„From Big Data to Smart Knowledge – Text and Data Mining in Science and Economy“ (Köln, 23.–24. Februar 2015)

Resumen: La Directiva 2019/790 del Parlamento Europeo y del Consejo de 17 de abril de 2019 sobre los derechos de autor y derechos afines en el mercado único digital ha implementado ciertas excepciones sobre la minería de textos y datos. Pese a que, a priori, podría parecer que se ofrece un impulso importante a este tipo de actividades sus efectos en la práctica quedan mitigados por el encorsetamiento de su formulación que, incluso, es susceptible de generar distorsiones competitivas. Este artículo pretende dar una visión sucinta y crítica sobre estas nuevas excepciones y plantear ciertas vías de mejora futura.Palabras clave: Big Data, minería de textos y datos, Internet de las cosas, Inteligencia Artificial, Mercado Único Digital, Directiva 2019/790, excepciones al derecho de autor, “uso justo”, regla de los tres pasos, doctrina de las facilidades esenciales, competencia, innovación.Abstract: Directive 2019/790 of the European Parliament and of the Council of 17 April 2019 on copyright and related rights in the digital single market has implemented certain exceptions on text and data mining. Although these exceptions might seem to provide a significant boost to this type of activities, their effects in practice are mitigated by the tightening of its wording, which is even likely to generate competitive distortions. This article aims to give a succinct and critical review of these new exceptions and to suggest some ways of improvement for the near future.Keywords: Big Data, Text and Data Mining (TDM), IoT, AI, Single Digital Market, Directive 2019/790, copyright limitations, “fair use”, “three-steps doctrine”, esencial facilities doctrine, competition, innovation.

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Challenges and Cloud Computing Environments Towards Big Data

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset207277 ◽

2014 ◽

pp. 203-208

Author(s):

Kiran Kumar S V N Madupu

Keyword(s):

Data Mining ◽

Cloud Computing ◽

Big Data ◽

Technology Development ◽

Computing Environments ◽

Modern Technologies

Big Data has terrific influence on scientific discoveries and also value development. This paper presents approaches in data mining and modern technologies in Big Data. Difficulties of data mining as well as data mining with big data are discussed. Some technology development of data mining as well as data mining with big data are additionally presented.

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Retrieving Information and Discovering Knowledge from Unstructured Data Using Big Data Mining Technique: Heavy Oil Fields Example

10.2523/17805-ms ◽

2014 ◽

Cited By ~ 1

Author(s):

Wenkuang Wu ◽

Xiaoguang Lu ◽

Ben Cox ◽

Guoqiang Li ◽

Lihua Lin ◽

...

Keyword(s):

Data Mining ◽

Big Data ◽

Heavy Oil ◽

Oil Fields ◽

Unstructured Data ◽

Data Mining Technique ◽

Big Data Mining ◽

Mining Technique

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Trends and Opportunities in Health Analytics as a Service and Implications for Use in Low Resource Settings: A Literature Review Abstract (Preprint)

10.2196/preprints.15737 ◽

2019 ◽

Author(s):

Meghana Bastwadkar ◽

Carolyn McGregor ◽

S Balaji

Keyword(s):

Data Mining ◽

Cloud Computing ◽

Big Data ◽

Intensive Care ◽

Literature Review ◽

Health Monitoring ◽

Data Analytics ◽

Neonatal Intensive Care ◽

Big Data Analytics ◽

Healthcare Facilities

BACKGROUND This paper presents a systematic literature review of existing remote health monitoring systems with special reference to neonatal intensive care (NICU). Articles on NICU clinical decision support systems (CDSSs) which used cloud computing and big data analytics were surveyed. OBJECTIVE The aim of this study is to review technologies used to provide NICU CDSS. The literature review highlights the gaps within frameworks providing HAaaS paradigm for big data analytics METHODS Literature searches were performed in Google Scholar, IEEE Digital Library, JMIR Medical Informatics, JMIR Human Factors and JMIR mHealth and only English articles published on and after 2015 were included. The overall search strategy was to retrieve articles that included terms that were related to “health analytics” and “as a service” or “internet of things” / ”IoT” and “neonatal intensive care unit” / ”NICU”. Title and abstracts were reviewed to assess relevance. RESULTS In total, 17 full papers met all criteria and were selected for full review. Results showed that in most cases bedside medical devices like pulse oximeters have been used as the sensor device. Results revealed a great diversity in data acquisition techniques used however in most cases the same physiological data (heart rate, respiratory rate, blood pressure, blood oxygen saturation) was acquired. Results obtained have shown that in most cases data analytics involved data mining classification techniques, fuzzy logic-NICU decision support systems (DSS) etc where as big data analytics involving Artemis cloud data analysis have used CRISP-TDM and STDM temporal data mining technique to support clinical research studies. In most scenarios both real-time and retrospective analytics have been performed. Results reveal that most of the research study has been performed within small and medium sized urban hospitals so there is wide scope for research within rural and remote hospitals with NICU set ups. Results have shown creating a HAaaS approach where data acquisition and data analytics are not tightly coupled remains an open research area. Reviewed articles have described architecture and base technologies for neonatal health monitoring with an IoT approach. CONCLUSIONS The current work supports implementation of the expanded Artemis cloud as a commercial offering to healthcare facilities in Canada and worldwide to provide cloud computing services to critical care. However, no work till date has been completed for low resource setting environment within healthcare facilities in India which results in scope for research. It is observed that all the big data analytics frameworks which have been reviewed in this study have tight coupling of components within the framework, so there is a need for a framework with functional decoupling of components.

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