The Project PAI Data Protocol ("PAI Data") is a specification that extends the Project PAI Blockchain Protocol to include a method of securing and provisioning access to arbitrary data. In the context of PAI Coin Development Proposal (PDP) 2, this pa...
Progress Data Cloud brings all your data services in one place so you can achieve your data and AI goals faster.
In some fields, scientific data formats differ across experiments due to specialized hardware and data acquisition systems. Researchers need to develop, document, and maintain experiment-specific analysis software to interact with these data formats....
Positive-unlabeled learning refers to the process of training a binary classifier using only positive and unlabeled data. Although unlabeled data can contain positive data, all unlabeled data are regarded as negative data in existing positive-unlabel...
from data sets, so that the people whom the data describe remain anonymous. Data anonymization has been defined as a "process by which personal data is
Dirty data, also known as rogue data, are inaccurate, incomplete or inconsistent data, especially in a computer system or database. Dirty data can contain
parts of the data and then replacing, modifying, or deleting the affected data. Data cleansing can be performed interactively using data wrangling tools
Data is the lifeblood of the modern world, forming a fundamental part of AI, decision-making, and research advances. With increase in interest in data, governments have taken important steps towards a regulated data world, drastically impacting data...
Industry 4.0 offers opportunities to combine multiple sensor data sources using IoT technologies for better utilization of raw material in production lines. A common belief that data is readily available (the big data phenomenon), is oftentimes chall...
Data streams are often defined as large amounts of data flowing continuously at high speed. Moreover, these data are likely subject to changes in data distribution, known as concept drift. Given all the reasons mentioned above, learning from streams...
Reference data is data used to classify or categorize other data. Typically, they are static or slowly changing over time. Examples of reference data include:
Nov 11, 2024 · Metadata is often described as “data about data,” providing information about a data item, file, or collection that helps us understand, find, and use it effectively.
This document defines the high level metadata necessary to describe the physical parameter space of observed or simulated astronomical data sets, such as 2D-images, data cubes, X-ray event lists, IFU data, etc.. The Characterisation data model is an...
Looking to export all data? Go to Export all your organization's data. With the Data Export tool, you can export some or all of your organization’s data to a Google Cloud Storage archive and download it. …
Looking to export all data? Go to Export all your organization's data. With the Data Export tool, you can export some or all of your organization’s data to a Google Cloud Storage archive and …
Hi reddit! We [unveiled the CERN Open Data Portal to the world](http://home.web.cern.ch/about/updates/2014/11/cern-makes-public-first-data-lhc-experiments) recently, releasing [samples for education]...
This paper discusses about the challenges, advantages and shortcomings of existing solutions in data security and privacy in public cloud computing. As in cloud computing, oceans of data will be stored. Data stored in public cloud would face both out...
We introduce the concept of {\it fresh data trading}, in which a destination user requests, and pays for, fresh data updates from a source provider, and data freshness is captured by the {\it age of information} (AoI) metric. Keeping data fresh relie...
Despite data's crucial role in machine learning, most existing tools and research tend to focus on systems on top of existing data rather than how to interpret and manipulate data. In this paper, we propose DataLab, a unified data-oriented platform t...
In the context of cloud environments, data providers entrust their data to data consumers in order to allow further computing on their own IT infrastructure. Usage control measures allow the data provider to restrict the usage of its data even on the...