[ABE-L] Convite: Seminário DEST/UFMG em 20/08/2021.

[Vinicius Mayrink]

Caros,

Na próxima sexta-feira (*20 de agosto, às 13:30h*) o ciclo de
Seminários do *Departamento
de Estatística da UFMG* terá a apresentação de *Thais C. O. Fonseca*.

Thais é Professora do DME - IM (UFRJ) e obteve o título de Doutora em
Estatística pela *University of Warwick* (Reino Unido). Entre 2019-2020
realizou período pós-doc na *University of Warwick*. Ela já foi presidente
da ISBrA (Capítulo Brasileiro da ISBA) e é pesquisadora visitante no
IPEA-RJ. Suas áreas de pesquisa são: Inferência Bayesiana, Estatística
Espacial, Modelos Multiescala, Processamento de Imagem e Econometria.

O seminário será transmitido ao vivo pelo canal do Youtube "*Seminários
DEST - UFMG <https://www.youtube.com/channel/UCoZC2_pME9ca_-Hx4djd60w>*".

Att,
Vinícius Mayrink

*********** Título e Resumo ***********

Thais C. O. Fonseca (DME -IM, UFRJ)

*Can you render your Lattes? A Bayesian Network modelling of digital
preservation risks.*

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technology, outdated policies, and a skills gap across the archives sector.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).

-- 
*Vinícius D. Mayrink*
*Professor Associado - Departamento de Estatística*

*ICEx, Universidade Federal de Minas Gerais*
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