This is a presentation used to deliver an invited talk for Babu Banarasi Das University (BBDU, Department of Computer Science and Engineering) Development Program «Artificial Intelligence for Sustainable Development» organized by AI Research Centre, Department of Computer Science & Engineering, ShodhGuru Research Labs, Soft Computing Research Society, IEEE UP Section, Computational Intelligence Society Chapter in 2022. Read more here -> https://anastasijanikiforova.com/2022/09/24/ai-for-open-data-or-open-data-for-ai-an-invited-talk-for-bbdu-development-program-artificial-intelligence-for-sustainable-development%f0%9f%8e%a4/
The role of open data in the development of sustainable smart cities and smar...Anastasija Nikiforova
This presentation is a supplementary material for the guest lecture "The role of open data in the development of sustainable smart cities and smart society" I delivered for the Federal University of Technology – Paraná (Universidade Tecnológica Federal do Paraná (UTFPR)) (Brazil, May 2022).
An overview of current Open Data activities and approaches and our own approach to manage and develop Open Data projects using Linked Data as the technical piece for the best results in the long run. Prepared for ICT 2010, http://ec.europa.eu/information_society/events/cf/ict2010/item-display.cfm?id=2790
Presentation given at the conference "open data for impact"
Erasmus+ project "Public Makers"
https://www.linkedin.com/posts/wide-luxembourg_opendata-publicmakers-activity-6818166878473596928-7ImU/
Digital Leadership Interview : Gavin Starks, CEO of the Open Data Institute (...Capgemini
"Large organizations should think about releasing their data and rely on third parties to innovate on their behalf rather than trying to innovate internally."
Presentation on Open Government Data Tools and Infrastructure for Citizen Engagement at the WSIS Forum, May 2012 in Geneva Switzerland.
See: http://groups.itu.int/wsis-forum2012/Agenda/DraftAgenda.aspx?se=43276
Day 2: Openness: making use of open data, Mr. Peter Reichstädter, CIO, Parlia...wepc2016
At first, it was assumed that if parliaments made their data available, people would come and get it. More recently, it has become clear that there is still much to do to make open data “profitable” and usable in a constant and reliable way. The session will also question parliament’s ability to access and use data from the executive branch of government and elsewhere in its own research activities.
Invited talk "Open Data as a driver of Society 5.0: how you and your scientif...Anastasija Nikiforova
This presentation is prepared as a part of my talk on the openness (open data and open science) in the context of Society 5.0 during the International Conference and Expo on Nanotechnology and Nanomaterials. It was very pleasant to receive an invitation to deliver the talk on my recently published article Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough? (Sensors 2021, 21(15), 5204), which I have entitled as “Open Data as a driver of Society 5.0: how you and your scientific outputs can contribute to the development of the Super Smart Society and transformation into Smart Living?“. The paper has been briefly discussed in my previous post, thus, just a few words on this talk and overall experience.
The role of open data in the development of sustainable smart cities and smar...Anastasija Nikiforova
This presentation is a supplementary material for the guest lecture "The role of open data in the development of sustainable smart cities and smart society" I delivered for the Federal University of Technology – Paraná (Universidade Tecnológica Federal do Paraná (UTFPR)) (Brazil, May 2022).
An overview of current Open Data activities and approaches and our own approach to manage and develop Open Data projects using Linked Data as the technical piece for the best results in the long run. Prepared for ICT 2010, http://ec.europa.eu/information_society/events/cf/ict2010/item-display.cfm?id=2790
Presentation given at the conference "open data for impact"
Erasmus+ project "Public Makers"
https://www.linkedin.com/posts/wide-luxembourg_opendata-publicmakers-activity-6818166878473596928-7ImU/
Digital Leadership Interview : Gavin Starks, CEO of the Open Data Institute (...Capgemini
"Large organizations should think about releasing their data and rely on third parties to innovate on their behalf rather than trying to innovate internally."
Presentation on Open Government Data Tools and Infrastructure for Citizen Engagement at the WSIS Forum, May 2012 in Geneva Switzerland.
See: http://groups.itu.int/wsis-forum2012/Agenda/DraftAgenda.aspx?se=43276
Day 2: Openness: making use of open data, Mr. Peter Reichstädter, CIO, Parlia...wepc2016
At first, it was assumed that if parliaments made their data available, people would come and get it. More recently, it has become clear that there is still much to do to make open data “profitable” and usable in a constant and reliable way. The session will also question parliament’s ability to access and use data from the executive branch of government and elsewhere in its own research activities.
Invited talk "Open Data as a driver of Society 5.0: how you and your scientif...Anastasija Nikiforova
This presentation is prepared as a part of my talk on the openness (open data and open science) in the context of Society 5.0 during the International Conference and Expo on Nanotechnology and Nanomaterials. It was very pleasant to receive an invitation to deliver the talk on my recently published article Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough? (Sensors 2021, 21(15), 5204), which I have entitled as “Open Data as a driver of Society 5.0: how you and your scientific outputs can contribute to the development of the Super Smart Society and transformation into Smart Living?“. The paper has been briefly discussed in my previous post, thus, just a few words on this talk and overall experience.
This report coordinated by Nesta and commissioned by the European Commission, DG CONNECT is the first systematic network analysis of the emerging digital social innovation (DSI) ecosystem in Europe.
OGPL is a joint product from India and United States to promote transparency and greater citizen engagement by making more government data, documents, tools and processes publicly available.
EDF2014: Kush Wadhwa, Senior Partner, Trilateral Research & Consulting: Addre...European Data Forum
Selected Talk by Kush Wadhwa, Senior Partner, Trilateral Research & Consulting at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Addressing risks and opportunities engendered by big data: The BYTE project
Von Open Data zu Linked Open Data, M. Kaltenböck, SWCMartin Kaltenböck
Präsentation von Martin Kaltenböck, Semantic Web Company am 28.11. 2011 bei der AGEO Jahresveranstaltung 2011 über den Weg von Open Data (Offenen Daten) zu Linked Open Data (Vernetzten offenen Daten), sowie über das Potential und die Vorteile von Linked Open Data (LOD) im Bereich von Offenen Regierungsdaten (Open Government Data- OGD).
This talk reviews the foundations of Open Data and provides insight into the implementation and economic benefits by reviewing existing initiatives and lessons learned, as well as emerging models.
Presentation at the Nordic Data Journalism Conference 2016 in Helsinki, Finland about the Global Goals for Sustainable Development and the need of a Data Revolution that includes using Open Data and Responsible Data practices. Notes can be found on http://bit.ly/noda16-pernillan
Data Quality for AI or AI for Data quality: advances in Data Quality Manageme...Anastasija Nikiforova
“Data is the new oil” is only partly true, since according to Forbes, data is more than oil, while according to Ataccama, “Manual Data Quality Doesn’t Cut It in 2023” – this was the main driver behind of my guest lecture entitled “Data Quality for AI or AI for Data quality: advances in Data Quality Management for the success and sustainability of emerging technologies, business and society”, as part of which we discussed what is the role of artificial intelligence in data quality management and what is the role of data quality for AI, concluding that it is not about “data quality for AI” OR “AI for data quality” but rather about AND.
We also looked at what is the current market offer regarding AI-driven data quality management, what are the pros and cons of these solutions and what are the prerequisites that we have to take into account when using them (e.g., metadata and their quality for those, which derive DQ rules based on metadata analysis), and how possibly more promising solution could be built.
We also looked at what are those data quality specificities we should consider depending on the artifact – a data object (dataset), whose owner is known / is unknown (open data), Information System, Data Warehouse, Data Lake, Data Lakehouse, Data Mesh – where, when and how DQ takes place in them? What are the current trends? And are these indeed trends or rather hype?
Towards High-Value Datasets determination for data-driven development: a syst...Anastasija Nikiforova
Slides for the talk delivered as part of EGOV-CeDEM-ePart 2023 (EGOV2023) conference, aimed at examining how HVD determination has been reflected in the literature over the years and what has been found by these studies to date, incl. the indicators used in them, involved stakeholders, data-related aspects, and frameworks, which was done by conducting a Systematic Literature Review.
Read the paper here -> https://link.springer.com/chapter/10.1007/978-3-031-41138-0_14
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This report coordinated by Nesta and commissioned by the European Commission, DG CONNECT is the first systematic network analysis of the emerging digital social innovation (DSI) ecosystem in Europe.
OGPL is a joint product from India and United States to promote transparency and greater citizen engagement by making more government data, documents, tools and processes publicly available.
EDF2014: Kush Wadhwa, Senior Partner, Trilateral Research & Consulting: Addre...European Data Forum
Selected Talk by Kush Wadhwa, Senior Partner, Trilateral Research & Consulting at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Addressing risks and opportunities engendered by big data: The BYTE project
Von Open Data zu Linked Open Data, M. Kaltenböck, SWCMartin Kaltenböck
Präsentation von Martin Kaltenböck, Semantic Web Company am 28.11. 2011 bei der AGEO Jahresveranstaltung 2011 über den Weg von Open Data (Offenen Daten) zu Linked Open Data (Vernetzten offenen Daten), sowie über das Potential und die Vorteile von Linked Open Data (LOD) im Bereich von Offenen Regierungsdaten (Open Government Data- OGD).
This talk reviews the foundations of Open Data and provides insight into the implementation and economic benefits by reviewing existing initiatives and lessons learned, as well as emerging models.
Presentation at the Nordic Data Journalism Conference 2016 in Helsinki, Finland about the Global Goals for Sustainable Development and the need of a Data Revolution that includes using Open Data and Responsible Data practices. Notes can be found on http://bit.ly/noda16-pernillan
Data Quality for AI or AI for Data quality: advances in Data Quality Manageme...Anastasija Nikiforova
“Data is the new oil” is only partly true, since according to Forbes, data is more than oil, while according to Ataccama, “Manual Data Quality Doesn’t Cut It in 2023” – this was the main driver behind of my guest lecture entitled “Data Quality for AI or AI for Data quality: advances in Data Quality Management for the success and sustainability of emerging technologies, business and society”, as part of which we discussed what is the role of artificial intelligence in data quality management and what is the role of data quality for AI, concluding that it is not about “data quality for AI” OR “AI for data quality” but rather about AND.
We also looked at what is the current market offer regarding AI-driven data quality management, what are the pros and cons of these solutions and what are the prerequisites that we have to take into account when using them (e.g., metadata and their quality for those, which derive DQ rules based on metadata analysis), and how possibly more promising solution could be built.
We also looked at what are those data quality specificities we should consider depending on the artifact – a data object (dataset), whose owner is known / is unknown (open data), Information System, Data Warehouse, Data Lake, Data Lakehouse, Data Mesh – where, when and how DQ takes place in them? What are the current trends? And are these indeed trends or rather hype?
Towards High-Value Datasets determination for data-driven development: a syst...Anastasija Nikiforova
Slides for the talk delivered as part of EGOV-CeDEM-ePart 2023 (EGOV2023) conference, aimed at examining how HVD determination has been reflected in the literature over the years and what has been found by these studies to date, incl. the indicators used in them, involved stakeholders, data-related aspects, and frameworks, which was done by conducting a Systematic Literature Review.
Read the paper here -> https://link.springer.com/chapter/10.1007/978-3-031-41138-0_14
Public data ecosystems in and for smart cities: how to make open / Big / smar...Anastasija Nikiforova
This is a set of slides used as part of my keynote "Public data ecosystems in and for smart cities: how to make open / Big / smart / geo data ecosystems value-adding for SDG-compliant Smart Living and Society 5.0" delivered at the 5th International Conference on Advanced Research Methods and Analytics (CARMA 2023) -> https://carmaconf2023.wordpress.com/keynote-speakers/. read more here -> https://anastasijanikiforova.com/2023/06/30/keynote-at-the-5th-international-conference-on-advanced-research-methods-and-analytics-carma-2023/
Overlooked aspects of data governance: workflow framework for enterprise data...Anastasija Nikiforova
This presentation is a supplementary material for the article "Overlooked aspects of data governance: workflow framework for enterprise data deduplication" (Azeroual, Nikiforova, Shei) presented at The International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS2023).
Abstract of the paper: Data quality in companies is decisive and critical to the benefits their products and services can provide. However, in heterogeneous IT infrastructures where, e.g., different applications for Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), product management, manufacturing, and marketing are used, duplicates, e.g., multiple entries for the same customer or product in a database or information system, occur. There can be several reasons for this, but the result of non-unique or duplicate records is a degraded data quality. This ultimately leads to poorer, inefficient, and inaccurate data-driven decisions. For this reason, in this paper, we develop a conceptual data governance framework for effective and efficient management of duplicate data, and improvement of data accuracy and consistency in large data ecosystems. We present methods and recommendations for companies to deal with duplicate data in a meaningful way.
Data Quality as a prerequisite for you business success: when should I start ...Anastasija Nikiforova
These are slides for my talk "Data Quality as a prerequisite for you business success: when should I start taking care of it?" I delivered as an invited keynote for HackCodeX Forum that gathered international experts to share their experience and knowledge on the emerging technologies and areas such as Artificial Intelligence, Security, Data Quality, Quantum Computing, Sustainability, Open Data, Privacy etc.
Framework for understanding quantum computing use cases from a multidisciplin...Anastasija Nikiforova
This presentation is a supplementary material for the article "Framework for understanding quantum computing use cases from a multidisciplinary perspective and future research directions" (Ukpabi, D.C., Karjaluoto, H., Botticher, A., Nikiforova, A., Petrescu, D.I., Schindler, P., Valtenbergs, V., Lehmann, L., & Yakaryılmaz, A) available at https://arxiv.org/ftp/arxiv/papers/2212/2212.13909.pdf. THe presentation, however, was delivered for QWorld Quantum Science Days 2023 | May 29-31.
Data Lake or Data Warehouse? Data Cleaning or Data Wrangling? How to Ensure t...Anastasija Nikiforova
This presentation was delivered as part of the Data Science Seminar titled “When, Why and How? The Importance of Business Intelligence“ organized by the Institute of Computer Science (University of Tartu) in cooperation with Swedbank.
In this presentation I talked about:
*“Data warehouse vs. data lake – what are they and what is the difference between them?” (structured vs unstructured, static vs dynamic (real-time data), schema-on-write vs schema on-read, ETL vs ELT) with further elaboration on What are their goals and purposes? What is their target audience? What are their pros and cons?
*“Is the Data warehouse the only data repository suitable for BI?” – no, (today) data lakes can also be suitable. And even more, both are considered the key to “a single version of the truth”. Although, if descriptive BI is the only purpose, it might still be better to stay within data warehouse. But, if you want to either have predictive BI or use your data for ML (or do not have a specific idea on how you want to use the data, but want to be able to explore your data effectively and efficiently), you know that a data warehouse might not be the best option.
*“So, the data lake will save my resources a lot, because I do not have to worry about how to store /allocate the data – just put it in one storage and voila?!” – no, in this case your data lake will turn into a data swamp! And you are forgetting about the data quality you should (must!) be thinking of!
*“But how do you prevent the data lake from becoming a data swamp?” – in short and simple terms – proper data governance & metadata management is the answer (but not as easy as it sounds – do not forget about your data engineer and be friendly with him [always… literally always :D) and also think about the culture in your organization.
*“So, the use of a data warehouse is the key to high quality data?” – no, it is not! Having ETL do not guarantee the quality of your data (transform&load is not data quality management). Think about data quality regardless of the repository!
*“Are data warehouses and data lakes the only options to consider or are we missing something?“– true! Data lakehouse!
*“If a data lakehouse is a combination of benefits of a data warehouse and data lake, is it a silver bullet?“– no, it is not! This is another option (relatively immature) to consider that may be the best bit for you, but not a panacea. Dealing with data is not easy (still)…
In addition, in this talk I also briefly introduced the ongoing research into the integration of the data lake as a data repository and data wrangling seeking for an increased data quality in IS. In short, this is somewhat like an improved data lakehouse, where we emphasize the need of data governance and data wrangling to be integrated to really get the benefits that the data lakehouses promise (although we still call it a data lake, since a data lakehouse is nut sufficiently mature concept with different definitions of it).
Putting FAIR Principles in the Context of Research Information: FAIRness for ...Anastasija Nikiforova
This presentation is a supplementary material for "Putting FAIR Principles in the Context of Research Information: FAIRness for CRIS and CRIS for FAIRness" (Otmane Azeroual, Joachim Schopfel, Janne Polonen, and Anastasija Nikiforova) paper presented at 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K) conference, and also received the Best Paper Award. In this presentation we raise a discussion on this topic showing that the improvement of FAIRness is a dual or bidirectional process, where CRIS promotes and contributes to the FAIRness of data and infrastructures, and FAIR principles push for further improvement in the underlying CRIS data model and format, positively affecting the sustainability of these systems and underlying artifacts. CRIS are beneficial for FAIR, and FAIR is beneficial for CRIS.
See the text here -> https://www.scitepress.org/Link.aspx?doi=10.5220/0011548700003335
Cite as -> Azeroual, O.; Schöpfel, J.; Pölönen, J. and Nikiforova, A. (2022). Putting FAIR Principles in the Context of Research Information: FAIRness for CRIS and CRIS for FAIRness. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KMIS, ISBN 978-989-758-614-9; ISSN 2184-3228, pages 63-71. DOI: 10.5220/0011548700003335
Open data hackathon as a tool for increased engagement of Generation Z: to h...Anastasija Nikiforova
This is presentation for the paper "Open data hackathon as a tool for increased engagement of Generation Z: to hack or not to hack?" presented at EGETC2022.
A hackathon is known as a form of civic innovation in which participants representing citizens can point out existing problems or social needs and propose a solution. Given the high social, technical, and economic potential of open government data (OGD), the concept of open data hackathons is becoming popular around the world. This concept has become popular in Latvia with the annual hackathons organised for a specific cluster of citizens – Generation Z. This study presents the latest findings on the role of open data hackathons and the benefits that they can bring to both the society, participants, and government. First, a systematic literature review is carried out to establish a knowledge base. Then, empirical research of 4 case studies of open data hackathons for Generation Z participants held between 2018 and 2021 in Latvia is conducted to understand which ideas dominated and what were the main results of these events for the OGD initiative. It demonstrates that, despite the widespread belief that young people are indifferent to current
societal and natural problems, the ideas developed correspond to current situation and are aimed at solving them, revealing aspects for improvement in both the
provision of data, infrastructure, culture, and government- related areas.
Barriers to Openly Sharing Government Data: Towards an Open Data-adapted Inno...Anastasija Nikiforova
This is the presentation for our ongoing study "Barriers to Openly Sharing Government Data: Towards an Open Data-adapted Innovation Resistance Theory" (Anastasija Nikiforova, Anneke Zuiderwijk) presented at ICEGOV2022 conference – 15th International Conference on Theory and Practice of Electronic Governance (nominated to the Best Paper Awards).
In short, the study aims to develop an Open Government Data-adapted Innovation Resistance Theory model to empirically identify predictors affecting public agencies’ resistance to openly sharing government data. Here we want to understand:
💡what are functional and behavioural factors that facilitate or hamper opening government data by public organizations?
💡does IRT provide a new and more complete insight compared to more traditional UTAUT and TAM? – IRT has not been applied in this domain, yet, so we are checking whether it should be considered, or rather those models we are familiar so much are the best ones?
💡and additionally – does the COVID-19 pandemic had an [obvious/significant] effect on the public agencies in terms of their readiness or resistance to openly share government data?
Based on a review of the literature on both IRT research and barriers associated with open data sharing by public agencies, we developed an initial version of the model. Once the model is refined in a qualitative study (interviews with public agencies), we will validate it to study the resistance of public authorities to openly sharing government data in a quantitative study.
Read the paper and cite as -> Nikiforova A., Zuiderwijk A. (2022) Barriers to openly sharing government data: towards an open data-adapted innovation resistance theory, In 15th International Conference on Theory and Practice of Electronic Governance (ICEGOV 2022). Association for Computing Machinery, New York, NY, USA, 215–220, https://doi.org/10.1145/3560107.3560143 – best paper award nominee
Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRISAnastasija Nikiforova
This presentation is a supplementary material for the "Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRIS" presented at 15th International Conference on Current Research Information Systems (CRIS2022) - Linking Research Information across data spaces. It provides an insight on the ongoing study of combining data lake as a data repository and data wrangling seeking for an increased data quality in CRIS systems, although the proposed approach is domain-agnostic and can be used not only within CRIS.
Read the article here -> Azeroual, O., Schöpfel, J., Ivanovic, D., & Nikiforova, A. (2022, May). Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRIS. In CRIS2022: 15th International Conference on Current Research Information Systems --> https://hal.archives-ouvertes.fr/hal-03694519/
Data security as a top priority in the digital world: preserve data value by ...Anastasija Nikiforova
Today, in the age of information and Industry 4.0, billions of data sources, including but not limited to interconnected devices (sensors, monitoring devices) forming Cyber-Physical Systems (CPS) and the Internet of Things (IoT) ecosystem, continuously generate, collect, process, and exchange data. With the rapid increase in the number of devices and information systems in use, the amount of data is increasing. Moreover, due to the digitization and variety of data being continuously produced and processed with a reference to Big Data, their value, is also growing. As a result, the risk of security breaches and data leaks. The value of data, however, is dependent on several factors, where data quality and data security that can affect the data quality if the data are accessed and corrupted, are the most vital. Data serve as the basis for decision-making, input for models, forecasts, simulations etc., which can be of high strategical and commercial / business value. This has become even more relevant in terms of COVID-19 pandemic, when in addition to affecting the health, lives, and lifestyle of billions of citizens globally, making it even more digitized, it has had a significant impact on business. This is especially the case because of challenges companies have faced in maintaining business continuity in this so-called “new normal”. However, in addition to those cybersecurity threats that are caused by changes directly related to the pandemic and its consequences, many previously known threats have become even more desirable targets for intruders, hackers. Every year millions of personal records become available online. Moreover, the popularity of IoTSE decreased a level of complexity of searching for connected devices on the internet and easy access even for novices due to the widespread popularity of step-by-step guides on how to use IoT search engine to find and gain access if insufficiently protected to webcams, routers, databases and other artifacts. A recent research demonstrated that weak data and database protection in particular is one of the key security threats. Various measures can be taken to address the issue. The aim of the study to which this presentation refers is to examine whether “traditional” vulnerability registries provide a sufficiently comprehensive view of DBMS security, or whether they should be intensively and dynamically inspected by DBMS holders by referring to Internet of Things Search Engines moving towards a sustainable and resilient digitized environment. The paper brings attention to this problem and make the reader think about data security before looking for and introducing more advanced security and protection mechanisms, which, in the absence of the above, may bring no value.
IoTSE-based Open Database Vulnerability inspection in three Baltic Countries:...Anastasija Nikiforova
This presentation is devoted to the "IoTSE-based Open Database Vulnerability inspection in three Baltic Countries: ShoBEVODSDT sees you" research paper developed by Artjoms Daskevics and Anastasija Nikiforova and presented during the The International conference on Internet of Things, Systems, Management and Security (IOTSMS2021) co-located with The 8th International Conference on Social Networks Analysis, Management and Security (SNAMS2021), December 6-9, 2021, Valencia, Spain (online)
Read paper here -> Daskevics, A., & Nikiforova, A. (2021, December). IoTSE-based open database vulnerability inspection in three Baltic countries: ShoBEVODSDT sees you. In 2021 8th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 1-8). IEEE -> https://ieeexplore.ieee.org/abstract/document/9704952?casa_token=NfEjYuud0wEAAAAA:6QxucVPuY762I3qzD6D_oWqa0B9eMUFRNMG-E7dyHKohSYIzI0bH1V9bLaAcly_Lp-Ll52ghO5Y
Stakeholder-centred Identification of Data Quality Issues: Knowledge that Can...Anastasija Nikiforova
This presentations is a supplementary material for presenting the "Stakeholder-centred Identification of Data Quality Issues: Knowledge that Can Save Your Business" (authored by Anastasija Nikiforova and Natalija Kozmina) research paper during the The International Conference on Intelligent Data Science Technologies and Applications (IDSTA2021), November 15-16, 2021. Tartu, Estonia (web-based)
Read paper here -> Nikiforova, A., & Kozmina, N. (2021, November). Stakeholder-centred Identification of Data Quality Issues: Knowledge that Can Save Your Business. In 2021 Second International Conference on Intelligent Data Science Technologies and Applications (IDSTA) (pp. 66-73). IEEE -> https://ieeexplore.ieee.org/abstract/document/9660802?casa_token=LFJa20LrXAwAAAAA:wVwhTcCPWqxdloAvDQ3-l98KkkLx70xzG3zNvIIkJbC6wvJ4VxwX_VGc3mmW_7c1T-QJlOtTiao
ShoBeVODSDT: Shodan and Binary Edge based vulnerable open data sources detect...Anastasija Nikiforova
This presentation is devoted to the "ShoBeVODSDT: Shodan and Binary Edge based vulnerable open data sources detection tool or what Internet of Things Search Engines know about you" research paper developed by Artjoms Daskevics and Anastasija Nikiforova and presented during the The International Conference on Intelligent Data Science Technologies and Applications (IDSTA2021), November 15-16, 2021. Tartu, Estonia (web-based).
Read paper here -> Daskevics, A., & Nikiforova, A. (2021, November). ShoBeVODSDT: Shodan and Binary Edge based vulnerable open data sources detection tool or what Internet of Things Search Engines know about you. In 2021 Second International Conference on Intelligent Data Science Technologies and Applications (IDSTA) (pp. 38-45). IEEE.
OPEN DATA: ECOSYSTEM, CURRENT AND FUTURE TRENDS, SUCCESS STORIES AND BARRIERSAnastasija Nikiforova
"OPEN DATA: ECOSYSTEM, CURRENT AND FUTURE TRENDS, SUCCESS STORIES AND BARRIERS" set of slides was prepared for the Guest Lecture, which I has delivered to the students of the University of South-Eastern Norway (USN), October 2021
Towards enrichment of the open government data: a stakeholder-centered determ...Anastasija Nikiforova
This set of slides is a part of the presentation prepared and delivered in the scope of the 14th International Conference on Theory and Practice of Electronic Governance (ICEGOV 2021), 6-8 October, 2021, Smart Digital Governance for Global Sustainability
It is based on the paper -> Nikiforova, A. (2021, October). Towards enrichment of the open government data: a stakeholder-centered determination of High-Value Data sets for Latvia. In 14th International Conference on Theory and Practice of Electronic Governance (pp. 367-372) -> https://dl.acm.org/doi/abs/10.1145/3494193.3494243?casa_token=bPeuwmFWwQwAAAAA:ls-xXIPK5uXDHyxtBxqsMJOCuV6ud_ip59BX8n78uJnqvql6e8H9urlDG9zzeNklRmGFwI4sCXU06w
Atvērtā lekcija "Atvērto datu potenciāls" notika LU SZF maģistrantūras kursa “Datu sabiedrības vadība” ietvaros, ko nolasīja Dr.sc.comp. Anastasija Ņikiforova, LU Datorikas fakultātes docente, pētniece.
Atvērtie dati tiek uzskatīti par vērtīgu resursu, kura izmantošana ir potenciāli spējīga sniegt ievērojamus ekonomiskus, tehnoloģiskus un sociālus ieguvumus. Taču to panākšanai ir jāizpildās virknei priekšnosacījumu, kas attiecināmi gan uz datiem, gan uz infrastruktūru, gan uz lietotājiem, t.i. atvērto datu iniciatīvas veiksmes faktors ir ilgtspējīgas atvērto pārvaldes datu ekosistēmas izveide un uzturēšana. Lekcijas mērķis ir sniegt ieskatu par atvērto datu popularitāti un potenciālu tehnoloģisko un ekonomisko procesu attīstībai, uzmanību pievēršot to praktiskiem pielietojumiem gan Latvijā, gan ārpus tās, datus transformējot (inovatīvajos) risinājumos un pakalpojumos. Tāpat, ir plānots sniegts ieskatu par nozīmīgākajiem aspektiem, kas potenciāli ir spējīgi sekmēt ilgtspējīgas atvērto datu ekosistēmas izveidi, nodrošinot iespēju ikvienam interesentam atvērtus datus transformēt vērtībā.
PhD, Dc. comp.sc. Anastasija Ņikiforova ir Latvijas Universitātes Datorikas Fakultātes docente un Inovatīvo informācijas tehnoloģiju laboratorijas pētniece. Dr. Ņikiforovas pētnieciskas intereses ir saistītas ar datu pārvaldības, īpaši datu kvalitātes, un atvērto datu saistītājiem jautājumiem. LU Datorikas fakultātē papildus citiem docētājiem kursiem viņa ir izstrādājusi Specsemināru “Atvērtie dati un datu kvalitāte” un maģistra programmas kursu “Atvērtie pārvaldes dati datu-virzītā pasaulē”. Dr. Ņikiforova ir Latvijas Zinātnes padomes eksperte Inženierzinātnes un tehnoloģijas (Elektrotehnika, elektronika, informācijas un komunikāciju tehnoloģijas) un Dabaszinātnes (Datorzinātnes un informātika) nozarēs, kā arī LATA (Latvijas Atvērto Tehnoloģiju Asociācija) asociētā biedre. Viņa ir vairāk kā 25 zinātnisko rakstu (līdz-)autore, 4 no kuriem ir publicēti augstākā rangā Q1 žurnālos.
TIMELINESS OF OPEN DATA IN OPEN GOVERNMENT DATA PORTALS THROUGH PANDEMIC-RELA...Anastasija Nikiforova
This presentation is a supplementary material for the following article -> Nikiforova, A. (2020, October). Timeliness of open data in open government data portals through pandemic-related data: a long data way from the publisher to the user. In 2020 Fourth International Conference on Multimedia Computing, Networking and Applications (MCNA) (pp. 131-138). IEEE.
The paper addresses the “timeliness” of data in open government data (OGD) portals. It is one of the primary principles of open data, which is considered to be a success factor, while at the same time it is one of the biggest barriers that can disrupt users trust in data and even the desire to use the entire open data portal. However, assessing this aspect is a very difficult task that, in most cases, becomes an impossible for open data users. There is therefore a lack of comparative studies on the timeliness of data of different national open data portals. Unfortunately, 2020 gave the opportunity to find out this. It became easy enough to compare how long is the data path from the data holder to the OGD portal by analysing the timeliness of Covid-19-related data sets in relation to the first case observed in a country. The study thus fills the gap of comparative studies by addressing 60 countries and their OGD portals concerning the timeliness of the data, providing a report on how much and what countries provide the open data as quickly as possible. It makes it possible to understand how quickly OGD portals react to emergencies by opening and updating data for their further potential reuse, which is essential in the digital data-driven world.
Read paper here -> Nikiforova, A. (2020, October). Timeliness of open data in open government data portals through pandemic-related data: a long data way from the publisher to the user. In 2020 Fourth International Conference on Multimedia Computing, Networking and Applications (MCNA) (pp. 131-138). IEEE.https://ieeexplore.ieee.org/abstract/document/9264298?casa_token=FtfC_6bqZnsAAAAA:TaSnKrE7ZCxLyq5hvxX-X8O2sK_vZYcodTBtxoWOvaOAIFmMmy65f5dIK-kKYxFAMiC5jyl7Eeg
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
TOP 10 B TECH COLLEGES IN JAIPUR 2024.pptxnikitacareer3
Looking for the best engineering colleges in Jaipur for 2024?
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NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
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We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Artificial Intelligence for open data or open data for artificial intelligence?
1. ARTIFICIAL INTELLIGENCE FOR OPEN DATA OR
OPEN DATA FOR ARTIFICAL INTELLIGENCE?
Faculty Development Program «Artificial Intelligence for Sustainable Development» by
Artificial Intelligence Research Centre, Department of Computer Science & Engineering, Babu Banarasi Das University, India
ShodhGuru Innovation and Research Lab, Soft Computing Research Society, New Delhi
IEEE UP Section, Computational Intelligence Society Chapter
Anastasija Nikiforova, PhD
2. BIO
PhD in Computer Science – Data Processing Systems and Data Networking
Research interests include but are not limited to data management with a focus on data quality, open
government data, Smart City, Society 5.0, sustainable development, IoT, HCI, digitization.
Most recent experience:
✓ Assistant professor at the University of Tartu, Institute of Computer Science
✓ European Open Science Cloud Task Force “FAIR Metrics and Data Quality”
✓ associate member of the Latvian Open Technology Association.
✓ expert of the Latvian Council of Sciences in (1) Natural Sciences – Computer Science & Informatics,
(2) Engineering and Technology-Electrical Engineering, Electronics, ICT, (3) Social Sciences –
Economics and Business
✓ expert of the COST – European Cooperation in Science & Technology
✓ visiting researcher at the Delft University of Tehnology, Faculty Technology Policy and Management
✓ assistant professor at the Faculty of Computing, University of Latvia
✓ researcher in the Innovation Laboratory, Faculty of Computing, University of Latvia
✓ IT-expert at the Latvian Biomedical Research and Study Centre, BBMRI-ERIC LV National Node
✓ advisor for the Institute for Social and Political Studies, University of Latvia
3. BIO
➢program committee for 20+ international conferences
➢invited reviewer for 15+ high-quality (Q1-Q2) journals
➢Editorial Board Member and an Associate Editor
✓ BMC Research Notes (Springer Nature
✓ eJournal of eDemocracy and Open Government (JeDEM)
✓ Data & Policy (Cambridge Press)
✓ International Journal on Semantic Web and Information
Systems (IJSWIS) (IGI Global)
6. ✓ Artificial intelligence has the potential to benefit society, businesses and governmental bodies.
✓ AI is the key to sustainable future value creation (Saheb, 2022)
✓ AI offers new opportunities in developing and emerging countries to overcome obstacles and achieve the global Sustainable
Development Goals (including, but not limited to agriculture, food safety, mobility)
Image source: Artificial intelligence and sustainability - Major
7. OPTIMIST vs PESSIMIST
Cyber-optimists
✓ “AI can empower creative activities, freeing workers to
perform non-value-adding operational tasks”
✓ “With big data exploitation, it may be possible to
generate scenarios and predictive models useful for
strategic decision-making”
✓ “AI ethical usage can improve transparency,
accountability, productivity, and service’s quality for
public value creation”
✓ AI contributes to “efficiency, error reduction,
transparency, 24/7 customizable services, pattern
detection, simulations for decision-making, and thus
public value generation”
✓ And many more…
(Castro & New, 2016; Criado & Gil-Garcia, 2019; Valle-Cruz, 2019, 2022)
Cyber-pessimists
And what about realists?
Or maybe one of these clusters is about them?
“In AI we trust!”
✓ “Data quality and legacy biases in AI-based models are a peril
for decision-making”
✓ “Algorithmic opacity”
✓ “Automated manipulation and discretion by AI”, “systematic
manipulation”, “algorithmic biases”
✓ “The lack of explainability of some AI-based techniques and
systems”
✓ Subjectivity
✓ amplification of social inequalities, dangers of inequity,
discrimination, racism, unfairness
✓ “racist bias risks to job performance, privacy, and human rights
violation”
✓ And many more…
(Coglianese & Lehr, 2016; Hartmann & Wenzelburger, 2021; Janssen et al., 2022; Young et al., 2019)
Image source: Dr. Sheldon Cooper on Twitter | Optimism, Optimism quotes, Pessimist (pinterest.com)
8. Source: Saheb, T., & Saheb, T. Topical Review of Artificial Intelligence National Policies: A Mixed Method Analysis. Available at SSRN 4208097.
✓ Combinations of open data and AI models are expected to play a transformational role in human society, especially in prominent
areas such as healthcare and drug discovery (Jiménez-Luna, et al., 2021). Similar trends across domains as data-dependent AI
models continue to improve performance
✓ AI technologies are expected to augment humans and transform society (also about Society 5.0)
✓ Expansive open data has the potential to catalyze AI transformations and to support the next wave of open-data and AI-driven
value creation → there is an urgent need to support and enhance open data initiatives.
Sooooooooooo…..
IT’S ALL ABOUT OPEN DATA!
(not all, but a lot about it)
OPEN DATA FOR AI
9. Source: Saheb, T., & Saheb, T. Topical Review of Artificial Intelligence National Policies: A Mixed Method Analysis. Available at SSRN 4208097.
10. Open data are data that anyone can access, use and share ***
OPEN DATA AND
OPEN GOVERNMENT DATA (OGD)
Source: https://www.opengovguide.com/topics/open-government-data/
Complete
Primary
Accessible
Machine-
processable
Timely
Non-discriminatory
Non-proprietary
Licence-free
12. Supporting growing economies
To support the emergence of new data-driven businesses and
the growth of existing ones, governments need to publish key
datasets.
Governments also need to support data infrastructure that
connects data with those who use it.
In return, governments are reaping the benefits of a growing
data economy, such as in Finland where SMEs with access to
open data grew 15% faster than those without.
Take me to the Finnish case study
Improved service delivery
Governments need to balance the demands of growing
populations with the need to tackle small-scale, local
issues.
The availability of detailed open data is essential to
improving delivery of services at the local level.
Some of these new services are available now:
Take me to mySociety
Take me to the Hungarian 'right to know' portal
Take me to Fix my Street Norway
Cost savings
Open data allows governments to make savings in key areas such as
healthcare, education and utilities.
In the UK, open data helped reveal £200 million of savings in the
health service.
In France, energy data is being used to drive more efficient energy
generation practices.
Show me the France energy data.
Open data can also bring transparency and accountability to
budgets.
Source: https://data.europa.eu/elearning/en/module2/#/id/co-01
OPEN DATA USE. GOVERNMENT (source: data.europa.eu)
13. Improving the way we move
Open data has the power to revolutionise the way we travel.
Within the Dutch transport industry, open data is helping a
growing number of small companies to develop new services.
French app Tranquilien improves passenger comfort on
transport and promotes efficient use of public transport by
providing relevant information about empty seats, leaving times
A new Dutch app, winner of the prestigious Apps4Europe
competition, helps disabled people to book travel assistance for
their journeys using open data.
Open transport data saves commuters time, makes journeys
more accessible and helps tourists to travel in unfamiliar cities.
Improving the way we work
Open data is changing the way we work.
Open data reduces the time needed to find information and allows
professionals to focus more of their time on productive activities.
OpenCorporates offers an open database of companies around the
world, showing their networks, financial stability and environmental
impact. This helps organisations learn more about prospective
clients, providers and partners.
Take me to OpenCorporates
The Finnish Kannattaako kauppa service provides insights on the
price development of real estate in the future, making it easy to
compare houses and neighborhoods by price and population.
Improving the way we govern
Open data is becoming a key source of evidence for governments in the policymaking
process. Public administration will gain the most from opening up data, with a value of 22
bn EUR in 2020. For agriculture, the arts and entertainment sector, the benefits expected
are smaller with 379 million EUR each. They still have a lot of potential in these sectors but
will take more time to reach the full potential. They are also making the development of
public policy more transparent and supporting dialogue between governments and citizens.
Data on key issues such as immigration, trade and budget cuts can be used to inform
important policy decisions.
CityScale is a Ukrainian platform that provides Ukrainian citizens with relevant open data,
such as on crime rates, health care, and air pollution.
Take me to London fire station analysis
OPEN DATA USE. COMMUNITY AND PUBLIC
TRANSFORMATION, CULTURE AND ENVIRONMENT
Environment
Open data helps farmers to improve yields and support a
growing population without the need to destroy valuable
habitats. Plantwise are collecting open data to produce valuable
information packs for farmers about plant health and threats
from diseases. Take me to Plantwise
CIARD has produced a central repository of more than 1,500
open agricultural research collections worldwide, highlighting
new research opportunities. Take me to CIARD
Saving lives
Open data is helping to save lives. Open geographic data and aid
statistics are being used by humanitarian groups to deliver targeted
supplies in disaster zones.
Open mapping data helped disaster response teams target aid
delivery during the 2010 Haiti earthquake. Haiti Open Street Map.
Open data was also used for responses to the Philippines typhoon
in 2014.
Culture
Open data is connecting people with important cultural issues and helping to shape a more
informed debate around them.
OpenGLAM is helping to capture the heritage and cultural memories of groups in Germany,
Switzerland and Finland. Take me to OpenGLAM.
The Open Data Institute is leading a global Data as Culture programme, with artists in
residence re-examining the fundamental ways in which data is perceived. Take me to ODI
Data as Culture
14. OPEN DATA IN THE MOTION
COVID-19 OGD → a SARS-CoV-2 virus transmission model based on human flow
networks → new perspectives + modeling of different scenarios + illustrating the
evolution of and trends in the pandemic
López, V.; Čukić, M. A dynamical model of SARS-CoV-2 based on people flow networks.
Saf. Sci. 2021, 134, 105034
relationship between COVID-19 open data and PM2.5 → a positive relationship between
long-term PM2.5 exposure and the incidence of COVID-19
Chen, L.J.; Ho, Y.H.; Lee, H.C.; Wu, H.C.; Liu, H.M.; Hsieh, H.H.; Lung, S.C.C.
An open framework for participatory PM2.5 monitoring in smart cities. IEEE Access 2017, 5, 14441–14454.
a sensor-generated air pollution open data catalog → system focusing on the
detecting and treatment of one of the most important sleep disorders,
Obtrusive sleep apnea (OSA) (open data processing, along with other factors
such as sleep environment, sleep status, physical activities, and
physiological parameters)
Yacchirema, D.C.; Sarabia, D.; Palau, C.E.; Esteve, M. A Smart System for Sleep Monitoring by Integrating IoT
With Big Data Analytics. IEEE Access 2018, 6, 35988–36001
real-time (!!!) open data → a participatory urban-sensing framework for fine
particulate matters PM2.5 - Taiwan +29 countries → one of the largest
deployment projects for PM2.5 monitoring in the world → collected data are
released in real time and in an open data manner, which has contributed to
the development of other products and services using data which has been
made open, thereby creating a chain of valuable open data-based solutions
and services
Stieb, D.M.; Evans, G.J.; To, T.M.; Brook, J.R.; Burnett, R.T. An ecological analysis of long-term exposure to PM2.5
and incidence of COVID-19 in Canadian health regions. Environ. Res. 2020, 191, 110052
https://www.mdpi.com/1424-8220/21/15/5204/htm
smart home connected to the Internet through a home gateway. Encrypted data
traffic available in the form of open data to everyone (200,000 samples of encrypted
data obtained from 15 applications in this particular case) → a software-defined
network home gateway (SDN-HGW) framework to manage distributed smart home
networks and support the SDN controller of the core network, where the SDN
controller enables efficient network quality-of-service management based on real-
time traffic monitoring and resource allocation of the core network for both types of
data flows, encrypted or unencrypted.
Wang, P.; Ye, F.; Chen, X.; Qian, Y. Datanet: Deep Learning Based Encrypted Network Traffic Classification in SDN Home Gateway. IEEE Access 2018, 6, 55380–55391
Wang, P.; Chen, X.; Ye, F.; Sun, Z. A survey of techniquesfor mobile service encrypted traffic classification using deep learning. IEEE Access 2019, 7, 54024–54033
15. ROLE OF THE OPENNESS. O(G)D
➢ The majority of studies found which actively utilize or promote open data can be classified in at least two general categories,
where open data are used as:
➢ an input for new services, such as (bio)medicine or healthcare, transport, environment, Smart City etc.,
➢ a tool to improve the algorithms already developed, optimize solutions in use, or introduce new ones where the open data can be used
as training data without the need for resources (both, time, money and human) to be spent on data collection.
➢ The way in which open (government) data are reused points to:
➢ their potential by themselves as a resource and a tool, i.e. data opening can be considered to be the key to various benefits, both
commercial and non-commercial,
➢ their potential in regard to Society 5.0,
➢ the more data become available, the more new application areas will be explored.
➢ This, in turn, contributes significantly to the development of new cooperation and combating challenges with common forces
INPUT DATA (RESOURCE)
New services, solutions etc.
Example: medicine, transport, environment,
Smart City etc.
TOOL
Improvement of existing algorithms
Optimization of the existing algorithms, development of
new algorithms (using as training data or supplementing
data etc.).
TOOL OR RESOURCE?
16. ROLE OF THE OPENNESS. O(G)D
➢ The majority of studies found which actively utilize or promote open data can be classified in at least two general categories,
where open data are used as:
➢ an input for new services, such as (bio)medicine or healthcare, transport, environment, Smart City etc.,
➢ a tool to improve the algorithms already developed, optimize solutions in use, or introduce new ones where the open data
can be used as training data without the need for resources (both, time, money and human) to be spent on data collection.
➢ The way in which open (government) data are reused points to:
➢ their potential by themselves as a resource and a tool, i.e. data opening can be considered to be the key to various benefits,
both commercial and non-commercial,
➢ their potential in regards to Society 5.0,
➢ the more data become available, the more new application areas will be explored.
➢ This, in turn, contributes significantly to the development of new cooperation and combating challenges with common
forces
17. OPEN DATA IN THE SCIENCE. TOOL OR RESOURCE?
INPUT DATA (RESOURCE)
New services, solutions etc.
Example: medicine, transport, environment,
Smart City etc.
TOOL
Improvement of existing algorithms
Optimization of the existing algorithms,
development of new algorithms (using as
training data or supplementing data etc.).
20. Source: Saheb, T., & Saheb, T. Topical Review of Artificial Intelligence National Policies: A Mixed Method Analysis. Available at SSRN 4208097.; https://datos.gob.es/en/blog/artificial-intelligence-and-open-data
✓ Open data is essential for the proper functioning of AI, since the algorithms must be fed by data whose quality and
availability is essential for its continuous improvement, as well as to audit its correct operation
✓ AI today is data-dependent, and it is necessary to ensure both a wide range** of data (data sharing) and high-
quality data
Sooooooooooo…..
IT’S ALL ABOUT DATA QUALITY!
(not all, but a lot about it)
PREREQUISITES FOR OPEN DATA FOR AI:
IS IT ONLY ABOUT DATA AVAILABILITY?
21. Source: Saheb, T., & Saheb, T. Topical Review of Artificial Intelligence National Policies: A Mixed Method Analysis. Available at SS
✓ AI entails an increase in the sophistication of data processing, since it requires greater precision, updating and
quality, which must be obtained from very diverse sources to increase the quality of the algorithms results.
✓ An added difficulty - processing is carried out in an automated way and must offer precise answers immediately
to face changing circumstances ➔ a dynamic perspective that justifies the need for data not only to be offered in
open and machine-readable format, but also with the highest levels of precision and disaggregation.
AI defines new prerequisites for open data
AI FOR OPEN DATA
Source: Saheb, T., & Saheb, T. Topical Review of Artificial Intelligence National Policies: A Mixed Method Analysis. Available at SS
22. OPEN DATA AND AI – MAGIC DUO:
IS IT ALWAYS ABOUT UNICORNS AND ICE CREAM?
23. The Verge; https://www.gamingdeputy.com/an-ai-generated-40000-toxic-molecules-in-6-hours-the-risk-of-open-data-never-considered/
✓ Based on easily obtainable open data on toxic molecules collected over the years, AI, without knowing anything about wars and
unconventional weapons, has managed to create 40,000 molecular associations potentially usable as biochemical weapons* in just 6 hours
✓ Not all are actually usable, and the need to synthesize them remains standing, but some associations correspond to known chemical
weapons with one even more toxic than the VX nerve gas, identified as a weapon of mass destruction by the United Nations
✓ incredible and worrying result is therefore the relative ease with which a malevolent actor could generate biochemical weapons
Question: Probably it is not easy, isn’t so?
Answer: “If you have someone who knows how to program in Python and has some machine learning skills, then, probably in two days of
work, they could build something like this dataset-driven generative model of toxic molecules.“
Question: what to do?
Answer: «provide tokens for the use of those open data that can be used to develop AI models on sensitive issues such as chemical and
biochemical weapons»
AI defines new prerequisites for open data
AN AI GENERATED 40,000 TOXIC MOLECULES IN 6 HOURS.
THE RISK OF OPEN DATA NEVER CONSIDERED
24. ✓ There is often a lack of frameworks, capacities and strategies for responsible and locally appropriate development of AI applications.
✓ For example, only 25 out of 54 African countries have data protection legislation, and only a few pioneering countries such as Kenya and India have
launched strategies for the use and promotion of AI ➔ developing and emerging countries therefore risk being left behind in the use and development of
AI or becoming dependent on leading AI nations
✓ Cross-border personal data-related risks (Guaman et al., 2021) ➔ as cross-border data flows are prevalent and used in AI applications such as Google
Maps, Search, or Waze, national AI policies need to pay special attention to multilateral consensus on data flows privacy and security (Yakovleva, 2022).
✓ Another risk - inequalities, discrimination and human rights violations that will be exacerbated by the new technology.
✓ Lack of or limited provision of open, non-discriminatory and inclusive training data
✓ Lack of trust [open data OR AI?]
✓ Lack of contextualisation [open data OR AI?]
✓ Lack of quality [open data OR AI?]
✓ Lack of literacy [open data OR AI?]
✓ While the emphasis of current policies is primarily on the technical aspects, the ethical and social implications should be considered [open data OR AI?]
✓ The need of «green» AI and consideration of FATE principles (Fairness, Accountability, Transparency and Explainability) (Werder et al., 2022).
✓ And many more…
SEVERAL OTHERS RISKS
https://www.bmz-digital.global/en/overview-of-initiatives/fair-forward/
30. Thank you for your
attention!
Contact information:
Website: https://anastasijanikiforova.com/
Email: nikiforova.anastasija@gmail.com
LinkedIn: https://www.linkedin.com/in/anastasija-nikiforova-466b99b3/
31. REFERENCES
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