of R&D. The paper addresses a set of cases studies, four within Europe (UK, Finland, Italy, and Spain) and two outside (US and Japan). Each case study provides an outline of the strategies devised to improve the domestic science system; offers a map of the main actors of science policy and introduces the main performers of research assessment. A short overview of how evaluation is approached at European level is also given. The study shows that approaches vary significantly from case to case and that it is not always possible to identify a clear research evaluation framework. In some cases, new strategies have been devised to improve the research system and the process of renovation has affected the structure and the role of research assessment. Overall, official documents across countries emphasise that research evaluation is not a means in itself, and call on its use as a policy design tool. However, very few cases of “management by results” can be identified. The success of research evaluation practice is always tied to strong cultural support and it is where research assessment meets with reluctance and mistrust that it yields no fruit. The absence of an “evaluative culture” is the main obstacle to an efficient research evaluation system.Research Evaluation Systems, Management by Results, Evaluative Culture, Research Policy, Policy Planning

Discovering Relations by Entity Search in Lightweight Semantic Text Graphs

Entity search is becoming a popular alternative for full text search. Recently Google released its entity search based on confirmed, human-generated data such as Wikipedia. In spite of these developments, the task of entity discovery, search, or relation search in unstructured text remains a major challenge in the fields of information retrieval and information extraction. This paper tries to address that challenge, focusing specifically on entity relation discovery. This is achieved by processing unstructured text using simple information extraction methods, building lightweight semantic graphs and reusing them for entity relation discovery by applying algorithms from graph theory. An important part is also user interaction with semantic graphs, which can significantly improve information extraction results and entity relation search. Entity relations can be discovered by various text mining methods, but the advantage of the presented method lies in the similarity between the lightweight semantics extracted from a text and the information networks available as structured data. Both graph structures have similar properties and similar relation discovery algorithms can be applied. In addition, we can benefit from the integration of such graph data. We provide both a relevance and performance evaluations of the approach and showcase it in several use case applications

When the crowd becomes shareholder: an enquiry on Italian Equity Crowdfunding initiatives

This thesis aims at providing a valuable contribution in the field of Italian Equity Crowdfunding, which is currently experiencing its most successful period and consequently is being characterized by continuous updates in recorded volumes; symptomatically, the amount of equity subscribed in the first nine months of 2017 has already overcome the whole subscriptions obtained since the first deal has been hosted in 2014. The main research areas that have been covered consist in the platforms’ ecosystem and the whole Italian ECF campaigns launched until September 2017; for both of them descriptive and statistical analyses have been conducted, aiming at representing in the most effective way the current status of pla