Analysis of functional requirements to ensure authenticity and integrity of archiving Norwegian electronic public administration records

Authenticity and integrity are crucial elements of trust in physical or electronic document archiving. This thesis analyzed the functional requirements of authenticity and integrity and how to ensure them in the context of the Norwegian public administration records. NOARK is the Norwegian recordkeeping and archiving standard and Fedora Commons an open source archival repository software are used as a record management system and archival system respectively to establish the case of the study. For the purpose of meeting the objectives of the study, standards, literatures and previous studies on the area of trusted recordkeeping and archiving are analyzed; on the basis of which an archival framework addressing authenticity, integrity and trusted chain custody is proposed and prototype is developed as a proof of concept. The validation is carried out by purposely compromising the authenticity and integrity of the electronic records in the process of transferring from NOARK to Fedora Commons and detecting the failure in either of authenticity or integrity or both before and after archiving the records. The study found out that records archived using our framework have met the authenticity and integrity requirements of archival objects. Records archived using the proposed archival framework are found to improve the evidential value of records for court cases.Joint Master Degree in Digital Library Learning (DILL

Proveniência de dados em workflows de bioinformática

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2012.Avanços tecnológicos, tanto em equipamentos quanto em algoritmos, têm tornado a execução de experimentos científicos cada vez mais rápida e eficiente. Isso permite que os cientistas executem mais experimentos e possam compará-los entre si, o que traz maior acurácia às análises. Porém, a quantidade de dados que devem ser tratados aumenta a cada novo experimento executado, o que dificulta a identificação da origem dos dados e como os mesmos foram transformados em cada experimento. Assim, tem-se a necessidade de novas ferramentas que tornem possível preservar, não só as conclusões de um experimento científico, mas também a origem dos dados utilizados e as condições e parâmetros com os quais foram executados. Estudos recentes mostram que a utilização de modelos de proveniência de dados facilita o gerenciamento dos dados tanto em ambiente científico quanto naqueles disponibilizados pela internet. Uma importante área para o uso de proveniência de dados é o da bioinformática, principalmente em projetos genoma e transcritoma de alto desempenho, visto que seus experimentos geram grande volume de dados e seus processos podem ser executados diversas vezes com diferentes ferramentas, dados e parâmetros. Neste trabalho propomos a utilização de uma estrutura de proveniência de dados baseada no modelo PROV-DM para experimentos em projetos de bioinformática a fim de permitir que os cientistas possam trabalhar com seus experimentos em detalhes e, quando necessário, possam consultá-los e reexecutá-los de forma mais planejada e controlada. _____________________________________________________________________________________________________________________________ ABSTRACTTechnological Advances, both in equipment and algorithms, have made the execution of scientific experiments increasingly faster and more e efficient. This allows scientists to execute more experiments and compare them, generating greater accuracy in analyses. However, the great quantity of data to be treated increases with each new experiment performed, which makes it difficult to identify the origin of data and how they were transformed in each experiment. Thus, there is a pressing need for new tools that make possible the preservation of, not only conclusions of scientific experiments, but also the origin of data used and the conditions and parameters with which each were performed. Recent studies show that the use of data provenance models facilitates the management of data, both in the scientific environment and those available on the internet. An important area for the use of data provenance is in bioinformatics, mainly in genome and high performance transcriptome projects, since these experiments generate a large volume of data and their process can be executed many times with different tools, data and parameters. In this work we propose the use of a data provenance structure based on the model PROV-DM for experiments in bioinformatics projects with the objective of allowing scientists to work with their experiments in ne detail, and, when necessary, consult them or re-execute them in a more planned and controlled way