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Lesson Observation Data in Learning Analytics Datasets: Observata [chapter]

Maka Eradze, Mart Laanpere
2017 Lecture Notes in Computer Science  
The technological environment that supports the learning process tends to be the main data source for Learning Analytics.  ...  This paper focuses on how the data extracted from the observations can be integrated with data coming from activity tracking, resulting in a multimodal dataset.  ...  Conclusions and Future Work In this paper, we have discussed the importance of observational data inclusion into MMLA dataset.  ... 
doi:10.1007/978-3-319-66610-5_50 fatcat:kjtjskimevaovdiys7ctg7vdyq

Real World Applications of Machine Learning Techniques over Large Mobile Subscriber Datasets [article]

Jobin Wilson, Chitharanj Kachappilly, Rakesh Mohan, Prateek Kapadia, Arun Soman, Santanu Chaudhury
2015 arXiv   pre-print
However, due to the sheer data volume, variety, velocity and veracity of mobile subscriber datasets, sophisticated data analytics techniques and frameworks are necessary to derive actionable insights in  ...  service personalization and targeted promotions to a distributed Big Data Analytics platform, capable of performing large scale machine learning and data mining to deliver real time service personalization  ...  into a scalable big data analytics platform, enabling large scale machine learning applications.  ... 
arXiv:1502.02215v1 fatcat:zgjpne4cu5hn7pecrgvmq437bi

Images of the arXiv: Reconfiguring large scientific image datasets

Kynan Tan, Anna Munster, Adrian Mackenzie
2021 Journal of Cultural Analytics  
We suggest that such methods allow us different entry points into large scientific image datasets and that they initiate a new set of questions about how scientific representation might be operating at  ...  In this article, we suggest ways -including algorithms drawn from machine learning that facilitate visually 'slicing' through the image data and metadata -for exploring large datasets of statistical scientific  ...  From this, we propose that the ML and deep learning techniques we use func tion to observe a transversal plane in the image arXiv dataset.  ... 
doi:10.22148/001c.21374 fatcat:vhp3c5eicrhpxn5p6ltxcxyw2q

Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets

Laurens Bogaardt, Romulo Goncalves, Raul Zurita-Milla, Emma Izquierdo-Verdiguier
2019 ISPRS International Journal of Geo-Information  
For instance, it is used in dimensionality reduction and as a support operator for various analytical tasks applicable to spatio-temporal data.  ...  This article examines several such techniques in relation to the inherent scale of the structure within the data.  ...  Then, the lessons learned are verified using real-world datasets.  ... 
doi:10.3390/ijgi8020055 fatcat:h3pgorj4qrdfdcgcmbrnnce2mi

QDataset: Quantum Datasets for Machine Learning [article]

Elija Perrier, Akram Youssry, Chris Ferrie
2021 arXiv   pre-print
The datasets are structured to provide a wealth of information to enable machine learning practitioners to use the QDataSet to solve problems in applied quantum computation, such as quantum control, quantum  ...  The availability of large-scale datasets on which to train, benchmark and test algorithms has been central to the rapid development of machine learning as a discipline and its maturity as a research discipline  ...  is to classify data into discrete categories.  ... 
arXiv:2108.06661v1 fatcat:ig6eijrobrgqjgsqcn7bcqpgua

Using Conversation Analysis in Data-Driven Aviation Training with Large-Scale Qualitative Datasets

William Tuccio, Maurice Nevile
2017 Journal of Aviation/Aerospace Education & Research  
This includes new technologies such as mobile learning as well as new ways of collecting and managing training data.  ...  The purpose of the study is to show how the CARM frameworktailored to large-scale, long-duration interactionsmay be applied to the recordings to create interactive training targeting two goals: (a) flight  ...  Acknowledgements We are grateful to the editors and reviewers for their valuable comments. Thanks to those who freely shared their training flights, including Matt Wells, Rodney Hoover, John Kiger,  ... 
doi:10.15394/jaaer.2017.1706 fatcat:7wnyt4rugvfknmet756eds7rcm

Stagnated Liberalization, Long‐term Convergence, and Index Methodology: Three Lessons from the CITRIX Citizenship Policy Dataset

Samuel D. Schmid
2021 Global Policy  
The main idea of this approach is to use statistical dimensionality tests to validate deductively specified additive concept structures. This is the first lesson we can learn from CITRIX.  ...  While explaining the construction of the dataset, I advance a synthetic approach to index methodology.  ...  Acknowledgements I would like to thank Giacomo Solano and Marc Helbling for inviting me to contribute to this special section.  ... 
doi:10.1111/1758-5899.12903 fatcat:ndabigye2nfwpojw7yegmbhqke

Interactive Exploration of Implicit and Explicit Relations in Faceted Datasets

Jian Zhao, Christopher Collins, Fanny Chevalier, Ravin Balakrishnan
2013 IEEE Transactions on Visualization and Computer Graphics  
It was mostly from him that I learned how to be a good researcher and how to explore the world with novel approaches and critical thinking.  ...  My greatest thanks must go to my supervisor, Ravin Balakrishnan. He was the first to bring me into the academic world and open my eyes.  ...  It has been a challenging adventure, and I was fortune to receive support from many people. They have deeply inspired my minds and shaped my thinking. I would like to thank all of them,  ... 
doi:10.1109/tvcg.2013.167 pmid:24051774 fatcat:43xwwk6lezbqzk2bf65ivvkp5u

Accessible data curation and analytics for international-scale citizen science datasets

Benjamin Murray, Eric Kerfoot, Liyuan Chen, Jie Deng, Mark S. Graham, Carole H. Sudre, Erika Molteni, Liane S. Canas, Michela Antonelli, Kerstin Klaser, Alessia Visconti, Alexander Hammers (+8 others)
2021 Scientific Data  
We present ExeTera, a Python-based open source software package designed to provide Pandas-like data analytics on datasets that approach terabyte scales.  ...  The size of the dataset means that it can no longer be readily processed using standard Python-based data analytics software such as Pandas on commodity hardware.  ...  Finally, this dataset is novel in terms of its scale and deployment for epidemiological analysis, and the schema has been altered to better capture data based on lessons learned during early phases of  ... 
doi:10.1038/s41597-021-01071-x pmid:34811392 pmcid:PMC8608807 fatcat:bh7tyo2dafgzpkwy4wwnh3es4e

Design Implications of Digital Social Innovation: A Playful Approach to Analyse Cases Study Dataset [chapter]

Francesca Valsecchi, Miaosen Gong
2014 Lecture Notes in Computer Science  
We conclude by discussing the lesson learn by this cases study analysis that privileged the heuristics of digital tools to the hermeneutics of more traditional research approaches.  ...  We approach the analysis by information visualization methods and data manipulation tools, and in the paper we present process and results of the visualization, and the discussion of the stories we gather  ...  Density Design Research Lab, Milan Polytechnic and their RAW, kindly given away to the use of everybody, as the spirit of community and opensource inspired.  ... 
doi:10.1007/978-3-319-07308-8_35 fatcat:vqjwbtgombhcdptjkuj7uudhiu

Algorithmic Fairness Datasets: the Story so Far [article]

Alessandro Fabris, Stefano Messina, Gianmaria Silvello, Gian Antonio Susto
2022 arXiv   pre-print
Progress in fair Machine Learning hinges on data, which can be appropriately used only if adequately documented.  ...  Data-driven algorithms are studied in diverse domains to support critical decisions, directly impacting people's well-being.  ...  Acknowledgements The authors would like to thank the following researchers and dataset creators for the useful feedback on the data briefs: Alain Barrat, Luc Behaghel, Asia Biega, Marko Bohanec, Chris  ... 
arXiv:2202.01711v2 fatcat:5hf4a42pubc5vnt7tw3al4m5bq

Multi-decadal oceanic ecological datasets and their application in marine policy and management

Martin Edwards, Gregory Beaugrand, Graeme C. Hays, J. Anthony Koslow, Anthony J. Richardson
2010 Trends in Ecology & Evolution  
Lessons learnt from reviewing these sequences of observations provide valuable context for the continuation of existing time-series and perspective for the initiation of new time-series in response to  ...  Concluding sections call for a more integrated approach to marine observation systems and highlight the future role of ocean observations in adaptive marine management.  ...  Second, ocean observations are also needed for evaluating the efficacy of management actions and for learning about how the system functions in order to improve future management.  ... 
doi:10.1016/j.tree.2010.07.007 pmid:20813425 fatcat:ccpsasgwe5an5lsb7kxujl2aze

Deliverable 1.6 Beneficiaries Dataset - 1st Call

S.A. Bright Development Studio
2020 Zenodo  
This report compiles the Open Dataset containing the list of beneficiaries, project description and funds of BlockStart's open call #1 (Ideation Kick-off, Prototype and Pilot stages), which took place  ...  Now it is possible to generate reports from its own production and aggregate data from past producers.  ...  The system is based on blockchain technology, remote sensing and big data analytics.  ... 
doi:10.5281/zenodo.5244819 fatcat:df6lzez6afeihc4eeyhiqk3ycu

Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets

Anna Di Mauro, Andrea Cominola, Andrea Castelletti, Armando Di Nardo
2020 Water  
Counting these new datasets and more traditional aggregate water demand data, the literature is rich with heterogeneous urban water demand datasets.  ...  The reviewed datasets are classified and analyzed according to the following criteria: spatial scale, temporal scale, and dataset accessibility.  ...  Moreover, since digital disruption has transformed the electricity industry earlier and some lessons learned may apply also in the water or multi-utility sectors [26] , we additionally explore similarities  ... 
doi:10.3390/w13010036 fatcat:wwjoo2xjxffrpbhubozjtfjpfq

V for variety: Lessons learned from complex smart cities data harmonization and integration

Iman Avazpour, John Grundy, Liming Zhu
2016 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)  
These tasks support improved business intelligence, analytics and enduser access to data.  ...  We then discuss a set of lessons that we have learned from our experience that we hope will be useful for others embarking on similar problems.  ...  We hope the lessons help novice data analytics developers in their harmonization task and to better incorporate resources.  ... 
doi:10.1109/percomw.2016.7457092 dblp:conf/percom/AvazpourGZ16 fatcat:cdr6sxb3cnbovcfirjslum4ewa
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