ترغب بنشر مسار تعليمي؟ اضغط هنا

Comprehensiveness of Archives: A Modern AI-enabled Approach to Build Comprehensive Shared Cultural Heritage

169   0   0.0 ( 0 )
 نشر من قبل Abhishek Gupta
 تاريخ النشر 2020
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

Archives play a crucial role in the construction and advancement of society. Humans place a great deal of trust in archives and depend on them to craft public policies and to preserve languages, cultures, self-identity, views and values. Yet, there are certain voices and viewpoints that remain elusive in the current processes deployed in the classification and discoverability of records and archives. In this paper, we explore the ramifications and effects of centralized, due process archival systems on marginalized communities. There is strong evidence to prove the need for progressive design and technological innovation while in the pursuit of comprehensiveness, equity and justice. Intentionality and comprehensiveness is our greatest opportunity when it comes to improving archival practices and for the advancement and thrive-ability of societies at large today. Intentionality and comprehensiveness is achievable with the support of technology and the Information Age we live in today. Reopening, questioning and/or purposefully including others voices in archival processes is the intention we present in our paper. We provide examples of marginalized communities who continue to lead community archive movements in efforts to reclaim and protect their cultural identity, knowledge, views and futures. In conclusion, we offer design and AI-dominant technological considerations worth further investigation in efforts to bridge systemic gaps and build robust archival processes.



قيم البحث

اقرأ أيضاً

311 - Fionn Murtagh 2008
The history of data analysis that is addressed here is underpinned by two themes, -- those of tabular data analysis, and the analysis of collected heterogeneous data. Exploratory data analysis is taken as the heuristic approach that begins with data and information and seeks underlying explanation for what is observed or measured. I also cover some of the evolving context of research and applications, including scholarly publishing, technology transfer and the economic relationship of the university to society.
Event collections are frequently built by crawling the live web on the basis of seed URIs nominated by human experts. Focused web crawling is a technique where the crawler is guided by reference content pertaining to the event. Given the dynamic natu re of the web and the pace with which topics evolve, the timing of the crawl is a concern for both approaches. We investigate the feasibility of performing focused crawls on the archived web. By utilizing the Memento infrastructure, we obtain resources from 22 web archives that contribute to building event collections. We create collections on four events and compare the relevance of their resources to collections built from crawling the live web as well as from a manually curated collection. Our results show that focused crawling on the archived web can be done and indeed results in highly relevant collections, especially for events that happened further in the past.
157 - Yuhang Lu , Jun Zhou , Jing Wang 2017
Motivated by the important archaeological application of exploring cultural heritage objects, in this paper we study the challenging problem of automatically segmenting curve structures that are very weakly stamped or carved on an object surface in t he form of a highly noisy depth map. Different from most classical low-level image segmentation methods that are known to be very sensitive to the noise and occlusions, we propose a new supervised learning algorithm based on Convolutional Neural Network (CNN) to implicitly learn and utilize more curve geometry and pattern information for addressing this challenging problem. More specifically, we first propose a Fully Convolutional Network (FCN) to estimate the skeleton of curve structures and at each skeleton pixel, a scale value is estimated to reflect the local curve width. Then we propose a dense prediction network to refine the estimated curve skeletons. Based on the estimated scale values, we finally develop an adaptive thresholding algorithm to achieve the final segmentation of curve structures. In the experiment, we validate the performance of the proposed method on a dataset of depth images scanned from unearthed pottery sherds dating to the Woodland period of Southeastern North America.
Web archiving services play an increasingly important role in todays information ecosystem, by ensuring the continuing availability of information, or by deliberately caching content that might get deleted or removed. Among these, the Wayback Machine has been proactively archiving, since 200
226 - Julian Posada 2020
This commentary traces contemporary discourses on the relationship between artificial intelligence and labour and explains why these principles must be comprehensive in their approach to labour and AI. First, the commentary asserts that ethical frame works in AI alone are not enough to guarantee workers rights since they lack enforcement mechanisms and the representation of different stakeholders. Secondly, it argues that current discussions on AI and labour focus on the deployment of these technologies in the workplace but ignore the essential role of human labour in their development, particularly in the different cases of outsourced labour around the world. Finally, it recommends using existing human rights frameworks for working conditions to provide more comprehensive ethical principles and regulations. The commentary concludes by arguing that the central question regarding the future of work should not be whether intelligent machines will replace humans, but who will own these systems and have a say in their development and operation.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا