Big data and Smart data: two interdependent and synergistic digital policies within a virtuous data exploitation loop

Lacam, Jean-Sébastien; Salvetat, David

doi:10.1016/j.hitech.2021.100406

Cited by 9 publications

(12 citation statements)

References 36 publications

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“…The exploitation of intelligent data is conducted via extracting a sample of data previously created by Big Data policy, which is in turn enriched by contributions of Smart Data approach. Therefore, different forms of data management can be synergized to better the performance level [27].…”

Section: Big Datamentioning

confidence: 99%

Big Data—Knowledge Discovery in Production Industry Data Storages—Implementation of Best Practices

2021

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CRISP-DM (cross-industry standard process for data mining) methodology was developed as an intuitive tool for data scientists, to help them with applying Big Data methods in the complex technological environment of Industry 4.0. The review of numerous recent papers and studies uncovered that most of papers focus either on the application of existing methods in case studies, summarizing existing knowledge, or developing new methods for a certain kind of problem. Although all of these types of research are productive and required, we identified a lack of complex best practices for a specific field. Therefore, our goal is to propose best practices for the data analysis in production industry. The foundation of our proposal is based on three main points: the CRISP-DM methodology as the theoretical framework, the literature overview as an expression of current needs and interests in the field of data analysis, and case studies of projects we were directly involved in as a source of real-world experience. The results are presented as lists of the most common problems for selected phases (‘Data Preparation’ and ‘Modelling’), proposal of possible solutions, and diagrams for these phases. These recommendations can help other data scientists avoid certain problems or choose the best way to approach them.

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Section: Big Datamentioning

confidence: 99%

Big Data—Knowledge Discovery in Production Industry Data Storages—Implementation of Best Practices

2021

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“…Big data and artificial intelligence have been used in other scientific activities that provide colour to governance with various scientific disciplines (Lacam & Salvetat, 2021). This process can be used as an instrument from the main base to show whether the policies implemented will be effective or not.…”

Section: Introductionmentioning

confidence: 99%

Big Data and Artificial Intelligence in Policy Making: A Mini-Review Approach

Supriyanto

Saputra

2022

IJASSH

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The digitization era in public affairs is increasingly disrupting Indonesia. Governance in Indonesia is forced to implement aspects of digitalization in its public services. Big data and artificial intelligence have been used in other scientific activities that provide colour to governance with various scientific disciplines. This study discusses the use of big data and artificial intelligence in policymaking in Indonesia by focusing on the ability of policymakers in policymaking. The method used in this paper is qualitative research with a literature study approach. We reviewed articles with related themes as many as 25 articles published in the last five years from ScienceDirect. The result of this research is that the dynamics that exist in the implementation of public services require appropriate and fast decision-making, considering that this is a community demand. Therefore, public leaders need to disrupt themselves in public services so that these services can be served quickly by enriching skills in big data and artificial intelligence. In conclusion, the critical aspect of the public policy decision-making process is similar to that of any other stage in the policymaking process. Like the preceding steps in the public policy process, the decision-making stage differs depending on the nature of the policy subsystems involved and the degree of consensus faced by decision-makers. The presence of big data in the public sector cannot be disputed as an intriguing approach, particularly during the policy formation cycle. Also, big data and artificial intelligence can help public leaders make decisions to deliver the best policies.

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“…Until now, it has been used to optimise production and to ensure quality and safety [ 7 ]; data itself is not useful if it is not used to create value. Today, there are literature debates on how “big” data can become “smart” by transforming the huge quantity of data into strategic knowledge for decision-makers [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

A Search Engine Concept to Improve Food Traceability and Transparency: Preliminary Results

Palocci

Presser²,

Kabza³

et al. 2022

Foods

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In recent years, the digital revolution has involved the agrifood sector. However, the use of the most recent technologies is still limited due to poor data management. The integration, organisation and optimised use of smart data provides the basis for intelligent systems, services, solutions and applications for food chain management. With the purpose of integrating data on food quality, safety, traceability, transparency and authenticity, an EOSC-compatible (European Open Science Cloud) traceability search engine concept for data standardisation, interoperability, knowledge extraction, and data reuse, was developed within the framework of the FNS-Cloud project (GA No. 863059). For the developed model, three specific food supply chains were examined (olive oil, milk, and fishery products) in order to collect, integrate, organise and make available data relating to each step of each chain. For every step of each chain, parameters of interest and parameters of influence—related to nutritional quality, food safety, transparency and authenticity—were identified together with their monitoring systems. The developed model can be very useful for all actors involved in the food supply chain, both to have a quick graphical visualisation of the entire supply chain and for searching, finding and re-using available food data and information.

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Big data and Smart data: two interdependent and synergistic digital policies within a virtuous data exploitation loop

Cited by 9 publications

References 36 publications

Big Data—Knowledge Discovery in Production Industry Data Storages—Implementation of Best Practices

Big Data—Knowledge Discovery in Production Industry Data Storages—Implementation of Best Practices

Big Data and Artificial Intelligence in Policy Making: A Mini-Review Approach

A Search Engine Concept to Improve Food Traceability and Transparency: Preliminary Results

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