Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.)最新文献_第5页

Querying Videos Using DNN Generated Labels 使用DNN生成标签查询视频

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209909

Yifan Wu, S. Drucker, Matthai Philipose, Lenin Ravindranath

引用次数: 1

SchemaDrill

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209908

William Spoth, Ting Xie, Oliver Kennedy, Ying Yang, B. Hammerschmidt, Z. Liu, D. Gawlick

引用次数: 7

What Type of a Matcher Are You?: Coordination of Human and Algorithmic Matchers 你是哪种类型的匹配者?:人力和算法匹配器的协调

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209905

Roee Shraga, A. Gal, Haggai Roitman

引用次数: 13

Draining the Data Swamp: A Similarity-based Approach 抽干数据沼泽:基于相似性的方法

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209911

Will Brackenbury, Rui Liu, Mainack Mondal, Aaron J. Elmore, Blase Ur, K. Chard, M. Franklin

{"title":"Draining the Data Swamp: A Similarity-based Approach","authors":"Will Brackenbury, Rui Liu, Mainack Mondal, Aaron J. Elmore, Blase Ur, K. Chard, M. Franklin","doi":"10.1145/3209900.3209911","DOIUrl":"https://doi.org/10.1145/3209900.3209911","url":null,"abstract":"While hierarchical namespaces such as filesystems and repositories have long been used to organize data, the rapid increase in data production places increasing strain on users who wish to make use of the data. So called \"data lakes\" embrace the storage of data in its natural form, integrating and organizing in a Pay-as-you-go fashion. While this model defers the upfront cost of integration, the result is that data is unusable for discovery or analysis until it is processed. Thus, data scientists are forced to spend significant time and energy on mundane tasks such as data discovery, cleaning, integration, and management -- when this is neglected, \"data lakes\" become \"data swamps.\" Prior work suggests that pure computational methods for resolving issues with the data discovery and management components are insufficient. Here, we provide evidence to confirm this hypothesis, showing that methods such as automated file clustering are unable to extract the necessary features from repositories to provide useful information to end-user data scientists, or make effective data management decisions on their behalf. We argue that the combination of frameworks for specifying file similarity and human-in-the-loop interaction is needed to aid automated organization. We propose an initial step here, classifying several dimensions by which items may be considered similar: the data, its origin, and its current characteristics. We initially consider this model in the context of identifying data that can be integrated or managed collectively. We additionally explore how current methods can be used to automate decision making using real-world data repository and file systems, and suggest how an online user study could be developed to further validate this hypothesis.","PeriodicalId":92279,"journal":{"name":"Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.)","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81259739","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: 25

Human-in-the-Loop Data Analysis: A Personal Perspective 人在循环数据分析:个人视角

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209913

A. Doan

{"title":"Human-in-the-Loop Data Analysis: A Personal Perspective","authors":"A. Doan","doi":"10.1145/3209900.3209913","DOIUrl":"https://doi.org/10.1145/3209900.3209913","url":null,"abstract":"In the past few years human-in-the-loop data analysis (HILDA) has received significant growing attention. Most HILDA works have focused on concrete problems. In this paper I take a step back and discuss several \"big picture\" questions regarding HILDA. First, I discuss problems that I believe should fall under the scope of the field, including some that have received little attention, such as fostering user communities that develop data repositories and tools. Next, I discuss important aspects in developing HILDA solutions that I believe should receive more attention. These include solving problems that real users care about, developing how-to guides to users, building end-to-end systems (such as extending the \"Pandas system\"), developing challenges and benchmarks, and developing a theory of human data interaction. Finally, I speculate about the future of the field, and discuss the dangers it can face, given that many other communities are also working on related problems. I argue that a focus on end-to-end problems and system building is important for us to thrive and make significant impacts.","PeriodicalId":92279,"journal":{"name":"Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.)","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79032057","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: 27

DIVE 潜水

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209910

Kevin Hu, Diana Orghian, César Hidalgo

引用次数: 2

Optimally Leveraging Density and Locality for Exploratory Browsing and Sampling 最优地利用密度和局部性进行探索性浏览和抽样

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209903

Albert Kim, Liqi Xu, Tarique Siddiqui, Silu Huang, S. Madden, Aditya G. Parameswaran

引用次数: 11

Evaluating Visual Data Analysis Systems: A Discussion Report 评估视觉数据分析系统:讨论报告

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-06-10 DOI: 10.1145/3209900.3209901

L. Battle, M. Angelini, Carsten Binnig, T. Catarci, P. Eichmann, Jean-Daniel Fekete, G. Santucci, M. Sedlmair, Wesley Willett

{"title":"Evaluating Visual Data Analysis Systems: A Discussion Report","authors":"L. Battle, M. Angelini, Carsten Binnig, T. Catarci, P. Eichmann, Jean-Daniel Fekete, G. Santucci, M. Sedlmair, Wesley Willett","doi":"10.1145/3209900.3209901","DOIUrl":"https://doi.org/10.1145/3209900.3209901","url":null,"abstract":"Visual data analysis is a key tool for helping people to make sense of and interact with massive data sets. However, existing evaluation methods (e.g., database benchmarks, individual user studies) fail to capture the key points that make systems for visual data analysis (or visual data systems) challenging to design. In November 2017, members of both the Database and Visualization communities came together in a Dagstuhl seminar to discuss the grand challenges in the intersection of data analysis and interactive visualization. In this paper, we report on the discussions of the working group on the evaluation of visual data systems, which addressed questions centered around developing better evaluation methods, such as \"How do the different communities evaluate visual data systems?\" and \"What we could learn from each other to develop evaluation techniques that cut across areas?\". In their discussions, the group brainstormed initial steps towards new joint evaluation methods and developed a first concrete initiative --- a trace repository of various real-world workloads and visual data systems --- that enables researchers to derive evaluation setups (e.g., performance benchmarks, user studies) under more realistic assumptions, and enables new evaluation perspectives (e.g., broader meta analysis across analysis contexts, reproducibility and comparability across systems).","PeriodicalId":92279,"journal":{"name":"Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.)","volume":"71 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85698291","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: 19

Provenance for Interactive Visualizations 交互式可视化的来源

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2018-05-07 DOI: 10.1145/3209900.3209904

Fotis Psallidas, Eugene Wu

引用次数: 11

Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations 使用实例级可视化解释解释黑箱分类器

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. Workshop on Human-In-the-Loop Data Analytics (2nd : 2017 : Chicago, Ill.) Pub Date : 2017-05-14 DOI: 10.1145/3077257.3077260

Paolo Tamagnini, Josua Krause, Aritra Dasgupta, E. Bertini

引用次数: 62