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<h1 class="">LDAV 2022 – Large Data Analysis and Visualization<o:p class=""></o:p></h1>
<p class="MsoNormal"><span lang="EN-GB" class="" style="font-size: 12pt;">The 12<sup class="">th</sup> IEEE Symposium on Large Data Analysis and Visualization, held in conjunction with IEEE VIS 2022, October 15, 2022, Oklahoma City, OK, USA<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><a href="https://nam12.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.ldav.org%2F&data=05%7C01%7C%7C8c24668a63cc491f06a708da3f3842a5%7C31d7e2a5bdd8414e9e97bea998ebdfe1%7C0%7C0%7C637891808115595248%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=zVRPadqEm5mrFCPFXnN63pa7F%2Bj1I%2BaZIIUBpI11zQc%3D&reserved=0" originalsrc="http://www.ldav.org/" shash="Jjn23pjdknfzd9oDj5rUaI9picQBHCiCOecMh9YBtxujjGGVyCv0Z40bGP16asNUNwiZzH+OlbzTTov0fQmj7kk5vAS5TsEisWzMVp24OqFPWY6YkFMY1UeqDhZaXdBbDiUnVlTxNkZpdgAoExk8AJu4JMs1i8wwKFStJUgosN8=" class=""><span class="InternetLink"><u class=""><span class="" style="font-size: 12pt; text-decoration: none;">http://www.ldav.org/</span></u></span></a><span class="" style="font-size: 12pt;"><o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">Contact: </span><a href="mailto:papers@ldav.org" class=""><span class="" style="font-size: 12pt;">papers@ldav.org</span></a><span class="" style="font-size: 12pt;"> </span></p>
<font size="3" class=""><span class="">Johanna Beyer - Harvard University<br class="">
<br class="">
</span><span class="">Steffen Frey - University of Groningen<br class="">
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</span></font><span class=""><font size="3" class="">Paul Navratil - Texas Advanced Computing Center</font><br class="">
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<p class="MsoNormal"><span lang="EN-GB" class="" style="font-size: 12pt;">Data scales are increasing throughout scientific, business, and research contexts. Large-scale scientific simulations, observation </span><span class="" style="font-size: 12pt;">technologies</span><span lang="EN-GB" class="" style="font-size: 12pt;">,
sensor networks, and experiments are generating enormous datasets, with some projects approaching the multiple exabyte range in the near term.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span lang="EN-GB" class="" style="font-size: 12pt;">Gaining insight from massive data is critical for disciplines such as climate science, nuclear physics, security, materials design, transportation, urban planning, and so on. Business-critical
decisions are made based on massive data in domains like social media, machine learning, software telemetry, and business intelligence. The tools and approaches needed to search, analyze, and visualize data at extreme scales can be fully realized only from
end-to-end solutions, and with collective, interdisciplinary efforts.</span><span class="" style="font-size: 12pt;"><o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span lang="EN-GB" class="" style="font-size: 12pt;">The 12<sup class="">th</sup> IEEE Large Scale Data Analysis and Visualization (LDAV) symposium, to be held in conjunction with IEEE VIS 2022, is specifically targeting methodological
innovation, algorithmic foundations, and possible end-to-end solutions. The LDAV symposium will bring together domain experts, data analysts, visualization researchers, and users to foster common ground for solving both near- and long-term problems.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">Scope:<o:p class=""></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" class="" style="font-size: 12pt;">We are looking for papers on a broad range of topics related to collection, analysis, manipulation, and visualization of large-scale data. We are particularly interested in innovative
approaches that combine information visualization, visual analytics, and scientific visualization.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span lang="EN-GB" class="" style="font-size: 12pt;">LDAV welcomes papers on techniques and algorithms, systems, application and design studies, empirical studies, state of the practice, and position statements. </span><span class="" style="font-size: 12pt;">See
the LDAV website for more details about topics. Please contact the paper chairs (</span><a href="mailto:papers@ldav.org" class=""><span class="" style="font-size: 12pt;">papers@ldav.org</span></a><span class="" style="font-size: 12pt;">) with specific questions.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span lang="EN-GB" class="" style="font-size: 12pt;">Representative topics include:<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpFirst" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Distributed,
parallel, and multi-threaded computation<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Streaming
methods<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Innovative
software solutions<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Advanced
hardware and GPU-based approaches<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Hierarchical
data storage, retrieval, processing, and rendering<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Sampling,
approximate query processing, and progressive computation<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Collection,
management, and curation of massive datasets</span><span class="" style="font-size: 12pt;"><o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Scalable
visualization and exploration methods<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Ensemble
data visualization and analysis<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">In-situ
data analysis<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Best
practices for large data visualization</span><span class="" style="font-size: 12pt;"><o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">End-to-end
system solutions in a large data context</span><span class="" style="font-size: 12pt;"><o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><a name="move508729398" class=""></a><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Industry
solutions for big data analysis and visualization<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Collaboration
or/and co-design of large data analysis with domain experts</span><a name="move5087280611" class=""></a><a name="move5087280911" class=""></a><span class="" style="font-size: 12pt;"><o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Cognitive
issues specific to manipulating and understanding large data<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">Application
case studies<o:p class=""></o:p></span></p>
<p class="MsoListParagraphCxSpLast" style="text-indent: -0.25in;"><a name="move5087293981" class=""></a><span lang="EN-GB" class="" style="font-size: 12pt; font-family: Symbol;">·<span class="" style="font-stretch: normal; font-size: 7pt; line-height: normal; font-family: "Times New Roman";"> </span></span><span lang="EN-GB" class="" style="font-size: 12pt;">New
challenges in visualizing experimental, observational, or simulation data<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">As part of the review criteria, reviewers will be asked to assess whether the contribution is in scope for LDAV, i.e., whether it considers “large data.” Therefore, we strongly encourage you to clearly
identify the “large data” aspect you address. <o:p class=""></o:p></span></p>
<p class="MsoNormal"><span class="" style="font-size: 12pt;"> <o:p class=""></o:p></span></p>
<p class="MsoNormal"><span class="" style="font-size: 12pt;">For LDAV, we define large data to be data of size and complexity that require innovation to be processed and understood. With respect to size, the techniques for handling this data require either
using atypical hardware or specialized techniques that run on typical hardware. Examples of atypical hardware include supercomputers or novel hardware (such as a just-released GPU, an understudied device like a FPGA, or a high-resolution display), with corresponding
techniques including, for example, efficient parallelization. There are many examples of specialized techniques that enable typical hardware to operate effectively on large data; canonical examples including multi-resolution and streaming techniques. With
respect to complexity, techniques in scope for LDAV should be illuminating data sets that are considerably larger than typical for a given task, for example, but not restricted to: rendering, layout, analysis, etc. Finally, data may be large relative to the
resources available, and such examples are welcomed at LDAV. For example, novel techniques may be needed to visualize or analyze data on a Raspberry Pi or sensor network.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><b class=""><span class="" style="font-size: 12pt;">Submission Instructions:<o:p class=""></o:p></span></b></p>
<p class="MsoNormal"><span class="" style="font-size: 12pt;">LDAV is accepting both <b class="">full papers</b> and <b class="">short papers</b>. The manuscripts should be formatted according to </span><a href="https://nam12.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.cs.sfu.ca%2F~vis%2FTasks%2Fcamera.html&data=05%7C01%7C%7C8c24668a63cc491f06a708da3f3842a5%7C31d7e2a5bdd8414e9e97bea998ebdfe1%7C0%7C0%7C637891808115751488%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=YgaqxUUNR0piepo2OgMhfoAxqQGBlvXE4TuduEDAAq0%3D&reserved=0" originalsrc="http://www.cs.sfu.ca/~vis/Tasks/camera.html" shash="AY3Shz/7CHsGWiw387gDODbgzGHbfRj4eVdujJ6aGXFRXrz1WCVmQrJkxjikdg4WSgV7DRvHy4Xfqf6U8lCq3tIzzhyl3D03VvGt1KhIakEmcPBrFU/wcQsFss985kRZwxUNMfX75UXsj2Uh7o/ToBf84ie2Yk5J7sCB2MXKAL8=" class=""><span class="InternetLink"><b class=""><span class="" style="font-size: 12pt; color: rgb(14, 115, 192);">guidelines
from IEEE VGTC</span></b></span></a><span class="" style="font-size: 12pt;">. Submission of an abstract is required prior to submission of a paper or short paper.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><b class=""><span class="" style="font-size: 12pt;">Submission site note:</span></b><span class="" style="font-size: 12pt;"> Go to the </span><a href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fnew.precisionconference.com%2Fvgtc&data=05%7C01%7C%7C8c24668a63cc491f06a708da3f3842a5%7C31d7e2a5bdd8414e9e97bea998ebdfe1%7C0%7C0%7C637891808115751488%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=l8BW87m%2B1A86FHM3an3Ksbp9iigMqhYPPSJ60SJR1U4%3D&reserved=0" originalsrc="https://new.precisionconference.com/vgtc" shash="VT4kk0p2c0BPNRLH6srWKPGicvJzIkjyK095xhx/DUZ8tW0Soy+1u/6sZh3vsLcvD8Q3ze/zSiGNYMsiP3nDP1LlEWBXqeLKDkkUBxUZDB1DaeC46+Tqw+vAAQOlh+APptPQsyJzEAwXk4znl57b6DuaBvxBsupmMg1QOzw8SIo=" class=""><span class="InternetLink"><b class=""><span class="" style="font-size: 12pt; color: rgb(14, 115, 192);">submission
site</span></b></span></a><b class=""><span class="" style="font-size: 12pt; color: rgb(14, 115, 192);"> </span></b><span class="" style="font-size: 12pt;">(<a name="OLE_LINK1" class=""></a><a name="OLE_LINK2" class=""></a><a name="__DdeLink__278_171723797" class=""></a><a href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fnew.precisionconference.com%2Fvgtc&data=05%7C01%7C%7C8c24668a63cc491f06a708da3f3842a5%7C31d7e2a5bdd8414e9e97bea998ebdfe1%7C0%7C0%7C637891808115751488%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=l8BW87m%2B1A86FHM3an3Ksbp9iigMqhYPPSJ60SJR1U4%3D&reserved=0" originalsrc="https://new.precisionconference.com/vgtc" shash="VT4kk0p2c0BPNRLH6srWKPGicvJzIkjyK095xhx/DUZ8tW0Soy+1u/6sZh3vsLcvD8Q3ze/zSiGNYMsiP3nDP1LlEWBXqeLKDkkUBxUZDB1DaeC46+Tqw+vAAQOlh+APptPQsyJzEAwXk4znl57b6DuaBvxBsupmMg1QOzw8SIo=" class="">https://new.precisionconference.com/vgtc</a>),
log in, go to 'Submissions', and select Society ‘VGTC’, Conference ‘LDAV 2022’, and Track ‘LDAV 2022 Papers’.<o:p class=""></o:p></span></p>
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<h2 class="">Full Papers<o:p class=""></o:p></h2>
<p class="MsoNormal"><span class="" style="font-size: 12pt;">Full papers should have a maximum length of 9 pages with up to two (2) additional pages allowed for only references (maximum total of 11 pages). Full papers may make contributions in techniques, systems,
applications, evaluations, or theory. The contributions of full papers are reviewed based on their novelty, contribution, replicability, and evaluation.<o:p class=""></o:p></span></p>
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<h2 class="">Short Papers<o:p class=""></o:p></h2>
<p class="MsoNormal"><span class="" style="font-size: 12pt;">Short papers should have a length of 4-5 pages in total. Short papers are a venue to report smaller contributions than full papers. Position papers and showcases of interesting application of visualization
are good topics for short papers. Technique, system, application, evaluation, or theory papers that have a smaller contribution than a full paper can also be submitted as a short paper.<o:p class=""></o:p></span></p>
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<h1 class="">Proceedings:<o:p class=""></o:p></h1>
<p class="MsoNormal"><span class="" style="font-size: 12pt;">The proceedings of the symposium will be published together with the VIS proceedings and via the IEEE Xplore Digital Library.<o:p class=""></o:p></span></p>
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<h1 class="">Best Paper:<o:p class=""></o:p></h1>
<p class="MsoNormal"><span class="" style="font-size: 12pt;">The LDAV Program Committee will present a Best Paper award to the authors whose submission is deemed the strongest according to the reviewing criteria. This award will be announced in conjunction
with VIS 2022.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">The Best Paper for LDAV will be published directly in IEEE Transactions on Visualization and Computer Graphics (TVCG). Further, other excellent papers will be encouraged to submit journal versions
of their work to TVCG (at least 30% new scientific/technical content), with reviewer continuity.<o:p class=""></o:p></span></p>
<h1 class="">Important Dates:<o:p class=""></o:p></h1>
<p class="MsoNormal"><span class="" style="font-size: 12pt;">Please note: all deadlines are firm and no extensions will be granted.<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">Abstract Deadline (firm):<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">June 13, 2022, 11:59 PM (AOE)<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">Paper Submission (firm):<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">June 20, 2022, 11:59 PM (AOE)<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">Author Notification:<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">July 25, 2022<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">Camera-Ready Deadline:<o:p class=""></o:p></span></p>
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<p class="MsoNormal"><span class="" style="font-size: 12pt;">August 8, 2022</span></p>
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