Knowledge Tree
big data
Also known as: big data analytics
Facts (30)
Sources
Advancing energy efficiency: innovative technologies and strategic ... oaepublish.com 7 facts
claimDigital solutions and smart grid technologies, such as big data and artificial intelligence, enhance power distribution efficiency, reduce losses, and facilitate the integration of renewable energy sources.
claimEmerging technologies such as artificial intelligence, big data, and blockchain have the potential to optimize energy management, enhance grid flexibility, and promote further efficiencies.
claimUtilities can use big data analytics to predict peak usage times and develop demand response plans that incentivize customers to reduce or shift energy usage, helping to stabilize the grid and optimize energy distribution.
claimBig data analytics accelerates energy audits by providing detailed insights into energy consumption patterns, allowing organizations to compare performance against industry standards and track progress.
referenceMarinakis, V., Doukas, H., Tsapelas, J., et al. published 'From big data to smart energy services: an application for intelligent energy management' in the journal Future Generation Computer Systems in 2020 (Volume 110, 572-86).
claimThe rise of big data provides organizations with new opportunities to enhance energy management processes by extracting insights from vast amounts of collected data.
referenceThe study titled 'Advancing energy efficiency: innovative technologies and strategic ...' synthesizes advancements in energy efficiency technologies across transportation, power generation, urban development, and industry, integrating case studies, policy frameworks, and technologies like blockchain, big data, and artificial intelligence.
A comprehensive overview on demand side energy management ... link.springer.com Mar 13, 2023 4 facts
referenceSimmhan Y, Aman S, Kumbhare A, Liu R, Stevens S, Zhou Q, and Prasanna V developed a cloud-based software platform for big data analytics in smart grids, as published in Computing in Science & Engineering in 2013.
referenceGiovanelli C, Liu X, Sierla S, Vyatkin V, and Ichise R (2017) explored the development of an aggregator that utilizes big data to bid on the frequency containment reserve market.
referenceSimmhan Y, Aman S, Kumbhare A, Liu R, Stevens S, Zhou Q, and Prasanna V developed a cloud-based software platform for big data analytics in smart grids, as published in Computing in Science & Engineering in 2013.
referenceGiovanelli et al. (2017) explored the development of an aggregator that utilizes big data to participate in the frequency containment reserve market.
Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org 4 facts
claimRecent approaches to entity resolution for knowledge graphs utilize multi-source big data techniques, Deep Learning, or knowledge graph embeddings.
referenceKricke, Grimmer, and Schmeißer published 'Preserving Recomputability of Results from Big Data Transformation Workflows' in Datenbank-Spektrum in 2017.
referenceM. Giese, A. Soylu, G. Vega-Gorgojo, A. Waaler, P. Haase, E. Jiménez-Ruiz, D. Lanti, M. Rezk, G. Xiao, Ö.L. Özçep, and R. Rosati authored 'Optique: Zooming in on Big Data', published in Computer in 2015.
referenceThe paper 'An Overview of End-to-End Entity Resolution for Big Data' by V. Christophides, V. Efthymiou, T. Palpanas, G. Papadakis, and K. Stefanidis was published in ACM Computing Surveys.
The New Field of Network Physiology: Building the Human ... frontiersin.org 2 facts
claimFuture developments in Network Physiology aim to establish the Human Physiolome, a form of Big Data containing large-scale signals from multiple systems and a repository of network maps representing physiological systems interactions for different states, conditions, and diseases.
claimThe keywords associated with the field of network physiology include dynamic networks, complex systems, control, AI, sensory networks, big data, and human physiolome.
Emerging Technologies And Their Impact On International Relations ... hoover.org 2 facts
claimThe use of Big Data and AI poses a significant problem regarding the manipulation of public opinion, as evidenced by the role of Cambridge Analytica in the Donald Trump campaign and alleged Russian infiltration in the 2016 US elections.
claimThe current landscape of emerging technologies includes Artificial Intelligence (AI), the Internet of Things (IoT), Big Data, blockchain, quantum computing, advanced robotics, autonomous systems, additive manufacturing (3D-printing), social networks, and biotechnology/genetic engineering.
Global perspectives on energy technology assessment and ... link.springer.com Oct 30, 2025 2 facts
referenceDigital transformation in the energy sector encompasses technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Big Data Analytics, and Blockchain, which facilitate processes, improve working capabilities, and enable data-driven decision-making.
claimEnergy technology assessment (ETA) research is increasingly integrating digital technologies, such as AI-driven modelling and big data analytics, to enhance decision-making for low-carbon systems.
Free and open-source software - Wikipedia en.wikipedia.org 1 fact
claimThe European Commission stated in 2017 that EU institutions should become open source software users and listed open source software as one of nine key drivers of innovation, alongside big data, mobility, cloud computing, and the internet of things.
The role of open source in shaping software thetopvoices.com Nov 12, 2024 1 fact
claimOpen source drives technological advancement in fields including artificial intelligence, machine learning, and big data.
Study about the impact of open source software and hardware ... digital-strategy.ec.europa.eu Sep 2, 2021 1 fact
claimThe study identified strengths, weaknesses, opportunities, and challenges of open source in ICT policy areas including cybersecurity, artificial intelligence, digitizing European industry, connected cars, high-performance computing, big data, and distributed ledger technologies.
Knowledge Graphs: Opportunities and Challenges - Springer Nature link.springer.com Apr 3, 2023 1 fact
claimData processing in the age of big data is a challenging task due to the complex and unstructured nature of educational data.
Virtue Epistemology - Stanford Encyclopedia of Philosophy plato.stanford.edu Jul 9, 1999 1 fact
referenceMichael P. Lynch explored the impact of big data on knowledge and understanding in his 2016 book 'The Internet of Us: Knowing More and Understanding Less in the Age of Big Data'.
Neuro-Symbolic AI: Explainability, Challenges & Future Trends linkedin.com Dec 15, 2025 1 fact
claimScalability limitations in neuro-symbolic AI arise because symbolic components do not scale easily with increasing knowledge base size or data complexity, limiting their utility in big data or dynamic environments.
A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Dec 9, 2025 1 fact
claimThe integration of neuro-symbolic AI with Big Data and IoT frameworks offers a pathway toward scalable, interpretable, and context-aware intelligence.
The Impact of Open Source Software on Technological Innovation ... linkedin.com Jun 7, 2024 1 fact
claimFoundational components of advanced technology ecosystems, including cloud computing, artificial intelligence, and big data analytics, are built on open-source platforms.
The evolution of the electronic components industry - tstronic tstronic.eu Sep 16, 2025 1 fact
claimModern electronic manufacturing service (EMS) providers and distributors utilize cloud platforms, big data analytics, and AI-driven tools to perform real-time availability analysis of components across global networks.