{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T14:01:38Z","timestamp":1742997698600,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030633929"},{"type":"electronic","value":"9783030633936"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-63393-6_28","type":"book-chapter","created":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T09:04:28Z","timestamp":1608627868000},"page":"425-442","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics"],"prefix":"10.1007","author":[{"given":"Suzanne","family":"Parete-Koon","sequence":"first","affiliation":[]},{"given":"Peter F.","family":"Peterson","sequence":"additional","affiliation":[]},{"given":"Garrett E.","family":"Granroth","sequence":"additional","affiliation":[]},{"given":"Wenduo","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Pravallika","family":"Devineni","sequence":"additional","affiliation":[]},{"given":"Nouamane","family":"Laanait","sequence":"additional","affiliation":[]},{"given":"Junqi","family":"Yin","sequence":"additional","affiliation":[]},{"given":"Albina","family":"Borisevich","sequence":"additional","affiliation":[]},{"given":"Ketan","family":"Maheshwari","sequence":"additional","affiliation":[]},{"given":"Melissa","family":"Allen-Dumas","sequence":"additional","affiliation":[]},{"given":"Srinath","family":"Ravulaparthy","sequence":"additional","affiliation":[]},{"given":"Kuldeep","family":"Kurte","sequence":"additional","affiliation":[]},{"given":"Jibo","family":"Sanyal","sequence":"additional","affiliation":[]},{"given":"Anne","family":"Berres","sequence":"additional","affiliation":[]},{"given":"Olivera","family":"Kotevska","sequence":"additional","affiliation":[]},{"given":"Folami","family":"Alamudun","sequence":"additional","affiliation":[]},{"given":"Keith","family":"Gray","sequence":"additional","affiliation":[]},{"given":"Max","family":"Grossman","sequence":"additional","affiliation":[]},{"given":"Anar","family":"Yusifov","sequence":"additional","affiliation":[]},{"given":"Ioana","family":"Danciu","sequence":"additional","affiliation":[]},{"given":"Gil","family":"Alterovitz","sequence":"additional","affiliation":[]},{"given":"Dasha","family":"Herrmannova","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,12,18]]},"reference":[{"key":"28_CR1","unstructured":"https:\/\/neutrons.ornl.gov\/vulcan"},{"issue":"3","key":"28_CR2","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1107\/S1600576718004727","volume":"51","author":"GE Granroth","year":"2018","unstructured":"Granroth, G.E., et al.: Event-based processing of neutron scattering data at the Spallation neutron source. J. Appl. Crystallogr. 51(3), 616 (2018)","journal-title":"J. Appl. Crystallogr."},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Wang, X.L., et al.: First results from the VULCAN diractometerat the SNS. In: Materials Science Forum, vol. 652, pp. 105\u2013110. Trans Tech Publications (2010)","DOI":"10.4028\/www.scientific.net\/MSF.652.105"},{"key":"28_CR4","doi-asserted-by":"publisher","unstructured":"Niyanth, S, Noyan, I.C., Seren, M.H., An, K.: Vulcan Beamline dataset. In: Partly supported by the US Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office program. This research used resources at the SNS, a DOE Office of Science User Facility operated by Oak Ridge National Laboratory. https:\/\/doi.org\/10.13139\/ORNLNCCS\/1604074","DOI":"10.13139\/ORNLNCCS\/1604074"},{"key":"28_CR5","doi-asserted-by":"publisher","unstructured":"Laanait, N., Borisevich, A., Yin, J.: A Database of Convergent Beam Electron Diffraction Patterns for Machine Learning of the Structural Properties of Materials. https:\/\/doi.org\/10.13139\/ORNLNCCS\/1604074","DOI":"10.13139\/ORNLNCCS\/1604074"},{"key":"28_CR6","doi-asserted-by":"publisher","unstructured":"Allen-Dumas, M., New, J. Chicago microclimate and building energy use data. https:\/\/doi.org\/10.13139\/ORNLNCCS\/1619243","DOI":"10.13139\/ORNLNCCS\/1619243"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Berres, A., Im, P., Kurte, K., Allen-Dumas, M., Thakur, G., Sanyal, J.: A mobility-driven approach to modeling building energy. In: 5th IEEE Workshop on Big Data Analytics in Supply Chains and Transportation, Los Angeles (2019)","DOI":"10.1109\/BigData47090.2019.9006308"},{"key":"28_CR8","unstructured":"https:\/\/nhts.ornl.gov\/"},{"key":"28_CR9","unstructured":"Microsoft building footprints. https:\/\/github.com\/Microsoft\/USBuildingFootprints"},{"key":"28_CR10","unstructured":"https:\/\/usbuildingdata.blob.core.windows.net\/usbuildings-v1-1\/Illinois.zip"},{"key":"28_CR11","unstructured":"Census data for Chicago community areas. https:\/\/datahub.cmap.illinois.gov\/dataset\/2010-census-data-summarized-to-chicago-community-areas"},{"key":"28_CR12","unstructured":"https:\/\/datahub.cmap.illinois.gov\/dataset\/community-data-snapshots-raw-data"},{"key":"28_CR13","unstructured":"https:\/\/krisenergy.com\/company\/about-oil-and-gas\/exploration\/"},{"key":"28_CR14","unstructured":"https:\/\/www.geoexpro.com\/articles\/2016\/01\/super-high-resolution-seismic-data-in-the- norwegian-barents-sea"},{"key":"28_CR15","unstructured":"https:\/\/digital.gov\/2019\/02\/27\/how-a-health-tech-sprint-inspired-an-ai-ecosystem"},{"key":"28_CR16","unstructured":"https:\/\/www.whitehouse.gov\/briefings-statements\/call-action-tech-community-new-machine-readable-covid-19-dataset\/"},{"key":"28_CR17","unstructured":"https:\/\/www.kaggle.com\/allen-institute-for-ai\/CORD-19-research-challenge\/tasks"},{"key":"28_CR18","volume-title":"Flow: The Psychology of Optimal Experience","author":"M Csikszentmihalyi","year":"1990","unstructured":"Csikszentmihalyi, M.: Flow: The Psychology of Optimal Experience. Harper Perennial, New York (1990)"},{"key":"28_CR19","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1002\/cd.26","volume":"93","author":"DJ Shernoff","year":"2001","unstructured":"Shernoff, D.J., Hoogstra, L.: Continuing motivation beyond the high school classroom. New Dir. Child Adolesc. Dev. 93, 73\u201387 (2001)","journal-title":"New Dir. Child Adolesc. Dev."},{"issue":"5","key":"28_CR20","doi-asserted-by":"publisher","first-page":"e93949","DOI":"10.1371\/journal.pone.0093949","volume":"9","author":"M Khabsa","year":"2014","unstructured":"Khabsa, M., Giles, C.L.: The number of scholarly documents on the public web. PloS One 9(5), e93949 (2014)","journal-title":"PloS One"},{"key":"28_CR21","unstructured":"Wang, LL., et al.: CORD-19: The Covid-19 Open Research Dataset. arXiv (2020)"},{"issue":"1","key":"28_CR22","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1162\/qss_a_00021","volume":"1","author":"K Wang","year":"2020","unstructured":"Wang, K., Shen, Z., Huang, C., Chieh-Han, W., Dong, Y., Kanakia, A.: Microsoft academic graph: when experts are not enough. Quant. Sci. Stud. 1(1), 396\u2013413 (2020)","journal-title":"Quant. Sci. Stud."},{"issue":"3","key":"28_CR23","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1002\/leap.1033","volume":"29","author":"AD Wade","year":"2016","unstructured":"Wade, A.D., Wang, K.: The rise of the machines: artificial intelligence meets scholarly content. Learned Publishing 29(3), 201\u2013205 (2016)","journal-title":"Learned Publishing"},{"key":"28_CR24","doi-asserted-by":"crossref","unstructured":"Saggion, H., Ronzano, F.: Scholarly data mining: making sense of scientific literature. In: 2017 ACM\/IEEE Joint Conference on Digital Libraries (JCDL), pp. 1\u20132 (2017)","DOI":"10.1109\/JCDL.2017.7991622"},{"key":"28_CR25","unstructured":"U.S. Energy Information Administration. Use of energy in the United States-Energy explained. https:\/\/www.eia.gov\/energyexplained\/index.php"},{"key":"28_CR26","unstructured":"DOE Office of Energy Efficiency and Renewable Energy efficiency trends in residential and commercial buildings. http:\/\/www.osti.gov\/servlets\/purl\/1218835\/"}],"container-title":["Communications in Computer and Information Science","Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-63393-6_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T22:08:15Z","timestamp":1619302095000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-63393-6_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030633929","9783030633936"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-63393-6_28","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"18 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SMC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Smoky Mountains Computational Sciences and Engineering Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Oak Ridge, TN","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"smc2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/smc.ornl.gov\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"94","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.75","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}