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Future Internet
Special Issues
Open Data and Artificial Intelligence
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Open Data and Artificial Intelligence

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Big Data and Augmented Intelligence".

Deadline for manuscript submissions: closed (20 September 2021) | Viewed by 9882

Special Issue Editor

Prof. Dr. Haklae Kim

E-Mail Website
Guest Editor
Department of Library and Information Science, Chung-Ang University, Seoul, Korea
Interests: knowledge engineering; open data; data science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Open data are considered the lifeline of artificial intelligence. Wikipedia is a source of important data for text analysis in the field of artificial intelligence, and ImageNet recognizes it as key data for image analysis based on deep learning. High-quality data are essential for implementing artificial intelligence. Governments and enterprises around the world provide large-scale open data to citizens and encourage free use. Recently, open data on COVID-19 have continuously been increasing, and efforts to analyze data and find new alternatives using artificial intelligence technology are also actively underway.

The purpose of this issue is to share research on open data and artificial intelligence technology and to explore new challenges. The main topics include an introduction to various policies, technologies, and standards for activating the use of open data, and applications by using open data and artificial intelligence technologies.

Dr. Haklae Kim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Challenges, barriers, and drivers of AI and open data
  • Open data standardization and quality
  • Open data policy
  • The use of AI technologies and open data
  • Open datasets for artificial intelligence
  • Open-data-driven services and applications (IoT, healthcare, governments, COVID-19)

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Published Papers (2 papers)

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Research

14 pages, 10955 KiB  
Article
Blockchain Implementation Method for Interoperability between CBDCs
by Hyunjun Jung and Dongwon Jeong
Future Internet 2021, 13(5), 133; https://doi.org/10.3390/fi13050133 - 18 May 2021
Cited by 20 | Viewed by 5666
Abstract
Central Bank Digital Currency (CBDC) is a digital currency issued by a central bank. Motivated by the financial crisis and prospect of a cashless society, countries are researching CBDC. Recently, global consideration has been given to paying basic income to avoid consumer sentiment [...] Read more.
Central Bank Digital Currency (CBDC) is a digital currency issued by a central bank. Motivated by the financial crisis and prospect of a cashless society, countries are researching CBDC. Recently, global consideration has been given to paying basic income to avoid consumer sentiment shrinkage and recession due to epidemics. CBDC is coming into the spotlight as the way to manage the public finance policy of nations comprehensively. CBDC is studied by many countries. The bank of the Bahamas released Sand Dollar. Each country’s central bank should consider the situation in which CBDCs are exchanged. The transaction of the CDDB is open data. Transaction registers CBDC exchange information of the central bank in the blockchain. Open data on currency exchange between countries will provide information on the flow of money between countries. This paper proposes a blockchain system and management method based on the ISO/IEC 11179 metadata registry for exchange between CBDCs that records transactions between registered CBDCs. Each country’s CBDC will have a different implementation and time of publication. We implement the blockchain system and experiment with the operation method, measuring the block generation time of blockchains using the proposed method. Full article
(This article belongs to the Special Issue Open Data and Artificial Intelligence)
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9 pages, 1410 KiB  
Article
Development of Knowledge Graph for Data Management Related to Flooding Disasters Using Open Data
by Jiseong Son, Chul-Su Lim, Hyoung-Seop Shim and Ji-Sun Kang
Future Internet 2021, 13(5), 124; https://doi.org/10.3390/fi13050124 - 11 May 2021
Cited by 11 | Viewed by 3620
Abstract
Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we [...] Read more.
Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we must focus on these various data. Disaster data depend on the domain by disaster type and include heterogeneous data and lack interoperability. In particular, in the case of open data related to disasters, there are several issues, where the source and format of data are different because various data are collected by different organizations. Moreover, the vocabularies used for each domain are inconsistent. This study proposes a knowledge graph to resolve the heterogeneity among various disaster data and provide interoperability among domains. Among disaster domains, we describe the knowledge graph for flooding disasters using Korean open datasets and cross-domain knowledge graphs. Furthermore, the proposed knowledge graph is used to assist, solve, and manage disaster problems. Full article
(This article belongs to the Special Issue Open Data and Artificial Intelligence)
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