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More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
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Presentation by Thomas Margoni (Senior Lecturer in Intellectual Property and Internet Law, Co-director, CREATe, University of Glasgow) as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
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Presentation by Jacques Flores Dourojeanni (Research Data Management Consultant Utrecht University Library), as delivered during the OpenAIRE Legal Policy Webinar series on April 29th 2020.
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Presentation by Jacques Flores Dourojeanni (Research Data Management Consultant Utrecht University Library), as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
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Presentation by Prodromos Tsiavos (Senior Legal Advisor - ARC/ Director - Onassis Group) as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
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Presentation by Jacques Flores Dourojeanni (Research Data Management Consultant Utrecht University Library), as delivered during the OpenAIRE Legal Policy Webinar series on April 29th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
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Presentation by Prodromos Tsiavos (Senior Legal Advisor - ARC/ Director - Onassis Group) as delivered during the OpenAIRE Legal Policy Webinar series on April 29th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
20200504_OpenAIRE Legal Policy Webinar: GDPR and Sharing DataOpenAIRE
Presentation by Jacques Flores Dourojeanni (Research Data Management Consultant Utrecht University Library), as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
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Presentation by Prodromos Tsiavos (Senior Legal Advisor - ARC/ Director - Onassis Group) as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
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Links: https://www.cessda.eu/Research-Infrastructure/Training/Expert-Tour-Guide-on-Data-Management
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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Jeff Christiansen Snippet: https://www.youtube.com/watch?v=PV_vuUKRm6w
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data mining privacy concerns ppt presentationiWriteEssays
Data Mining and privacy Presentation
This is a sample presentation on data mining. The presetation looks at the critical Issues In Data Mining: Privacy, National Security And Personal Liberty Implications Of Data Mining
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Full Webinar: https://youtu.be/FSlA1noJ1VU
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Webinar: https://www.youtube.com/watch?v=pwtlr7BtdQU
Full Webinar: https://youtu.be/FSlA1noJ1VU
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General Data Protection Regulation comes into force across the EU on May 25, 2018. Investment fund complexes, distributors, fund administrators and depositaries with global reach will need to consider their controls and processes as they relate to personal data.
Our experts offer invaluable insight on:
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- Practical guidance on “operationalizing” GDPR principles
How problems with data protection affect science researchers, especially when sharing large datasets with researchers around the globe: issues and solutions?
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Who is it for?: Researchers, Data Managers, General public.
OpenAIRE webinars during OA week 2017: Legal aspects of Open Science (Thomas ...OpenAIRE
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Presented in Beijing on 25 March 2009.A l
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SWOT of Bigdata Security Using Machine Learning Techniquesijistjournal
This paper gives complete guidelines on BigData, Different Views of BigData, etc.How the BigData is useful to us and what are the factors affecting BigData all the things are covered under this paper. The paper also contains the BigData Machine learning techniques and how the Hadoop comes into the picture. It also contains the what is importance of BigData security. The paper mostly covers all the main point that affect Big Data and Machine Learning.
The aim of the webinar is to introduce the audience, in particular non-lawyers, to the legal framework of text and data mining, focusing on the main aspects of the law at the European level.
A Dynamic Intelligent Policies Analysis Mechanism for Personal Data Processin...Konstantinos Demertzis
The evolution of the Internet of Things is significantly a
ected by legal restrictions imposed for personal data handling, such as the European General Data Protection Regulation (GDPR).
The main purpose of this regulation is to provide people in the digital age greater control over their personal data, with their freely given, specific, informed and unambiguous consent to collect and process the data concerning them. ADVOCATE is an advanced framework that fully complies with the requirements of GDPR, which, with the extensive use of blockchain and artificial intelligence technologies, aims to provide an environment that will support users in maintaining control of their personal data in the IoT ecosystem. This paper proposes and presents the Intelligent Policies Analysis Mechanism (IPAM) of the ADVOCATE framework, which, in an intelligent and fully automated manner, can identify conflicting rules or consents of the user, which may lead to the collection of personal data that can be used for profiling. In order to clearly identify and implement IPAM, the problem of recording user data from smart entertainment devices using Fuzzy Cognitive Maps (FCMs) was simulated. FCMs are an intelligent decision-making system that simulates the processes of a complex system, modeling the correlation base, knowing the behavioral and balance specialists of the system. Respectively, identifying conflicting rules that can lead to a profile, training is done using Extreme Learning Machines (ELMs), which are highly ecient neural systems of small and flexible architecture that can work optimally in complex environments.
An itinerary for FAIR and privacy respecting data-driven innovation and researchMarlon Domingus
My talk for the National eScience Symposium 2017 in the Internet of Things track, October 12 2017.
TALK: An itinerary for FAIR and privacy respecting data-driven innovation and research
ABSTRACT: The big picture of the complex landscape of e-science, technology, legal and ethical responsibilities addressed. How to apply privacy values and responsibilities to new technological platforms like the IoT? Can we find an approach that ensures a high level of privacy protection and at the same time supports the interest of researchers and increase innovation? A practical recap of the most important recommendations for researchers creating collaborations and infrastructures.
New statutory limitation for Text Data Mining - a Pyrrhic victory? | www.euda...EUDAT
| www.eudat.eu | v1.0, July 2014 - Where does the text data mining sit in the copyright limitations system? What is the rationale behind copyright limitations? What are the limitations in international and EU law? This module addresses such questions. Download the presentation and find out.
Who is it for?: Researchers, Data Managers, General public.
GDPR regulations are little over a year away and there are still many questions to be answered for IT. think S3 working with leading technology vendors are answering these questions and leading the way to compliance of IT environments. If you have questions regarding GDPR or want to assess if you are ready for GDPR we can help.
The Survey of Data Mining Applications And Feature Scope IJCSEIT Journal
In this paper we have focused a variety of techniques, approaches and different areas of the research which
are helpful and marked as the important field of data mining Technologies. As we are aware that many MNC’s
and large organizations are operated in different places of the different countries. Each place of operation
may generate large volumes of data. Corporate decision makers require access from all such sources and
take strategic decisions .The data warehouse is used in the significant business value by improving the
effectiveness of managerial decision-making. In an uncertain and highly competitive business
environment, the value of strategic information systems such as these are easily recognized however in
today’s business environment, efficiency or speed is not the only key for competitiveness. This type of huge
amount of data’s are available in the form of tera- to peta-bytes which has drastically changed in the areas
of science and engineering. To analyze, manage and make a decision of such type of huge amount of data
we need techniques called the data mining which will transforming in many fields. This paper imparts more
number of applications of the data mining and also o focuses scope of the data mining which will helpful in
the further research.
A SURVEY ON PRIVACY PRESERVING ASSOCIATION RULE MININGijdkp
Businesses share data, outsourcing for specific business problems. Large companies stake a large part of
their business on analysis of private data. Consulting firms often handle sensitive third party data as part of
client projects. Organizations face great risks while sharing their data. Most of this sharing takes place with
little secrecy. It also increases the legal responsibility of the parties involved in the process. So, it is crucial to
reliably protect their data due to legal and customer concerns. In this paper, a review of the state-of-the-art
methods for privacy preservation is presented. It also analyzes the techniques for privacy preserving
association rule mining and points out their merits and demerits. Finally the challenges and directions for
future research are discussed.
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sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Nutraceutical market, scope and growth: Herbal drug technology
20200429_Data, Data Ownership and Open Science
1. Data, Data Ownership and Open
Science
OpenAIRE Legal Policy Webinars
29 April 2020
Dr. Thomas Margoni
Senior Lecturer in Intellectual Property and Internet Law
Co-director, CREATe
Coordinator, IP LLM Programme
School of Law – CREATe
University of Glasgow
www.create.ac.uk
thomas.margoni@glasgow.ac.uk
2. Example: OpenMinTeD
Copyright theory (and sometimes copyright law) says: no
E.g.: ideas, procedures, methods of operation, mathematical concepts, etc are
not protected by copyright law, only original expressions which constitute
intellectual creations (e.g. Arts. 2 WCT, 9(2) TRIPs, Art. 2 Berne and most
legal traditions requiring originality). Factual information and data as such fail
to qualify for copyright protection.
Other areas of law may say yes, but usually in specifically identified
situations, or with limited remedies e.g.:
1) Trade secrets, confidentiality (only if secret and limited remedies)
2) Contracts (privity, enforceability and remedies)
3) Data protection (only qualifying data and scope is protection)
4) PSI (reuse by default)
5) …
thomas.margoni@glasgow.ac.uk
Is data owned?
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
3. Example: OpenMinTeD
Databases: Are protected by copyright if the selection or arrangement is
original. However, what is protected in this case is the selection or
arrangement (e.g. the structure of the database), not the contained data.
● This means that if the original database is composed of copyright
protected elements (e.g. a DB of journal articles, films, songs, etc) the
content of the DB is protected NOT because is data, but because they
are works of authorship in their own right.
● If the original database is composed of non protected information (e.g.
temperature measurements, numbers or other factual information), the
copyright protecting the structure does NOT extend to the underlying
data, which remains free to reuse from a copyright point of view (but you
should always verify this is not personal or confidential data, etc.).
thomas.margoni@glasgow.ac.uk
Is data owned?
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
4. Example: OpenMinTeD
Databases: In the EU, non original databases are also protected (heard of the
SGDR?). In this case, a database whose making required a substantial
investment in obtaining, verifying or presenting (NOT creating) the data is
protected by Sui Generis Database Right (SGDR, a “lighter” form of
copyright), therefore effectively protecting obtained (but not created) data.
Copyright and SGDR are cumulable, so an original database (structure)
whose making required a substantial investment may enjoy a double form of
protection. If the “data” are in fact works (a database of journal articles) there
are 3 layers of rights protecting that database. All of them have to be properly
authorised if you want to reuse that database (e.g. this is way it is important to
use the right licence, e.g. CC BY 4.0).
thomas.margoni@glasgow.ac.uk
Is data owned?
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
5. Example: OpenMinTeD
What about the “data” contained in a work (not in a database)? Can you
extract statistical information about the English language from, e.g. a Harry
Potter novel?
In theory yes (the right to read is the right to mine), but in practice no (you
need a TDM exception).
If we take a closer look, EU copyright law (doesn’t say anything explicit
but) often means: YES.
Interplay between Arts. 2 and 5 InfoSoc Directive requires to obtain an
authorisation for data capturing/extraction + SGDR.
thomas.margoni@glasgow.ac.uk
Is data owned?
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
6. Example: OpenMinTeD
Modern data analytics (e.g. TDM, machine learning etc.) normally extracts principles,
facts, data, correlations, etc, which copyright theory stipulates that are not protected,
thus the extraction of those unprotected elements from protected works should not
need an exception (non consumptive uses).
Main obstacle of EU copyright framework is that it harmonised rights broadly
(reproduction, redistribution, communication to the public, etc), but did not do the same
with exceptions (exhaustive but not mandatory list, narrow interpretation, etc). There is
no flexible standard in the EU such as there are in many other countries around the
world.
Result: Often data contained in works are de facto or de jure (for non original
databases) protected (needs authorisation) in the EU but may not abroad.
thomas.margoni@glasgow.ac.uk
Is data owned?
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
7. Example: OpenMinTeD
By excluding protection of ideas, principles, factual information, non original
expressions the law’s goal is avoid the creation of monopolies over the
information needed by everyone to think, communication and create new
knowledge and to avoid the distortion of scientific freedoms and fundamental
rights that it may cause.
By excluding data created in databases the law’s goal is to avoid as much as
possible so-called “single source databases” due to their anti-competitive and
monopolistic nature.
Ideas and data as such are the basic bricks of human knowledge and should
not be owned but held in the public domain for everyone to have access to it,
but also to verify, reuse and replicate.
By affording protection to the obtaining of data structured in qualifying
databases against substantial extractions a limited reward for the investment
is given to the maker under EU law.
thomas.margoni@glasgow.ac.uk
Is data owned
and why does it matter for OS?
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
8. Example: OpenMinTeD
1) Text and Data mining: computational analysis of anything recorded in the
work (sec. 29A CDPA) or any automated analytical technique aiming to
analyse text and data in digital form in order to generate information such as
patterns, trends and correlations (Art. 3 CDSM);
2) Scope: exception to the right of reproduction (both);
3) Beneficiaries: Non commercial research (29A CDPA), research
organisations with lawful access for research purposes (Art. 3 CDSM), anyone
for any purpose but can be opted-out (Art. 4 CDSM).
4) Relationship to contracts: Cannot be limited by contract (except for Art. 4
CDSM).
5) Relationship to technology: Can be limited by technological measures
(integrity measures and TPM)
thomas.margoni@glasgow.ac.uk
Example: TDM exceptions
thomas.margoni@glasgow.ac.uk
9. Example: OpenMinTeD
OpenAIRE has 3 published guides for researchers at the moment:
● How do I know if my research data is protected?
https://www.openaire.eu/how-do-i-know-if-my-research-data-is-protected
● How do I license my research data?
https://www.openaire.eu/how-do-i-license-my-research-data
● Can I reuse someone else’s research data?
https://www.openaire.eu/can-i-reuse-someone-else-research-data
And a companion guide to help address open science issue for repositories:
● Making your repository Open
https://www.openaire.eu/making-your-repository-open
CREATe Open Science resource:
● https://www.create.ac.uk/open-science/
thomas.margoni@glasgow.ac.uk
Guides
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
10. Example: OpenMinTeD
● Open Access: Everything under CC BY 4.0/CC0 (or similar) can be copied,
reused, redistributed and mined (e.g. Wikipedia, www.copyrightuser.org) for any
purpose
● OpenCovidPledge: “to make our intellectual property available free of charge
for use in ending the COVID-19 pandemic”: www.opencovidpledge.org with
companies such as Amazon, Facebook, Hewlett Packard Enterprise, IBM,
Microsoft declaring adoption of either or both licenses.
● Wellcome statement on ‘Sharing research data and findings relevant to the
novel coronavirus (COVID-19) outbreak’:
https://wellcome.ac.uk/press-release/sharing-research-data-and-findings-relevan
t-novel-coronavirus-covid-19-outbreak
● Joint Comment to WIPO on Copyright and Artificial Intelligence,
http://infojustice.org/archives/42009#members
thomas.margoni@glasgow.ac.uk
Recent initiatives
thomas.margoni@glasgow.ac.ukthomas.margoni@glasgow.ac.uk
11. Open Access Week 2019
Thank you!
Dr. Thomas Margoni
Senior Lecturer in Intellectual Property and Internet Law
Co-director, CREATe
Director, IP LLM Programme
School of Law – CREATe
University of Glasgow
www.create.ac.uk
thomas.margoni@glasgow.ac.uk