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As with any other database solution, graph databases also need to be able to implement business rules related to a given application domain. At the moment, aside from integrity constraints, there is a limited number of mechanisms for business rules implementation in Graph Database Management Systems (GDBMSs). The underlying property graph data model does not include any formal notation on how to represent different constraints. Specifically, this paper discusses the problem of representing cardinality constraints in graph databases. We introduce the novel concept of k-vertex cardinality constraints, which enable us to specify the minimum and maximum number of edges between a vertex and a subgraph. We also propose an approach, which includes the representation of cardinality constraints through the property graph data model, and demonstrate its implementation through a series of stored procedures in Neo4j GDBMS. The proposed approach is then evaluated by performing experiments on synthetic and real datasets to test the influence of checking cardinality constraints on query execution times (QETs) when adding new edges. Additionally, a comparison is performed on synthetic datasets with varying outgoing vertex degrees in order to gain an insight into how increasing the vertex degree affects QETs. In general, the results obtained for each test scenario show that the implemented k-vertex cardinality constraints model does not significantly affect QETs. Also, the results indicate that the model is dependent on the order of the underlying k-vertex cardinality constraints and outgoing vertex degree in the dataset.
Martina Šestak; Marjan Heričko; Tatjana Welzer Družovec; Muhamed Turkanović. Applying k-vertex cardinality constraints on a Neo4j graph database. Future Generation Computer Systems 2020, 115, 459 -474.
AMA StyleMartina Šestak, Marjan Heričko, Tatjana Welzer Družovec, Muhamed Turkanović. Applying k-vertex cardinality constraints on a Neo4j graph database. Future Generation Computer Systems. 2020; 115 ():459-474.
Chicago/Turabian StyleMartina Šestak; Marjan Heričko; Tatjana Welzer Družovec; Muhamed Turkanović. 2020. "Applying k-vertex cardinality constraints on a Neo4j graph database." Future Generation Computer Systems 115, no. : 459-474.
SMEs represent a significant share of business companies in Europe. Their limitations might be overcome by using value chains, resulting in successful development and growth also within traditionally low-digitalized, natural fiber-based domains. Reaching a sustainable competitive advantage for natural fiber-based value chains is possible by boosting the digitalization of the included SMEs. The digitalization level can be improved by properly addressing the detected digitalization issues and challenges. This paper aims at proposing a novel comprehensive approach for assessing the digitalization level of natural fiber-based value chains and the respective SMEs. Using the proposed dimensions, indicators, and corresponding measurement instruments, the digitalization level of a particular SME, as well as of the entire value chain of SMEs can be assessed. The paper additionally depicts a practical demonstration for applying the proposed approach within two case studies. The proposed approach favors low-digitalized SMEs to enter and benefit from the digitalized value chains, as well as provides the benefits and facilitates the growth and sustainability of the existing natural fiber-based value chains.
Aida Kamišalić; Martina Šestak; Tina Beranič. Supporting the Sustainability of Natural Fiber-Based Value Chains of SMEs through Digitalization. Sustainability 2020, 12, 8121 .
AMA StyleAida Kamišalić, Martina Šestak, Tina Beranič. Supporting the Sustainability of Natural Fiber-Based Value Chains of SMEs through Digitalization. Sustainability. 2020; 12 (19):8121.
Chicago/Turabian StyleAida Kamišalić; Martina Šestak; Tina Beranič. 2020. "Supporting the Sustainability of Natural Fiber-Based Value Chains of SMEs through Digitalization." Sustainability 12, no. 19: 8121.