Relevant bibliographies by topics / Data Lakes

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data Lakes'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Data Lakes"

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Mathis, Christian. "Data Lakes." Datenbank-Spektrum 17, no. 3 (2017): 289–93. http://dx.doi.org/10.1007/s13222-017-0272-7.

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Abhijit, Joshi. "The Rise of Data Lakes: Best Practices for Architecture and Value Extraction." Journal of Scientific and Engineering Research 5, no. 12 (2018): 342–47. https://doi.org/10.5281/zenodo.11667542.

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This whitepaper aims to elucidate the concept and strategic importance of data lakes, providing an in-depth technical exploration suitable for executives and technical stakeholders alike. Drawing upon established best practices derived from industry leaders and seasoned data experts at Cloudera, this document intends to demystify data lakes, advocating for their adoption based on proven principles rather than transient trends. Amidst the complexity and burgeoning volumes of business and analytical data, clarity on optimal data lake architectures and actionable strategies for extracting value i
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Sainath, Muvva. "The Role of Data Lake and Delta Lake in Big Data, Machine Learning, and Artificial Intelligence." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 10, no. 6 (2022): 1–6. https://doi.org/10.5281/zenodo.14535503.

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Data Lakes and Delta Lakes are changing how we store and manage big data. Data Lakes are like huge digital buckets that can hold all kinds of information. Delta Lakes make these buckets even better by adding special features. These features help keep data organized and easy to use.This paper looks at how these new ways of handling data have grown over time. This paper compares what Data Lakes and Delta Lakes can do, especially for smart computer programs that learn and make decisions. We also look at how different businesses use these tools.By looking at the good points, tricky parts, and real
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Veernapu, Kiran. "AI Enhanced Data Quality in Data Warehouses and Data Lakes for Efficient Data-Driven Intelligence." International Scientific Journal of Engineering and Management 03, no. 07 (2024): 1–6. https://doi.org/10.55041/isjem02160.

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Data quality is paramount in data-driven decision-making processes, especially when dealing with large volumes of data in environments like data warehouses and data lakes. These systems store vast amounts of raw and processed data from multiple sources, making data management and quality assurance complex yet critical. With the growing adoption of Artificial Intelligence (AI), new techniques and tools have emerged that can significantly enhance data quality. This paper discusses how AI can improve the quality of data within both data warehouses and data lakes by automating data cleansing, vali
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Ganachari, Girish. "DATA GOVERNANCE FOR ENTERPRISE DATA LAKES." Journal of Artificial Intelligence, Machine Learning and Data Science 1, no. 1 (2023): 958–61. http://dx.doi.org/10.51219/jaimld/girish-ganachari/228.

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Nandish Shivaprasad. "Strategies for Data Lakes in Financial Data Management." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 2033–50. https://doi.org/10.32628/cseit2410612413.

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The deployment and optimization of data lakes in financial data management is investigated in this research article. Concerning an ever-growing volume and diversity of data, conventional data management technologies are showing insufficient capability for financial organizations. Providing a scalable and flexible infrastructure for storing and evaluating enormous volumes of organized and unstructured data, data lakes provide a good answer. With an eye on data governance, security, and analytics, this paper investigates many approaches for building, running, and managing data lakes in the finan
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Janelidze, Gulnara, Ia Aptsiauri, and Lela Tsitashvili. "Data lakes: Opportunities, Challenges, Threats and Ways to Mitigate Them." Journal of Technical Science and Technologies 8, no. 2 (2024): 31–35. https://doi.org/10.31578/jtst.v8i2.159.

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Data lakes, which collect and store huge amounts of structured and unstructured data, are currently one of the most important technological tools. Their structure differs from traditional databases, as they are more flexible and allow organizations to store diverse data in a single repository for further processing and analysis. Their use is advisable in many fields, ranging from business and science to public administration. However, the rapid development of data lakes presents new challenges. The paper presents the key characteristics of data lakes and data warehouses, along with a comparati
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Chandrakanth, Lekkala. "Implementing Efficient Data Versioning and Lineage Tracking in Data Lakes." Journal of Scientific and Engineering Research 10, no. 8 (2023): 117–23. https://doi.org/10.5281/zenodo.12792488.

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Data lakes are now the most prevalent solution for storing and managing large data volumes in unstructured, semi-structured, and structured formats. However, the data science problem is not associated with the data lake growth and its size and complexity because it may become difficult to guarantee data reproducibility, traceability and governance. Data versioning and lineage tracking stand right at the heart of an effectively managed data lake, providing organizations with a way to track revisions within datasets, retain the record of changes that transform data, and maintain rules of data re
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Mandala, Nishanth Reddy. "ETL in Data Lakes vs. Data Warehouses." ESP Journal of Engineering & Technology Advancements 1, no. 2 (2021): 224–30. https://doi.org/10.56472/25832646/jeta-v1i2p123.

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Xiong, Runqun, Shiyuan Zhao, Ciyuan Chen, and Zhuqing Xu. "Optimizing Multimodal Data Queries in Data Lakes." Tsinghua Science and Technology 30, no. 6 (2025): 2625–37. https://doi.org/10.26599/tst.2025.9010022.

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Dissertations / Theses on the topic "Data Lakes"

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Bosque, Edward F. "Time series analysis of RTC Great Lakes recruit graduate data." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA359541.

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Dhar, Samir. "Addressing Challenges with Big Data for Maritime Navigation: AIS Data within the Great Lakes System." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1479391944819196.

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Dolder, Danisa. "Regional Water Quality Data Viewer Tool: An Open-Source to Support Research Data Access." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9196.

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Water quality data collection, storage, and access is a difficult task and significant work has gone into methods to store and disseminate these data. We present a tool to disseminate research in a simple method that does not replace but extends and leverages these tools. In the United States, the federal government maintains two systems to fill that role for hydrological data: the U.S. Geological Survey (USGS) National Water Information System (NWIS) and the U.S. Environmental Protection Agency (EPA) Storage and Retrieval System (STORET), since superseded by the Water Quality Portal (WQP). Th
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Peng, Rong. "Kylo Data Lakes Configuration deployed in Public Cloud environments in Single Node Mode." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18817.

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The master thesis introduces the Kylo Data Lake which deployed in the public cloud environment,provides a perspective of datalake configuration and data ingestion experiment. This paper reveals the underlying architecture of Kylo data lake.
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Allen, Jason D. "Correlating phytoplankton assemblages with water quality in Illinois lakes and reservoirs : validating models based on historical data /." View online, 2008. http://repository.eiu.edu/theses/docs/32211131464742.pdf.

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Vannah, Benjamin. "Integrated Data Fusion and Mining (IDFM) Technique for Monitoring Water Quality in Large and Small Lakes." Master's thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6028.

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Monitoring water quality on a near-real-time basis to address water resources management and public health concerns in coupled natural systems and the built environment is by no means an easy task. Furthermore, this emerging societal challenge will continue to grow, due to the ever-increasing anthropogenic impacts upon surface waters. For example, urban growth and agricultural operations have led to an influx of nutrients into surface waters stimulating harmful algal bloom formation, and stormwater runoff from urban areas contributes to the accumulation of total organic carbon (TOC) in surface
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Dörnhöfer, Katja Judith [Verfasser]. "Assessing water colour of lakes with high and medium spatial resolution remote sensing data / Katja Judith Dörnhöfer." Kiel : Universitätsbibliothek Kiel, 2018. http://d-nb.info/1161409491/34.

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Lovell, Jessica. "Long term organic carbon dynamics in 17 Swedish lakes : The impact of acid deposition and climate change." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-264516.

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During the last three decades, a number of studies based on national environmental monitoring data have found increased concentrations of total organic carbon (TOC) in surface waters in much of the northern hemisphere including Sweden. There are many hypothesis of what has been the main cause of this trend, including changes in land use, decreased atmospheric deposition of acidifying compounds and climate change. Different hypothesis may have different implications for quantifying pre-industrial levels and for future predictions of TOC concentrations, which in turn will have different implicat
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Scharfenberger, Ulrike [Verfasser]. "Linking ecological theory with data : How empirical data and theory can inform each other to understand threshold-driven changes in lakes under global change pressure / Ulrike Scharfenberger." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1121007627/34.

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Wright, Sarah E. "Sample Frequency, Duration, and Spatial Representation Considerations of Great Lakes Beach Sanitary Survey Data at Three Beaches in Racine, Wisconsin." Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1416922217.

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Books on the topic "Data Lakes"

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Schmitz, Uwe. Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8.

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Zhu, Zhen. Data Warehousing, Data Lakes and Data Lakehouses. Edited by Aeron Zentner. SAGE Publications, Inc., 2024. http://dx.doi.org/10.4135/9781071937471.

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C, Norton David, and Great Lakes Environmental Research Laboratory, eds. Great Lakes ice data rescue project. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, 2000.

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C, Norton David, and Great Lakes Environmental Research Laboratory., eds. Great Lakes ice data rescue project. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, 2000.

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Akira, Kurata, Kira Tatsuo 1919-, International Lake Environment Committee., and United Nations Environment Programme, eds. Compact-size edition of Data book of world lake environments: A survey of the state of world lakes. International Lake Environment Committee, 1994.

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Kay, Roger L. River ice data instrumentation. U.S. Army Cold Regions Research and Engineering Laboratory, 1997.

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White, Kathleen D. Ice jam data collection. U.S. Army Cold Regions Research and Engineering Laboratory, 1994.

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A, Johncox David, Mueller David K, Geological Survey (U.S.), and Arvada (Colo ), eds. Methods of data collection and water-quality data for Standley Lake, Jefferson County, Colorado, 1989-90. U.S. Geological Survey, 1992.

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Ruddy, Barbara C. Methods of data collection and water-quality data for Standley Lake, Jefferson County, Colorado, 1989-90. U.S. Geological Survey, 1992.

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J, Dunn William. Hoosic River basin survey: Water quality data, wastewater discharge data, 1991. Massachusetts Dept. of Environmental Protection, Div. of Water Pollution Control, Technical Services Section, 1992.

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Book chapters on the topic "Data Lakes"

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Schmitz, Uwe. "Grundlagen." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_2.

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Schmitz, Uwe. "Einleitung." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_1.

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Schmitz, Uwe. "Exemplarische Einsatzmöglichkeiten." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_5.

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Schmitz, Uwe. "Konzeption und Architektur." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_3.

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Schmitz, Uwe. "Bewertung." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_7.

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Schmitz, Uwe. "Organisatorische Rahmenbedingungen." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_6.

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Schmitz, Uwe. "Datengetriebene Geschäftsmodelle." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_4.

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Schmitz, Uwe. "Fazit." In Data Lakes. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70332-8_8.

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Johnston, Craig. "Data Lakes." In Advanced Platform Development with Kubernetes. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5611-4_7.

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Husain, Mohd Shahid, Mohammad Zunnun Khan, and Tamanna Siddiqui. "Data Lakes." In Big Data Concepts, Technologies, and Applications. Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003441595-8.

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Conference papers on the topic "Data Lakes"

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Duan, Junyi, Huaixiao Yan, and Chengcheng Tao. "Flood Impact and Condition Assessment for Bridge Infrastructure in Southern Lake Michigan Region through Hybrid Fluid-Structure Interaction and Data-Driven Modeling." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.1399.

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<p>With the increase of flood risk in the Great Lakes region, infrastructure and community are facing critical challenges. In this paper, we investigate and assess the flood impact on bridge infrastructure in southern Lake Michigan region through the integration of fluid-structure interaction and machine learning-based data-driven modeling. The integrated models will quantify the flood impact on the bridge using the flood wave information in southern Lake Michigan region and assess the corresponding conditions of the bridge infrastructure. The coupled computational fluids dynamics modeli
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Pingos, Michalis, Spyros Loizou, and Andreas Andreou. "Integrating Data Lakes with Self-Adaptive Serious Games." In 20th International Conference on Evaluation of Novel Approaches to Software Engineering. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013467700003928.

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Vaghasiya, Priyam, and Dhruvitkumar Patel. "Optimizing Data Lakes for High-Performance Analytics in Big Data Ecosystems." In 2024 Global Conference on Communications and Information Technologies (GCCIT). IEEE, 2024. https://doi.org/10.1109/gccit63234.2024.10862088.

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Bouabdelli, Lamisse, Fatma Abdelhedi, Slimane Hammoudi, and Allel Hadjali. "An Advanced Entity Resolution in Data Lakes: First Steps." In 14th International Conference on Data Science, Technology and Applications. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013643200003967.

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Weintraub, Grisha, Ehud Gudes, and Shlomi Dolev. "Indexing cloud data lakes within the lakes." In SYSTOR '21: The 14th ACM International Systems and Storage Conference. ACM, 2021. http://dx.doi.org/10.1145/3456727.3463828.

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Bauer, Daniel, Chris Giblin, Luis Garcés-Erice, et al. "Revisiting data lakes." In Middleware '22: 23rd International Middleware Conference. ACM, 2022. http://dx.doi.org/10.1145/3564695.3564773.

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Rodrigues, Jéssica Xafranski, and Ronaldo dos Santos Mello. "Um Estudo sobre Arquiteturas e Metadados em Data Lakes." In Escola Regional de Banco de Dados. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/erbd.2022.223535.

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A grande quantidade de dados hoje gerada pela Internet e por organizações requer novas abordagens de gerenciamento desses dados. Data lakes são repositórios de dados volumosos e têm sido uma alternativa para gerenciar dados e metadados heterogêneos. Este trabalho apresenta um estudo sobre arquiteturas e abordagens para gerenciamento de metadados no contexto de sistemas de gerência de data lake.
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Mazur, O. E. "NEW DATA ON THE INFECTION OF FISH WITH HEMOFLAGELLATES (PROTOZOA: KINETOPLASTEA) IN SOME WATER BODIES OF BURYATIA (EASTERN SIBERIA)." In THEORY AND PRACTICE OF PARASITIC DISEASE CONTROL. All-Russian Scientific Research Institute for Fundamental and Applied Parasitology of Animals and Plant – a branch of the Federal State Budget Scientific Institution “Federal Scientific Centre VIEV”, 2023. http://dx.doi.org/10.31016/978-5-6048555-6-0.2023.24.262-267.

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New data were received on infection with Kinetoplastida of the family Trypanosomatidae in fish of various taxonomic groups in lakes in the Republic of Buryatia (Eastern Siberia). Kinetoplastids of the genus Trypanosoma recorded in the river perch,
 common pike, sand sculpin, Siberian loach, crucian carp, and Siberian roach were
 characterized by the greatest host diversity. The roach (Gusinoe Lake) is recorded
 for the first time for the Baikal basin as a host for hemoflagellates of this genus.
 Blood parasites of the genus Trypanoplasma were found in 3 fish species: the pi
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Scholz, Christopher A., and Douglas Wood. "Early-Stage Extension in the Southwest East African Rift: Integration of New Seismic Reflection Data." In SPE/AAPG Africa Energy and Technology Conference. SPE, 2016. http://dx.doi.org/10.2118/afrc-2614293-ms.

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ABSTRACT The western branch of the East African Rift is characterized by modest amounts of extension and by deeply-subsided, fault-controlled basins filled with large, deep lakes. Lakes Tanganyika and Nyasa (Malawi) are two of the largest lakes in the world, with maximum water depths of 1450 and 700 m respectively. Newly acquired seismic reflection data, along with newly reprocessed legacy data reveal thick sedimentary sections, in excess of 5 km in some localities. The 1980's vintage legacy data from Project PROBE have been reprocessed through pre-stack depth migration in Lake Tanganyika, and
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Zhao, Jia, Russell Tessier, and Wayne Burleson. "Distributed sensor data processing for many-cores." In the great lakes symposium. ACM Press, 2012. http://dx.doi.org/10.1145/2206781.2206821.

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Reports on the topic "Data Lakes"

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Bailard, Jennifer. Mojave Desert Network (MOJN) Streams and Lakes (STLK) Data Quality Report 2024. National Park Service, 2025. https://doi.org/10.36967/2312646.

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This HTML report summarizes data quality evaluations of discrete data collected for the Mojave Desert Network Inventory and Monitoring Program Streams and Lakes protocol. This protocol is designed to monitor the hydrologic and ecosystem health of nine streams and six subalpine lakes in Great Basin National Park. Collected data include lake surface elevations, lake clarity, water quality measurements, stream channel characteristics, water chemistry samples, and benthic macroinvertebrate samples. Lake surface elevations, lake clarity, water quality measurements, and stream channel characteristic
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Bailard, Jennifer. Mojave Desert Network (MOJN) Streams and Lakes (STLK) Data Quality Report 2024. National Park Service, 2025. https://doi.org/10.36967/2313986.

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This HTML report summarizes data quality evaluations of discrete data collected for the Mojave Desert Network Inventory and Monitoring Program Streams and Lakes protocol. This protocol is designed to monitor the hydrologic and ecosystem health of nine streams and six subalpine lakes in Great Basin National Park. Collected data include lake surface elevations, lake clarity, water quality measurements, stream channel characteristics, water chemistry samples, and benthic macroinvertebrate samples. Lake surface elevations, lake clarity, water quality measurements, stream channel characteristics, a
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Swanson, David, and Celia Hampton-Miller. Drained lakes in Bering Land Bridge National Preserve: Vegetation succession and impacts on loon habitat. National Park Service, 2023. http://dx.doi.org/10.36967/2296593.

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The northern coastal plain of Bering Land Bridge National Preserve (BELA) lost lakes at an alarming rate over the first two decades of this century, including four lakes over 100 ha in size in 2018-2019 alone. To understand the effects of these lake drainages, we sampled vegetation of these lakes in 2019 (a reconnaissance visit) and 2021 (for the installation of permanent vegetation monitoring plots). We used these data to summarize the changes that occurred in the first three years after drainage, and to create vegetation maps from 3-m resolution satellite images coinciding with the visit dat
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Todd, B. J., C. F. M. Lewis, and G. D. Hobson. Resurrection of 1967 single-channel seismic reflection data and isopach map of sediments in central and eastern Lake Erie, Ontario, Canada, and Ohio, Pennsylvania, and New York, U.S.A. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331498.

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In the Laurentian Great Lakes, the seismostratigraphy revealed by legacy seismic reflection profiles (i.e., analogue paper records) provides insight to the history of glaciation and deglaciation, sediment deposition and lake level history. Digital recovery and analysis of Great Lakes legacy seismic data is a cost-effective method to generate the offshore broad scale surfaces pertinent to the surficial framework geology layer required as input by three-dimensional stratigraphic studies. This Open File describes the digital recovery of 1566 km of recently discovered single channel seismic reflec
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Swanson, David. Area of lakes and ponds continues to decline in Alaska’s Arctic national parks. National Park Service, 2025. https://doi.org/10.36967/2313920.

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The area of lakes and ponds in the five National Park Service (NPS) units in northern Alaska from the 1980s to 2024 was summarized using data from Landsat satellite images. During the period for which annual Landsat data are available (2000–2024), most of the study area showed declining surface water area. The areas with rapidly declining water area had lakes of thermokarst origin in ice-rich permafrost, and sudden lake drainage events were common. The years 2017–2019 and 2021 had the most lake drainage events during the study time interval, and the majority of lake drainages occurred in the l
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Milkereit, B., A. G. Green, P. Morel-à-l'Huissier, M. W. Lee, and W. F. Agena. 1986 Great Lakes seismic reflection survey, migrated data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1988. http://dx.doi.org/10.4095/130458.

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Xu, S., S. K. Frey, A. R. Erler, et al. Laurentian Great Lakes integrated hydrologic model data package. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328298.

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Kress, Marin, David Young, Katherine Chambers, and Brandan Scully. AIS data case study : quantifying connectivity for six Great Lakes port areas from 2015 through 2018. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40720.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) presents results from a preliminary examination of commercial vessel traffic connectivity between six major port areas on the Great Lakes using Automatic Identification System (AIS) data collected from 2015 to 2018. The six port areas included in this study are Calumet Harbor, IL and IN; Cleveland, OH; Detroit, MI; Duluth-Superior, MN and WI; Indiana Harbor, IN; and Two Harbors, MN. These six locations represent an important subset of the more than 100 federally authorized navigation projects in the Great Lakes maintained by the US
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Maurer, M. A. Compilation of limnological data for selected Kenai Peninsula lakes, southcentral Alaska. Alaska Division of Geological & Geophysical Surveys, 1988. http://dx.doi.org/10.14509/1387.

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Rautman, Christopher Arthur. Geologic investigation of Playa Lakes, Tonopah Test Range, Nevada : data report. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/920839.

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