Software Tools for Indigenous Knowledge Management

Indigenous communities are beginning to realize the potential benefits which digital technologies can offer with regard to the documentation and preservation of their histories and cultures. However they are also coming to understand the opportunities for misuse and misappropriation of their knowledge which may accompany digitization. In this paper we describe a set of open source software tools which have been designed to enable indigenous communities to protect unique cultural knowledge and materials which have been preserved through digitization. The software tools described here enable authorized members of communities to: define and control the rights, accessibility and reuse of their digital resources; uphold traditional laws pertaining to secret/sacred knowledge or objects; prevent the misuse of indigenous heritage in culturally inappropriate or insensitive ways; ensure proper attribution to the traditional owners; and enable indigenous communities to describe their resources in their own words. Hopefully the deployment of such tools will contribute to the self-determination and empowerment of indigenous communities through the revitalization of their cultures and knowledge which have been eroded by colonization, western laws, western cultures and globalization

Implementing chain of custody requirements in database audit records for forensic purposes

During forensic database investigations, audit records become a crucial evidential element; particularly, when certain events can be attributed to insider activity. However, traditional reactive forensic methods may not be suitable, urging the adoption of proactive approaches that can be used to ensure accountability through audit records whilst satisfying Chain of Custody (CoC) requirements for forensic purposes. In this paper, role segregation, evidence provenance, event timeliness and causality are considered as CoC requirements in order to implement a forensically ready architecture for the proactive generation, collection and preservation of database audit records that can be used as digital evidence for the investigation of insider activity. Our proposal implements triggers and stored procedures as forensic routines in order to build a vector-clockbased timeline for explaining causality in transactional events recorded in audit tables. We expect to encourage further work in the field of proactive digital forensics and forensic readiness; in particular, for justifying admissibility of audit records under CoC restrictions

Performance Evaluation of Structured and Unstructured Data in PIG/HADOOP and MONGO-DB Environments

The exponential development of data initially exhibited difficulties for prominent organizations, for example, Google, Yahoo, Amazon, Microsoft, Facebook, Twitter and so forth. The size of the information that needs to be handled by cloud applications is developing significantly quicker than storage capacity. This development requires new systems for managing and breaking down data. The term Big Data is used to address large volumes of unstructured (or semi-structured) and structured data that gets created from different applications, messages, weblogs, and online networking. Big Data is data whose size, variety and uncertainty require new supplementary models, procedures, algorithms, and research to manage and extract value and concealed learning from it. To process more information efficiently and skillfully, for analysis parallelism is utilized. To deal with the unstructured and semi-structured information NoSQL database has been presented. Hadoop better serves the Big Data analysis requirements. It is intended to scale up starting from a single server to a large cluster of machines, which has a high level of adaptation to internal failure. Many business and research institutes such as Facebook, Yahoo, Google, and so on had an expanding need to import, store, and analyze dynamic semi-structured data and its metadata. Also, significant development of semi-structured data inside expansive web-based organizations has prompted the formation of NoSQL data collections for flexible sorting and MapReduce for adaptable parallel analysis. They assessed, used and altered Hadoop, the most popular open source execution of MapReduce, for tending to the necessities of various valid analytics problems. These institutes are also utilizing MongoDB, and a report situated NoSQL store. In any case, there is a limited comprehension of the execution trade-offs of using these two innovations. This paper assesses the execution, versatility, and adaptation to an internal failure of utilizing MongoDB and Hadoop, towards the objective of recognizing the correct programming condition for logical data analytics and research. Lately, an expanding number of organizations have developed diverse, distinctive kinds of non-relational databases (such as MongoDB, Cassandra, Hypertable, HBase/ Hadoop, CouchDB and so on), generally referred to as NoSQL databases. The enormous amount of information generated requires an effective system to analyze the data in various scenarios, under various breaking points. In this paper, the objective is to find the break-even point of both Hadoop/Pig and MongoDB and develop a robust environment for data analytics

ETDB-Caltech: a blockchain-based distributed public database for electron tomography

Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu, for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets

On-premise containerized, light-weight software solutions for Biomedicine

Bioinformatics software systems are critical tools for analysing large-scale biological data, but their design and implementation can be challenging due to the need for reliability, scalability, and performance. This thesis investigates the impact of several software approaches on the design and implementation of bioinformatics software systems. These approaches include software patterns, microservices, distributed computing, containerisation and container orchestration. The research focuses on understanding how these techniques affect bioinformatics software systems’ reliability, scalability, performance, and efficiency. Furthermore, this research highlights the challenges and considerations involved in their implementation. This study also examines potential solutions for implementing container orchestration in bioinformatics research teams with limited resources and the challenges of using container orchestration. Additionally, the thesis considers microservices and distributed computing and how these can be optimised in the design and implementation process to enhance the productivity and performance of bioinformatics software systems. The research was conducted using a combination of software development, experimentation, and evaluation. The results show that implementing software patterns can significantly improve the code accessibility and structure of bioinformatics software systems. Specifically, microservices and containerisation also enhanced system reliability, scalability, and performance. Additionally, the study indicates that adopting advanced software engineering practices, such as model-driven design and container orchestration, can facilitate efficient and productive deployment and management of bioinformatics software systems, even for researchers with limited resources. Overall, we develop a software system integrating all our findings. Our proposed system demonstrated the ability to address challenges in bioinformatics. The thesis makes several key contributions in addressing the research questions surrounding the design, implementation, and optimisation of bioinformatics software systems using software patterns, microservices, containerisation, and advanced software engineering principles and practices. Our findings suggest that incorporating these technologies can significantly improve bioinformatics software systems’ reliability, scalability, performance, efficiency, and productivity.Bioinformatische Software-Systeme stellen bedeutende Werkzeuge für die Analyse umfangreicher biologischer Daten dar. Ihre Entwicklung und Implementierung kann jedoch aufgrund der erforderlichen Zuverlässigkeit, Skalierbarkeit und Leistungsfähigkeit eine Herausforderung darstellen. Das Ziel dieser Arbeit ist es, die Auswirkungen von Software-Mustern, Microservices, verteilten Systemen, Containerisierung und Container-Orchestrierung auf die Architektur und Implementierung von bioinformatischen Software-Systemen zu untersuchen. Die Forschung konzentriert sich darauf, zu verstehen, wie sich diese Techniken auf die Zuverlässigkeit, Skalierbarkeit, Leistungsfähigkeit und Effizienz von bioinformatischen Software-Systemen auswirken und welche Herausforderungen mit ihrer Konzeptualisierungen und Implementierung verbunden sind. Diese Arbeit untersucht auch potenzielle Lösungen zur Implementierung von Container-Orchestrierung in bioinformatischen Forschungsteams mit begrenzten Ressourcen und die Einschränkungen bei deren Verwendung in diesem Kontext. Des Weiteren werden die Schlüsselfaktoren, die den Erfolg von bioinformatischen Software-Systemen mit Containerisierung, Microservices und verteiltem Computing beeinflussen, untersucht und wie diese im Design- und Implementierungsprozess optimiert werden können, um die Produktivität und Leistung bioinformatischer Software-Systeme zu steigern. Die vorliegende Arbeit wurde mittels einer Kombination aus Software-Entwicklung, Experimenten und Evaluation durchgeführt. Die erzielten Ergebnisse zeigen, dass die Implementierung von Software-Mustern, die Zuverlässigkeit und Skalierbarkeit von bioinformatischen Software-Systemen erheblich verbessern kann. Der Einsatz von Microservices und Containerisierung trug ebenfalls zur Steigerung der Zuverlässigkeit, Skalierbarkeit und Leistungsfähigkeit des Systems bei. Darüber hinaus legt die Arbeit dar, dass die Anwendung von SoftwareEngineering-Praktiken, wie modellgesteuertem Design und Container-Orchestrierung, die effiziente und produktive Bereitstellung und Verwaltung von bioinformatischen Software-Systemen erleichtern kann. Zudem löst die Implementierung dieses SoftwareSystems, Herausforderungen für Forschungsgruppen mit begrenzten Ressourcen. Insgesamt hat das System gezeigt, dass es in der Lage ist, Herausforderungen im Bereich der Bioinformatik zu bewältigen und stellt somit ein wertvolles Werkzeug für Forscher in diesem Bereich dar. Die vorliegende Arbeit leistet mehrere wichtige Beiträge zur Beantwortung von Forschungsfragen im Zusammenhang mit dem Entwurf, der Implementierung und der Optimierung von Software-Systemen für die Bioinformatik unter Verwendung von Prinzipien und Praktiken der Softwaretechnik. Unsere Ergebnisse deuten darauf hin, dass die Einbindung dieser Technologien die Zuverlässigkeit, Skalierbarkeit, Leistungsfähigkeit, Effizienz und Produktivität bioinformatischer Software-Systeme erheblich verbessern kann

Fraud and Performance Monitoring of Credit Card Tokenization Using Business Intelligence

This project major objective is to gather all the necessary data to analyze and deliver a best analytical reporting platform. This product developed for the analysts is expected to extensively use for insights on the token provisioning and its varied utilization with the banks and merchants. Also to monitor fraudulent occurring patterns and initiate necessary steps to avoid facing any adversities in the future. The reports are generated using the principles supporting descriptive analytics. Using many different KPIs, metrics and scorecards, etc., to support the analysis has given an advantage for better yield. These analytical dashboard has given a deep dive insight for the analysts. This project has been used by many analysts to come to an agreement on different patterns noticed by each individual. Also for the Senior Executives to get a profound understanding of how the widely different tokenization are used and its different attribute wise segregation

Inclusive Educational Review of Software Architectural Styles and Patterns for the Students of the College of Information and Computing Sciences of Cagayan State University

A good architectural design has a high contribution to the success of a system. In addition, this architectural design is useful for the Information Technology (IT) students as their basis of their software development of their capstone project. The utilization of inappropriate architecture can lead to disastrous consequences for IT student researchers. A detailed understanding of software architecture styles is very useful to analyze distributed and complex systems which is the trend of capstone projects. This paper explores the quality attributes of three architecture styles namely shared-nothing, broker, and representational state transfer, which are perceived as beneficial to distributed system architecture that serve as guide to student researchers. This is to provide a picture of the said three key software architecture styles which could be helpful not only for student researchers but also for the software developers by adding references to minimize the uncertainty while selecting the appropriate architectural style for their specific needs. An architectural style must be chosen correctly to obtain all its benefits in the system. In this paper, the three architectural styles are compared on the foundation of various quality attributes derived from ISO 9126-1 standard such as functionality, reliability, usability, efficiency, maintainability, and portability. The results of the study are useful to guide the student researchers in their capstone project and to reduce the number of unsuccessful attempts of software development component of their capstone project

The BI architecture of a luxury fashion company

Internship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business IntelligenceIn this paper will be explained what Business Intelligence means, what are the practices linked to it and the advantages obtained, translated into insights requested by the end users and the ones they didn’t know it was possible to have access. The second chapter will describe the basic concepts related to the BI field, like an introduction of what is a Database, which is the basis for every business intelligence system. Ending with a brief presentation of BI platform, used for the creation of reports and dashboards, which make data a real information not only for the analysts but especially for end-users. While the third chapter exposes the organization and the consultant company in which the BI task was developed and following in the fourth chapter there will be an overview of the technologies and tools used. Then a chapter will describe the AGILE methodology, that is the procedure adopted by the organization in order to manage and monitor the entire process of development of the different tasks requested by the end-users. Finally, the sixth chapter will explain the task subject of this thesis, the tables and the integration developed during the internship held at the organization