The Graph Database: Jack of All Trades or Just Not SQL?

This special issue of IT Professional focuses on the graph database. The graph database, a relatively new phenomenon, is well suited to the burgeoning information era in which we are increasingly becoming immersed. Here, the guest editors briefly explain how a graph database works, its relation to the relational database management system (RDBMS), and its quantitative and qualitative pros and cons, including how graph databases can be harnessed in a hybrid environment. They also survey the excellent articles submitted for this special issue

Navigating Secure Banking IT Landscapes: Insights for Solution Architects and Technical Leaders

In "Navigating Secure Banking IT Landscapes: Insights for Solution Architects and Technical Leaders," the authors examine the evolving strategies and intricate problems associated with banking IT infrastructure security. The purpose of this research is to offer technical professionals and solution architects useful information about the critical need for better cybersecurity measures. Examining new technology, industry standards, and innovative approaches tailored to the banking IT landscape, the study integrates theoretical frameworks with practical implications. Abstract: The study aims to empower banking sector leaders to make informed decisions, enhance technological foundations, and proactively navigate the ever-changing terrain of safe banking IT and persistent cyber threats. Research concludes that proactive incident response planning, frequent audits and continual monitoring are steps that IT executives may do to guarantee the long-term financial viability of the banking business. The auditor performed a thorough job of detecting cybersecurity occurrences, differentiating between genuine and fraudulent payment gateways, and determining the false positive rate ratio by applying networking theory

Migrating microservices to graph database

Microservice architecture is a popular approach to structuring web backend services. Another emerging trend, after a period of hibernation, is utilizing modern graph database management systems for managing complex, richly connected data. The two approaches have rarely been used in tandem, as microservices emphasize modularization and decoupling of services, while graph data models favor data integration. In this study, literature on microservices and graph databases is reviewed and a synthesis between the two paradigms is presented. Based on the theoretical discussion, a software architecture combining the two elements is formulated and implemented using microservices serving content metadata at Yleisradio, the Finnish national broadcasting company. The architecture design follows the Design Science Research Process model. Finally, the renewed system is evaluated using quantitative and qualitative metrics. The performance of the system is measured using automated API queries and load tests. The new system was compared to an earlier version based on a PostgreSQL database. The tests gave slight indication that the renewed system performed better for complex queries, where a large number of relations were traversed, but worse in terms of throughput under heavy load. Based on the these findings, a number of performance-enhancing optimizations to the system are introduced. Observations and perpectives are also gathered in a project retrospective session. It is concluded that the resulting architecture holds promise for managing complex data rich in relations in a safe manner. In it, the different domains of the knowledge graph are decoupled into distinct named graphs managed by different microservices

Education and Entrepreneurship in Amman, Jordan

My thesis examines the potential economic impact of entrepreneurial education in Amman, Jordan. In order to investigate this topic, I also considered the economic impacts of increased entrepreneurism and access to education more broadly. I found that entrepreneurial education is just a small piece of a much larger ecosystem needed to support economic development. In fact, encouraging the creation of nascent firms is a somewhat dubious aim given the lack of scholarship assessing whether there is a shortage of entrepreneurial activity in the Jordanian economy. Institutional factors are a vastly more important component of efforts to spur growth

SUBSISTENCE URBAN MARKETS AND IN-COUNTRY REMITTANCES: A SOCIAL NETWORK ANALYSIS OF URBAN STREET VENDORS IN GHANA AND THE TRANSFER OF RESOURCES TO RURAL VILLAGES

This dissertation uses a mixed method approach to examine the determinants of internal remittances that are connected to the social networks of urban migrant street vendors. Urban street markets are a point of entry for many migrants moving from rural areas to cities in the Global South. The qualitative portion of the dissertation uses an ethnographic approach including participant observation, interviews and focus groups to examine the social networks of street vendors in a market in the municipality of Madina, Ghana. The quantitative analysis codes data from the ethnography in order to conduct a social network analysis using quadratic assignment procedure and logistic regression quadratic assignment procedure to analyze the relationship between attributes of street vendors and remittance behavior. Findings lead to several policy recommendations for the international community, as well as locally based non-governmental organizations, microfinance organizations, national and local governments providing funding or designing interventions affecting street markets or working with individual street vendors

Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams

The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data

Understanding and Characterizing Engineering Research Data for its Better Management

Engineering research data is diverse in character, spanning everything from material properties to questionnaire responses and interview transcripts. As a first step towards improving its management, a terminology is being developed to help describe the different types of engineering information and the different forms of development process and management activity to which it is subjected to during research. In particular the notions of ‘data purposing’, ‘data re-purposing’ and ‘supporting data re-use’ have been identified as data preparation activities which motivate research data management. This terminology has evolved in tandem with a scoping survey and audit of selected cases of engineering research data, and underlies a new modelling method for visualizing the associations between research data objects. These Research Activity Information Development (RAID) diagrams support both the initial researchers in managing the data and later re-users in understanding the data

Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems

The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home

Volume 61 - Issue 4 - January, 1950

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