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AURA (Archives in the UK/ Republic of Ireland & AI): Bringing together Digital Humanists, Computer Scientists & stakeholders to unlock cultural assets

AURA (Archives in the UK/ Republic of Ireland & AI): Bringing together Digital Humanists, Computer Scientists & stakeholders to unlock cultural assets
AURA(英国/爱尔兰共和国档案馆)
批准号:
AH/V002341/1
负责人:
Lise Jaillant
金额:
$3.08万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
The AURA network brings together Digital Humanists, Computer Scientists, archivists and other stakeholders to unlock cultural assets held in "dark" digital archives currently closed to users. Not so long ago, historians, literary scholars and other scholars would read letters and other papers preserved in Special Collections Libraries. Of course, this analogue world has not disappeared, but the digital revolution has profoundly changed the way we encounter archives. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Yet, preserving born-digital records is not enough. We also need access to these archival materials, in order to produce new knowledge and foster public engagement. Archives are meant to be used, not locked away. A central problem is that most born-digital archives are closed to users due to privacy, copyright or technical issues. Even when access is possible (as in the case of web archives), users often need to physically travel to repositories rather than consult materials remotely. In order to unlock cultural assets, we need to bring the best minds together and harness the latest technology. At present, applying Artificial Intelligence to archives remains at the exploratory stage. Yet, automation is no longer a choice, it is a necessity. AI can be used to separate personal and business emails and improve accessibility to non-confidential records; identify sections of documents that refer to personal data allowing partial views or limited access to the archival content; extract named entities (people names, dates, events) from archives and link them to external sources.While access to digital archives is essential, we also need to anticipate the moment when born-digital records will be more accessible. To make sense of this mass of data, new methodologies are urgently needed, combining traditional humanistic methods with data-rich approaches. Collaborations between Humanities scholars, Computer Scientists, archivists and other stakeholders are therefore essential to make archives more accessible, but also to design new methodologies to analyse huge amounts of data.The network will focus on three major themes, that will be explored in each of the three workshops: "Open Data versus Privacy" (Workshop 1 in Dublin); "AI and Archives: Current Challenges and Prospects of Born-digital archives" (Workshop 2 in London); "AI and Archives: What comes next?" (Workshop 3 in Edinburgh). The workshops will be carefully structured to include a mix of short presentations, speed meetings with interdisciplinary teams to discuss a specific question relating to the overall workshop theme, and practical activities designed to lead to mutually beneficial, sustainable collaborations. We will also create wiki pages for each workshop to foster asynchronous discussion, and build on the participation of people that cannot be onsite. In addition, a project website will keep track of all the network activities in the form of reports, blog posts and recordings of presentations. Associated social media, as well as a dedicated listserv, will help us connect with interested parties - in academia, archival institutions and beyond.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1007/s00146-021-01370-2
发表时间: 2022
期刊: AI & SOCIETY
影响因子: 3
作者: [Dobbs T]
通讯作者: Dobbs T
Using AI and ML to optimize information discovery in under-utilized, Holocaust-related records
使用人工智能和机器学习优化未充分利用的大屠杀相关记录中的信息发现
DOI: 10.1007/s00146-021-01368-w
发表时间: 2022
期刊: AI & SOCIETY
影响因子: 3
作者: [Carter K]
通讯作者: Carter K
DOI: 10.1007/s00146-021-01367-x
发表时间: 2022
期刊: AI & society
影响因子: 3
作者: [Jaillant L, Caputo A]
通讯作者: Caputo A
Finding light in dark archives: using AI to connect context and content in email
在黑暗档案中寻找光明:使用人工智能连接电子邮件中的上下文和内容
DOI: 10.1007/s00146-021-01369-9
发表时间: 2021
期刊: AI & SOCIETY
影响因子: 3
作者: [Decker S]
通讯作者: Decker S
9
    Unlocking our Digital Past with Artificial Intelligence (LUSTRE)
    • 批准号:
      AH/X003132/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $10.28万
    • 财政年份:
      2022
    • 负责人:
      Lise Jaillant
    • 依托单位:
    EyCon (Visual AI and Early Conflict Photography)
    • 批准号:
      AH/W008408/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $12.88万
    • 财政年份:
      2022
    • 负责人:
      Lise Jaillant
    • 依托单位:
    AEOLIAN (Artificial intelligence for cultural organisations)
    • 批准号:
      AH/V009443/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $7.46万
    • 财政年份:
      2021
    • 负责人:
      Lise Jaillant
    • 依托单位:
    Survival of the Weakest: Preserving and Analysing Born-Digital Records to Understand How Small Poetry Publishers Survive in the Global Marketplace
    • 批准号:
      AH/R00773X/1
    • 项目类别:
      Fellowship
    • 资助金额:
      $24.84万
    • 财政年份:
      2018
    • 负责人:
      Lise Jaillant
    • 依托单位:
    海外基金