Value of Information: Intellectual Property, Privacy and Big Data

2018 ◽  
Keyword(s):  
Big Data ◽  
Intellectual Property ◽  
Value Of Information

Integrating Blockchain Platforms With Big Data Solutions for Regional Innovation Development

2020 ◽  
pp. 175-186
Author(s):  
Leyla Ayvarovna Gamidullaeva ◽  
Vardan Mkrttchian ◽  
Alexey Finogeev
Keyword(s):  
Big Data ◽  
Intellectual Property ◽  
Intellectual Property Rights ◽  
Third Party ◽  
Smart Contracts ◽  
Economic Activities ◽  
Regional Innovation ◽  
Innovation Development ◽  
Distributed Transaction ◽  
Main Component

The chapter discusses the creation of a mechanism for ensuring reliable and secure interaction among participants in regional innovation systems based on the establishment of smart contracts in the blockchain. The technology allows to reduce the possibility of fraud by dishonest participants, as well as to exclude the need for a third party by transferring its functions to a smart contract. This is important for ensuring confidential and transparent relations between participants in innovative projects, as well as with interested subjects of social and economic activities in the regions. The Ethereum blockchain platform was chosen to create smart contracts. On its basis, there were developed components to perform transactions in contracting, creating, and implementing innovations, transferring intellectual property rights, using rights and licenses for innovation, etc. The main component of the system is a distributed transaction register with digital copies of innovation objects.

scholarly journals Compelling truth: legal protection of the infosphere against big data spills

2016 ◽  
Vol 374 (2083) ◽  
pp. 20160114
Author(s):  
Burkhard Schafer
Keyword(s):  
Big Data ◽  
Intellectual Property ◽  
Property Rights ◽  
Intellectual Property Rights ◽  
Natural Environment ◽  
Data Science ◽  
Legal Protection ◽  
Data Breach ◽  
Luciano Floridi ◽  
Informational Environment

The paper explores whether legal and ethical concepts that have been used to protect the natural environment can also be leveraged to protect the ‘infosphere’, a neologism used by Luciano Floridi to characterize the totality of the informational environment. We focus, in particular, on the interaction between allocation of (intellectual) property rights and ‘communication duties’, in particular, data breach notification duties. This article is part of the themed issue ‘The ethical impact of data science’.

scholarly journals Preliminary assessment of the pragmatic value of information in the classification problem based on deep neural networks

2021 ◽  
Vol 16 (93) ◽  
pp. 9-20
Author(s):  
Valery P. Meshalkin ◽  
◽  
Maxim I. Dli ◽  
Andrey Yu. Puchkov ◽  
Ekaterina I. Lobaneva ◽  
...  
Keyword(s):  
Big Data ◽  
Random Forest ◽  
Data Processing ◽  
Value Of Information ◽  
Learning Algorithm ◽  
The State ◽  
Preliminary Assessment ◽  
Processing Scheme ◽  
Input Information ◽  
Controlled Object

A method is proposed for preliminary assessment of the pragmatic value of information in the problem of classifying the state of an object based on deep recurrent networks of long short-term memory. The purpose of the study is to develop a method for predicting the state of a controlled object while minimizing the number of used prognostic parameters through a preliminary assessment of the pragmatic value of information. This is an especially urgent task under conditions of processing big data, characterized not only by significant volumes of incoming information, but also by information rate and multiformatness. The generation of big data is now happening in almost all areas of activity due to the widespread introduction of the Internet of Things in them. The method is implemented by a two-level scheme for processing input information. At the first level, a Random Forest machine learning algorithm is used, which has significantly fewer adjustable parameters than a recurrent neural network used at the second level for the final and more accurate classification of the state of the controlled object or process. The choice of Random Forest is due to its ability to assess the importance of variables in regression and classification problems. This is used in determining the pragmatic value of the input information at the first level of the data processing scheme. For this purpose, a parameter is selected that reflects the specified value in some sense, and based on the ranking of the input variables by the level of importance, they are selected to form training datasets for the recurrent network. The algorithm of the proposed data processing method with a preliminary assessment of the pragmatic value of information is implemented in a program in the MatLAB language, and it has shown its efficiency in an experiment on model data.

Participatory Boundaries

2018 ◽  
pp. 105-136
Author(s):  
Nancy K. Baym
Keyword(s):  
Big Data ◽  
Intellectual Property ◽  
Property Law ◽  
Intellectual Property Law ◽  
Labor Practices ◽  
Fan Clubs

How do musicians deal with audiences who are organized into gift cultures online? This chapter explores the tensions they experience between wanting and needing to control audiences and recognizing music’s value as a participatory experience. It identifies three strategies of control (territorializing through fan clubs and contests, invoking intellectual property law, and datafying with big data) and two strategies of participation (accepting autonomy and letting them help through fan labor practices like fan funding and promotion). It identifies the challenges with both control and participation, arguing that in a market context, musicians cannot give themselves over fully to participation.

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