26

May

2022
Seminars

A BAYESIAN NETWORK MODELLING OF DIGITAL PRESERVATION RISKS

Time
16h00 - 19h00
Place
FGV

About Event

Digital records comprise primary sources which may be physical, born-digital or digitised. They are under threat from rapidly evolving technology, outdated policies and a skills gap across the archives sector. Thus, the preservation of digital material is a challenge for which many archives feel underprepared and ill-equipped. This talk presents the results of the Safeguarding the Nation’s Memory Project which aimed to help archivists manage digital preservation risks through the creation of a new quantitative risk management framework. This project has produced the web-based app DiAGRAM (the Digital Archiving Graphical Risk Assessment Model) which quantifies the effect on preservation risk of various actions and interventions. This work brings Bayesian Network methods into the digital heritage sphere for the first time through close collaboration with specialists in this field. Soft elicitation was used to identify the most likely elements contributing to digital preservation and their interrelations. Where good quality data was not available, expert elicitation based on the IDEA protocol was applied to define the unknown probability distributions. The result is a compact representation of reality, enabling the risk scores for various scenarios to be compared via expected utilities.

 

Joint work with Martine J. Barons (AS&RU, Department of Statistics, University of Warwick), Jim Q. Smith (AS&RU, Department of Statistics, University of Warwick), Hannah Merwood (Government Operational Research Service, UK), Alex Green (The National Archives, UK) and David H. Underdown (The National Archives, UK).

I. Seminar participants will not be able to access FGV premises wearing shorts, flip-flops, top or cropped tshirts, miniskirt or tank top. The use of the mask and the presentation of proof of vaccination (physical or digital) will be mandatory.  II. Text provided by the author. 

Apoiadores / Parceiros / Patrocinadores

Speakers

Thais Fonseca

Possui graduação e mestrado em Estatística pela Universidade Federal do Rio de Janeiro ambos em 2004 e doutorado em Estatística pela University of Warwick (2010). No período de 2019-2020 foi research fellow no Applied Statistics&Risk Unit, University of Warwick, UK. Orienta alunos de iniciação científica, mestrado e doutorado. Publicou artigos em periódicos de Estatística como JASA, Biometrika e outros e é autora de 3 capítulos de livro (2011, 2018 e 2021). Revisor de diversos periódicos tais como JASA, JRSS-C e Bayesian Analysis entre outros. Presidente eleita da ISBrA na gestão 2017-2018. Membro do Programa de Pós-Graduação em Estatística do IM/UFRJ desde 2011 e atualmente Vice-coordenadora do Programa de Pós-graduação em Estatística e Especialização em Ciência de Dados. Tem experiência na área de Probabilidade e Estatística, atuando nos seguintes temas: Redes Bayesianas, Inferência Bayesiana, Modelos Espaciais e Espaço-temporais, Modelos robustos, Econometria Bayesiana e Atuária. Entre 2016-2017 foi pesquisadora visitante no Instituto de Pesquisa Econômica Aplicada (IPEA, RJ).

Location

Fundação Getulio Vargas

Praia de Botafogo, 190 - sala 537

Informações: emap@fgv.br – 3799-5917

Endereço

Praia de Botafogo, 190 - sala 537

Informações: emap@fgv.br – 3799-5917