Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries最新文献

BIP!

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1007/978-1-4020-6754-9_1834

Thanasis Vergoulis, Serafeim Chatzopoulos, Kleanthis Vichos, Ilias Kanellos, A. Mannocci, Natalia Manola, P. Manghi

引用次数: 0

ABCDEF

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1145/3529372.3530916

H. Holzmann, Nick Ruest, Jefferson Bailey, Alex Dempsey, Samantha Fritz, Peggy Lee, Ian Milligan

{"title":"ABCDEF","authors":"H. Holzmann, Nick Ruest, Jefferson Bailey, Alex Dempsey, Samantha Fritz, Peggy Lee, Ian Milligan","doi":"10.1145/3529372.3530916","DOIUrl":"https://doi.org/10.1145/3529372.3530916","url":null,"abstract":"Over the past quarter-century, web archive collection has emerged as a user-friendly process thanks to cloud-hosted solutions such as the Internet Archive’s Archive-It subscription service. Despite advancements in collecting web archive content, no equivalent has been found by way of a user-friendly cloud-hosted analysis system. Web archive processing and research require significant hardware resources and cumbersome tools that interdisciplinary researchers find difficult to work with. In this paper, we identify six principles the ABCDEFs (Archive, Big data, Concurrent, Distributed, Efficient, and Flexible) - used to guide the development and design of a system. These make the transformation of, and working with, web archive data as enjoyable as the collection process. We make these objectives - largely common sense - explicit and transparent in this paper. They can be employed by every computing platform in the area of digital libraries and archives and adapted by teams seeking to implement similar infrastructures. Furthermore, we present ARCH (Archives Research Compute Hub 1, the first cloud-based system designed from scratch to meet all of these six key principles. ARCH is an interactive interface, closely connected with Archive-It, engineered to provide analytical actions, specifically generating datasets and in-browser visualizations. It efficiently streamlines research workflows while eliminating the burden of computing requirements. Building off past work by both the Internet Archive (Archive-It Research Services) and the Archives Unleashed Project (the Archives Unleashed Cloud), this merged platform achieves a scalable processing pipeline for web archive research. It is open-source and can be considered a reference implementation of the ABCDEF, which we have evaluated and discussed in terms of feasibility and compliance as a benchmark for similar platforms.CCS CONCEPTS • Information systems $rightarrow$ Digital libraries and archives; Data extraction and integration. 1https://github.com/internetarchive/arch","PeriodicalId":193331,"journal":{"name":"Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116602418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

HedgePeer HedgePeer

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1145/3529372.3533300

Tirthankar Ghosal, Kamal Kaushik Varanasi, Valia Kordoni

{"title":"HedgePeer","authors":"Tirthankar Ghosal, Kamal Kaushik Varanasi, Valia Kordoni","doi":"10.1145/3529372.3533300","DOIUrl":"https://doi.org/10.1145/3529372.3533300","url":null,"abstract":"Prague, Czech Republic Uncertainty detection from text is essential in many applications in information retrieval (IR). Detecting textual uncertainties helps extract factual information instead of uncertain or non-factual information. To avoid overprecise commitment, people use linguistic devices like hedges (uncertain words or phrases). In peer reviews, reviewers often use hedges wherever they are unsure about their opinion or when facts do not back their opinions. Usage of hedges or uncertain words in writing can also indicate the reviewer’s confidence or measure of conviction in their reviews. Reviewer confidence is important in the peer review process (especially to the editors or chairs) to judge the quality of evaluation of the paper under review. However, the self-annotated reviewer confidence score is often miscalibrated or biased and not an accurate representation of the reviewer’s conviction of their judgment on the merit of the paper. Less confident reviewers sometimes speculate their observations. Here in this paper, we introduce HedgePeer, a new uncertainty detection dataset of peer review comments, which is more than five times larger than the existing datasets on hedge detection in other domains. We curate our dataset from the open-access reviews available in the open review platform and annotate the review comments in terms of the hedge cues and hedge spans. We also provide several baseline approaches, including a multitask learning model with sentiment intensity and parts-of-speech as scaffold tasks to predict hedge cues and spans. We make our dataset and baseline codes available at https://github.com/Tirthankar-Ghosal/HedgePeer-Dataset. Our dataset is motivated towards computationally estimating the reviewer’s conviction from their review texts. CCS CONCEPTS • Computing methodologies → Information extraction; • Information systems → Information extraction.","PeriodicalId":193331,"journal":{"name":"Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130575968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

SchenQL

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1145/3529372.3533282

Christin Katharina Kreutz, Martin Blum, R. Schenkel

引用次数: 1

StreamingHub StreamingHub

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1145/3529372.3530936

Yasith Jayawardana, V. Ashok, S. Jayarathna

{"title":"StreamingHub","authors":"Yasith Jayawardana, V. Ashok, S. Jayarathna","doi":"10.1145/3529372.3530936","DOIUrl":"https://doi.org/10.1145/3529372.3530936","url":null,"abstract":"Reusable data/code and reproducible analyses are foundational to quality research. This aspect, however, is often overlooked when designing interactive stream analysis workflows for time-series data (e.g., eye-tracking data). A mechanism to transmit informative metadata alongside data may allow such workflows to intelligently consume data, propagate metadata to downstream tasks, and thereby auto-generate reusable, reproducible analytic outputs with zero supervision. Moreover, a visual programming interface to design, develop, and execute such workflows may allow rapid prototyping for interdisciplinary research. Capitalizing on these ideas, we propose StreamingHub, a framework to build metadata propagating, interactive stream analysis workflows using visual programming. We conduct two case studies to evaluate the generalizability of our framework. Simultaneously, we use two heuristics to evaluate their computational fluidity and data growth. Results show that our framework generalizes to multiple tasks with a minimal performance overhead. CCS CONCEPTS • Information systems → Document representation; Data management systems; • Human-centered computing → Visualization.","PeriodicalId":193331,"journal":{"name":"Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114747335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Open refine to wikibase: a new data upload pipeline 打开refine到wikibase:一个新的数据上传管道

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1145/3529372.3530919

Lucia Sohmen, Lozana Rossenova

引用次数: 0

TermoPL

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1145/3529372.3533301

P. Rychlik, M. Marciniak, A. Mykowiecka

引用次数: 1

Building digital library collections with greenstone 3 tutorial 建立数字图书馆收藏与绿石3教程

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2022-06-20 DOI: 10.1145/3529372.3530944

D. Bainbridge

引用次数: 0

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries 第22届ACM/IEEE数字图书馆联合会议论文集

Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries Pub Date : 2002-07-14 DOI: 10.1145/3529372

W. Hersh, G. Marchionini

{"title":"Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries","authors":"W. Hersh, G. Marchionini","doi":"10.1145/3529372","DOIUrl":"https://doi.org/10.1145/3529372","url":null,"abstract":"Welcome to JCDL 2002! This is the second in a series of ACM/IEEE-CS joint conferences on research and development in digital libraries. JCDL 2002 is a major international forum for research reports and discussion on digital libraries and associated technical, practical, and social issues. The conference takes a broad view of digital libraries as both extensions and augmentations of physical libraries, archives, museums, and other cultural institutions. The program captured in these proceedings represents a snapshot of the current state of digital library research and development and provides glimmers into the future of what digital libraries may become.This year's conference attracted 240 submissions from researchers in 18 countries. All full and short papers were reviewed by at least three members of the program committee and those accepted were revised for inclusion in these proceedings. Thirty-three of 99 full papers and 36 of 73 short papers were accepted this year. In addition to the papers, demonstrations, posters, and panels add to the mix of theory and practice and two keynote addresses will stimulate thought and discussion on intellectual property issues and trends in digital library practice. Eight tutorials and seven workshops bookend the conference to provide in-depth treatments of specific topics and issues. As in past years, the Vannevar Bush Award for best paper will be awarded in honor of Dr. Bush, the founder of the National Science Foundation and proposer of the Memex. This award was initiated by Robert Akscyn, President of Knowledge Systems, Inc. A subcommittee of the program committee (Lois Delcambre, Sue Dumais, Linda Hill, Gary Marchionini, Michael Nelson, and Rebecca Wesley) reviewed the seven highest rated papers to select a winner. This year's award goes to Donna Bergmark for her paper \"Collection Synthesis.","PeriodicalId":193331,"journal":{"name":"Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125504357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 40