Cost-based Optimization of Multistore Query Plans

2023 | Information Systems Frontiers | Citations: 0

Authors: Forresi, Chiara; Francia, Matteo; Gallinucci, Enrico; Golfarelli, Matteo

Abstract: Multistores are data management systems that enable query processing across diff ... Expand

Abstract: Multistores are data management systems that enable query processing across different and heterogeneous databases; besides the distribution of data, complexity factors like schema heterogeneity and data replication must be resolved through integration and data fusion activities. Our multistore solution relies on a dataspace to provide the user with an integrated view of the available data and enables the formulation and execution of GPSJ queries. In this paper, we propose a technique to optimize the execution of GPSJ queries by formulating and evaluating different execution plans on the multistore. In particular, we outline different strategies to carry out joins and data fusion by relying on different schema representations; then, a self-learning black-box cost model is used to estimate execution times and select the most efficient plan. The experiments assess the effectiveness of the cost model in choosing the best execution plan for the given queries and exploit multiple multistore benchmarks to investigate the factors that influence the performance of different plans. Collapse

Topics: database system MongoDB PostgreSQL document database relational database

Methods: computational algorithm experiment case study regression analysis method longitudinal research

CURIE: Towards an Ontology and Enterprise Architecture of a CRM Conceptual Model

2022 | Business & Information Systems Engineering | Citations: 0

Authors: Fernández-Cejas, Miguel; Pérez-González, Carlos J.; Roda-García, José L.; Colebrook, Marcos

Abstract: Companies face the challenge of managing customer relationships (CRM) in a conte ... Expand

Abstract: Companies face the challenge of managing customer relationships (CRM) in a context marked by a drastic digital transformation and unbridled evolution of consumer behavior, exacerbated by the COVID-19 pandemic. The customer is more demanding, has access to the global market and interacts with companies through multiple digital channels, such as email, social networks, mobile apps or instant messaging. In this situation, the success of a CRM implementation highly depends on information technology and the applications used. To harmonize this new business context with the development of information systems (IS), a suitable CRM ontology and enterprise architecture (EA) is needed. While an ontology-based conceptual model provides a unifying framework, aids sharing and reusing knowledge, and facilitates communication within a domain, an EA-based model unequivocally describes, analyzes, and visualizes how an organization should operate from the perspective of business, application, and technology. The purpose of the paper is the proposal of CURIE-O, a CRM OntoUML UFO-based ontology, together with CURIE-EA, a CRM ArchiMate-based EA to serve business managers and IS specialists an updated unifying framework of reference in the CRM domain as well as a highly efficient tool to support application development and maintenance in this changing and increasingly digital context. Modeling has proven to be an essential element to achieve high-performance information systems. In order to apply the ontology and the EA proposed here, the authors developed a CRM task management application prototype that was implemented as a case study in a consulting company. The methodology followed was design science research (DSR), in order to design and validate the artifacts. Within the DSR framework, other complementary research methods have been used, in particular literature research, interviews and focus groups carried out with several hotel chains in Tenerife (Canary Islands). The main existing CRM models in the scientific literature have also been analyzed together with the leading CRM market solutions. Collapse

Topics: knowledge representation microservice architecture Kubernetes PostgreSQL database system

Methods: ontological modelling design artifact conceptual modelling design science upper ontology

A Time-Sensitive IoT Data Analysis Framework

2021 | HICSS | Citations: 0

Authors: Korala, Harindu; Georgakopoulos, Dimitrios; Jayaraman, Prem Prakash; Yavari, Ali

Abstract: This paper proposes a Time-Sensitive IoT Data Analysis (TIDA) framework that mee ... Expand

Abstract: This paper proposes a Time-Sensitive IoT Data Analysis (TIDA) framework that meets the time-bound requirements of time-sensitive IoT applications. The proposed framework includes a novel task sizing and dynamic distribution technique that performs the following: 1) measures the computing and network resources required by the data analysis tasks of a timesensitive IoT application when executed on available IoT devices, edge computers and cloud, and 2) distributes the data analysis tasks in a way that it meets the time-bound requirement of the IoT application. The TIDA framework includes a TIDA platform that implements the above techniques using Microsoft’s Orleans framework. The paper also presents an experimental evaluation that validates the TIDA framework’s ability to meet the time-bound requirements of IoT applications in the smart cities domain. Evaluation results show that TIDA outperforms traditional cloud-based IoT data processing approaches in meeting IoT application time-bounds and reduces the total IoT data analysis execution time by 46.96%. Collapse

Topics: internet of things mobile system cloud computing smart city PostgreSQL

Methods: computational algorithm experiment design artifact optimization model OpenCV

Spatial Location and Air Transport Connections: The Case of Minnesota’s Medical Device Industry Cluster

2021 | HICSS | Citations: 0

Authors: Munnich, Lee; Fried, Travis; Cho, Joanne; Horan, Thomas

Abstract: Minnesota’s medical device industry cluster is not only one of the biggest drivi ... Expand

Abstract: Minnesota’s medical device industry cluster is not only one of the biggest driving economic forces in the state, but also a global leader in the development and distribution of medical devices. The study assessed the medical device industry’s spatial development and air transport implications, both in terms of industry cluster location and flow of products. The spatial analysis showed that most medical device companies are located within the seven-county Twin-Cities region, but that industries linked to the medical device industry cluster are much more dispersed throughout the state. Regarding products created, the supply chain of medical devices is highly dependent on Minneapolis-St Paul Airport (MSP), which plays a key role in their delivery of medical devices. Air Cargo analysis reveals the high value of medical devices. exports to various locations and raises issues about the future role of air cargo through MSP to the economic prosperity of the industry cluster. Collapse

Topics: supply chain management database system PostgreSQL

Methods: spatial analysis

Theories: theory of economic growth theory of economic development

Approaches to Enforce Privacy in Databases: Classical to Information Flow-Based Models

2021 | Information Systems Frontiers | Citations: 0

Authors: Shyamasundar, R.K.; Chaudhary, Pratiksha; Jaiswal, Arushi; Kuiri, Aniket

Abstract: Ever since databases became an ubiquitous part of enterprises or businesses, sec ... Expand

Abstract: Ever since databases became an ubiquitous part of enterprises or businesses, security and privacy became a requirement. Traditionally, privacy was realized through various methods of database access control and relied much on the use of statically defined views, which are essentially logical constructs imposed over database tables that can alter or restrict the data that can be viewed by an user. Privacy is about the responsible maintenance of private information. This responsibility is hard to define, which is why laws are necessary. With a vast accumulation of personal data in databases, there has been a heightened awareness and concern about the storage and use of private information leading to privacy-related guidelines, regulations and legislations, Compliance with these regulations has become one of the major concerns for organizations and companies. Traditionally, privacy in databases (DBs) have been addressed through access control techniques including multi-level security (MLS) based on mandatory access control (MAC), and restricted views to the users. As view definitions to comply with regulations became quite complex for accommodating all the restrictions in one view, explicit constructs for specifying privacy policies were introduced for complying with medical regulations like HIPAA (Health Insurance Portability and Accountability Act) from USA, in relational database systems. These enabled fine grained access control (FGAC) capable of enforcing disclosure control enunciated databases. Application of information flow control that is needed for multi-level security (MLS) databases to preserve privacy among multiple users but have their challenges like new abstractions for managing information flow in a relational database system, handling transactions and integrity constraints without introducing covert channels etc. As the DBs need to work alongside information flow controlled programming languages and operating systems for tracking flows, there is a need to enforce the security policy not only on the DBMS but also on the application platform. Due to the underlying requirement of decentralization, it calls for declassification/endorsement and santization requirements on the DB. In this paper, we shall first review some of the major privacy enhancing techniques used traditionally for DBs including MLS DBs, and then explore application of decentralized information flow control models for realizing information flow secure DBs in a robust manner. Towards the end, we shall also touch upon some of the roles of anonymization and psuedonymization including inference control and differential privacy in realizing privacy in practice. Collapse

Topics: privacy PostgreSQL database system differential privacy authorization

Methods: design science case study design artifact database modeling data modeling

Mining Social Networks to Detect Traffic Incidents

2021 | Information Systems Frontiers | Citations: 1

Authors: Vallejos, Sebastián; Alonso, Diego G.; Caimmi, Brian; Berdun, Luis; Armentano, Marcelo G.; Soria, Álvaro

Abstract: Social networks are usually used by citizens to report or complain about traffic ... Expand

Abstract: Social networks are usually used by citizens to report or complain about traffic incidents that affect their daily mobility. Automatically finding traffic-related reports and extracting useful information from them is not a trivial task, due to the informal language used in social networks, to the lack of geographic metadata, and to the large amount of non traffic-related publications. In this article, we address this problem by combining Machine Learning and Natural Language Processing techniques. Our approach (a) filters publications that report traffic incidents in social networks, (b) extracts geographic information from the textual content of the publications, and (c) provides a broadcasting service that clusters all the reports of the same incident. We compared the performance of our approach with state of the art approaches and with a popular traffic-specific social network, obtaining promising results. Collapse

Topics: Twitter social network application programming interface global navigation satellite system Wikipedia

Methods: experiment machine learning support vector machine natural language processing decision tree classification

Implementation of Aspect-oriented Business Process Models with Web Services

2020 | Business & Information Systems Engineering | Citations: 0

Authors: Jose, Hercules Sant Ana da Silva; Cappelli, Claudia; Santoro, Flavia Maria; Azevedo, Leonardo Guerreiro

Abstract: In software development, crosscutting concerns, such as security, audit, access ... Expand

Abstract: In software development, crosscutting concerns, such as security, audit, access control, authentication, logging, persistence, transaction, error handling etc. can be modularized using the aspect-oriented paradigm. In business process modeling, aspects have been used to reduce visualization complexity, increase reuse and improve model maintainability. There are techniques which address aspects in modeling and implementation phases of business process; however, these techniques adopt different semantic representations, hindering the integration of these phases into the BPM lifecycle. This work proposes an architecture for service discovery capable of selecting web services that implement crosscutting concerns and meet the goals established in the aspect modeling phase, executing them accordingly with a prioritization. A proof of concept to analyze the proposed architecture and generated artifacts was performed. Afterwards, the proposal was evaluated by means of an experiment. The results suggest that the definition of an operational goal enables the business specialists to concentrate on the modeling of the aspect without necessarily concerning its implementation, since a proper option for implementation is discovered during the execution of the process. Collapse

Topics: web service knowledge representation business process management virtualization technology source code

Methods: experiment design artifact ontological modelling simulation business process modeling

Efficient querying of multidimensional RDF data with aggregates: Comparing NoSQL, RDF and relational data stores

2020 | International Journal of Information Management | Citations: 0

Authors: Ravat, Franck; Song, Jiefu; Teste, Olivier; Trojahn, Cassia

Abstract: This paper proposes an approach to tackle the problem of querying large volume o ... Expand

Abstract: This paper proposes an approach to tackle the problem of querying large volume of statistical RDF data. Our approach relies on pre-aggregation strategies to better manage the analysis of this kind of data. Specifically, we define a conceptual model to represent original RDF data with aggregates in a multidimensional structure. A set of translations rules for converting a well-known multidimensional RDF modelling vocabulary into the proposed conceptual model is then proposed. We implement the conceptual model in six different data stores: two RDF triple stores (Jena TDB and Virtuoso), one graph-oriented NoSQL database (Neo4j), one column-oriented data store (Cassandra), and two relational databases (MySQL and PostGreSQL). We compare the querying performance, with and without aggregates, in these data stores. Experimental results, on real-world datasets containing 81.92 million triplets, show that pre-aggregation allows for reducing query runtime in all data stores. Neo4j NoSQL and relational databases with aggregates outperform triple stores speeding up to 99% query runtime. Collapse

Topics: Neo4j Cassandra relational database nosql database MySQL

Methods: experiment conceptual modelling computational algorithm multidimensional modeling optimization model

Design principles for a hybrid intelligence decision support system for business model validation

2019 | Electronic Markets | Citations: 30

Authors: Dellermann, Dominik; Lipusch, Nikolaus; Ebel, Philipp; Leimeister, Jan Marco

Abstract: One of the most critical tasks for startups is to validate their business model. ... Expand

Abstract: One of the most critical tasks for startups is to validate their business model. Therefore, entrepreneurs try to collect information such as feedback from other actors to assess the validity of their assumptions and make decisions. However, previous work on decisional guidance for business model validation provides no solution for the highly uncertain and complex context of early-stage startups. The purpose of this paper is, thus, to develop design principles for a Hybrid Intelligence decision support system (HI-DSS) that combines the complementary capabilities of human and machine intelligence. We follow a design science research approach to design a prototype artifact and a set of design principles. Our study provides prescriptive knowledge for HI-DSS and contributes to previous work on decision support for business models, the applications of complementary strengths of humans and machines for making decisions, and support systems for extremely uncertain decision-making problems. Collapse

Topics: business model decision support system decision support decision making crowdsourcing

Methods: design principle design artifact focus group qualitative interview design requirement

Theories: theory of bounded rationality

A Network View of Social Media Platform History: Social Structure, Dynamics and Content on YouTube

2019 | HICSS | Citations: 2

Authors: Paolillo, John C; Ghule, Sharad; Harper, Brian P

Abstract: Social media sites are prone to change from many internal and external causes, y ... Expand

Abstract: Social media sites are prone to change from many internal and external causes, yet it is difficult to directly explore their histories in terms of the content itself. Search and browsing features are biased toward new and paid content, archives are difficult to navigate systematically, and their scale makes any observations challenging to contextualize. Here, we present results of an ongoing study of YouTube’s history (currently with more than 76 million videos) using a combination of iterative browsing, network crawling and clustering within and across time periods. Through this method, we are able to identify historical patterns in YouTube's content related to internal and external events. Our approach thus illustrates an adaptation of network analysis for understanding the content histories of social media platforms. Collapse

Topics: YouTube database system social media PostgreSQL Google+

Methods: cluster analysis network analysis