CFP for Data For Policy 2024 is open!

And CFP for Data For Policy 2024 scheduled for 9-11 July, 2024 is open! All submissions are welcome with the deadline of 27 November, 2023.

This year Data For Policy conference, which is organized in collaboration with Imperial College London and Cambridge University Press will take place in London, UK, and will be running under the title “Decoding the Future: Trustworthy Governance with AI” – trendy, isn’t it? In this edition the conference “[we] are focusing on the future of governance and decision making with AI. Firstly, what are the emerging capabilities, use cases, and best practices enabling innovation that could contribute to improved governance with AI? Secondly, what concerns are being raised regarding these advancements in areas such as data, algorithms, privacy, security, fairness, and potential risks? For both discussions, we invite proposals that delve into the role and capacity of governance in preventing AI-related harms and explore the potential for governance to generate added value through responsible AI deployment. For a more thorough consideration of the conference theme, please read this informative blog, by Zeynep Engin and conference co-chairs.

Data for Policy is looking forward to your submission to one of six areas of the respective Data & Policy journal, which are transformed into the tracks for this conference. In addition, this list is complemented with a rich list of 11 special tracks.

Of course, my personal recommendation is to consider Area 1 “Digital & Data-driven Transformations in Governance” (chairs: Sarah Giest, Sharique Manazir, Francesco Mureddu, Keegan McBride, Anastasija Nikiforova, Sujit Sikder). More specifically, the track seeks for contributions on topics that include but are not necessarily limited to:

  • From data to decisions: knowledge generation and evidence formation;
  • Process, psychology and behaviour of decision-making in digital era;
  • Government operations and services;
  • Government-citizen interactions; and open government;
  • Democracy, public deliberation, public infrastructure, justice, media;
  • Public, private and voluntary sector governance and policy-making.


Of course, do not ignore other tracks since each and every track definitely deserves your attention:

  • Area 1: Digital & Data-Driven Transformations in Governance – the one I just suggested;
  • Area 2: Data Technologies & Analytics for Governance;
  • Area 3: Policy & Literacy for Data;
  • Area 4: Ethics, Equity & Trustworthiness;
  • Area 5: Algorithmic Governance;
  • Area 6: Global Challenges & Dynamic Threats;
  • Special Track 1: Establishing an Allied by Design AI ecosystem
  • Special Track 2: Anticipating Migration for Policymaking: Data-Based Approaches to Forecasting and Foresight
  • Special Track 3: AI, Ethics and Policy Governance in Africa
  • Special Track 4: Social Media and Government
  • Special Track 5: Data and AI: critical global perspectives on the governance of datasets used for artificial intelligence
  • Special Track 6: Generative AI for Sound Decision-making: Challenges and Opportunities
  • Special Track 7: Governance of Health Data for AI Innovation
  • Special Track 8: Accelerating collective decision intelligence
  • Special Track 9: Artificial Intelligence, Bureaucracy, and Organizations
  • Special Track 10: AI and data science to strengthen official statistics
  • Special Track 11: Data-driven environmental policy-making

To sum up:

🗓️ WHEN? 9-11 July, 2024 -> deadline for papers and abstracts – 27 November, 2023

WHERE? London, UK

WHY? To understand what are the emerging capabilities, use cases, and best practices enabling innovation that could contribute to improved governance with AI? what concerns are being raised regarding these advancements in areas such as data, algorithms, privacy, security, fairness, and potential risks? For a more thorough consideration of the conference theme, please read this.

Find your favorite among tracks and submit! See detail on the official website.

The International Conference on Intelligent Metaverse Technologies & Applications (iMeta) and the 8th IEEE International Conference on Fog and Mobile Edge Computing (FMEC) in Tartu

This year we – University of Tartu, Institute of Computer Science – have a pleasure to host FMEC2023, taking place in conjunction with iMETA, where iMETA, as you can assume, is associated with the metaverse (more precisely, the International Conference on Intelligent Metaverse Technologies & Applications), while FMEC – for the The Eighth IEEE International Conference on Fog and Mobile Edge Computing.

FMEC 2023 conference aims to investigate the opportunities and requirements for Mobile Edge Computing dominance, and seeks for novel contributions that help mitigating Mobile Edge Computing challenges. That is, the objective of FMEC 2023 is to provide a forum for scientists, engineers, and researchers to discuss and exchange new ideas, novel results and experience on all aspects of Fog and Mobile Edge Computing (FMEC) covering one of its major areas, which include, but not limited to the following tracks:

  • Track 1: Fog and Mobile Edge Computing fuels Smart Mobility
  • Track 2: Edge-Cloud Continuum and Networking
  • Track 3: Industrial Fog and Mobile Edge Computing Applications
  • Track 4: Trustworthy AI for Edge and Fog Computing
  • Track 5: Security and privacy in Fog and Mobile Edge Computing
  • Track 6: Decentralized Data Management and Streaming Systems in FMEC
  • Track 7: FMEC General Track

iMETA conference, in turn, aims to provide attendees with comprehensive understanding of the communication, computing, and system requirements of the metaverse. Through keynote speeches, panel discussions, and presentations, attendees had the opportunity to engage with experts and learn about the latest developments and future trends in the field, covering areas such as:

  • AI
  • Security and Privacy
  • Networking and Communications
  • Systems and Computing
  • Multimedia and Computer Vision
  • Immersive Technologies and Services
  • Storage and Processing

As part of these conferences, I had the pleasure of chairing one of the sessions, where the room was carefully selected by the organizers to make me feel as I would be at home – we were located in the so-called Baltic rooms of VSpa conference center, i.e., Estonia, Lithuania, and Latvia, so guess which room the session took place in? Bingo, Latvia! All in all, 5 talks were delivered:

  • Federated Object Detection for Quality Inspection in Shared Production by Vinit Hegiste
  • Federated Bayesian Network Ensembles by Florian van Daalen
  • Hyperparameters Optimization for Federated Learning System: Speech Emotion Recognition Case Study by Mohammadreza Mohammadi
  • Towards Energy-Aware Federated Traffic Prediction for Cellular Networks by Vasileios Perifanis
  • RegAgg: A Scalable Approach for Efficient Weight Aggregation in Federated Lesion Segmentation of Brain MRIs by Muhammad Irfan Khan, Esa Alhoniemi, Elina Kontio, Suleiman A. Khan and Mojtaba Jafaritadi

Each of the above was followed by a very lively discussion, which continued also after the session. This, in turn, was followed by an insightful keynote delivered by Mérouane Debbah on “Immersive Media and Massive Twinning: Advancing Towards the Metaverse”.

Also, thanks to our colleagues from EEVR (Estonian VR and AR Association), I briefly went to my school times and chemistry lessons having a bit of fun – good point, I’ve always loved them (nerd and weirdo, I know…).

Thanks to the entire FMEC and iMETA organizing team!

CFP for a new dg.o2024 SUSTAINABLE PUBLIC AND OPEN DATA ECOSYSTEMS track

25th Annual International Conference on Digital Government Research (dg.o2024) is coming with the revised list of tracks, where the special attention I invite you to draw to is a new track “Sustainable Public and Open Data Ecosystems” (chairs: Anastasija Nikiforova (University of Tartu, Estonia), Anthony Simonofski (UniversitĂ© de Namur ASBL, Belgium), Anneke Zuiderwijk (Delft University of Technology, the Netherlands) & Manuel Pedro RodrĂ­guez BolĂ­var (University of Granada, Spain)).

Briefly about the track… Public and open data ecosystems promise the transformation of government data-driven actions, the fostering of public sector innovations and the collaborative smartification of cities, society and life, triggering value-adding sustainable development goals-compliant smart living and society 5.0 (Nikiforova, 2021, Nikiforova et al., 2023). Recent research found that concepts affecting and shaping the ecosystem are: 1) stakeholders / actors and their roles, 2) phases of the data lifecycle, in which a stakeholder participates in the ecosystem, 3) technical and technological infrastructure, 4) generic services and platforms, 5) human capacities and skills of both providers and consumers, 6) smart city domains (thematic categories) as the targeted areas for data reuse, 7) externalities affecting goals, policy, and resources, 8) level of (de)centralization of data sources – development, restrictions, 9) perception of importance and support from public officials, and 10) user interface, user experience, and usability (Lnenicka et al., 2021). The body of knowledge in the above areas (not to say about putting them all together) is very limited. New research is needed to help public managers and politicians for (1) implementing emerging technologies and technological innovations, (2) improving the achievement of sustainable development goals for increasing transparency, participation, and cooperation, and (3) meeting the stakeholders’ expectations, needs, regulations and demands.

This track welcomes contributions covering, but not limited to:

đź’ˇ The concepts of theoretical approaches toward Public Data ecosystems, Open Data ecosystems, Data Spaces, and Data Marketplaces;

đź’ˇInfrastructures supporting Public and Open Data Ecosystems;

đź’ˇThe role of emerging technologies in Public and Open Data ecosystems;

đź’ˇInstitutional aspects of implementing sustainable Public and Open Data Ecosystems;

đź’ˇOther sustainability dimensions of Public and Open Data Ecosystems;

đź’ˇStakeholder-centric dimensions of Public and Open Data Ecosystems;

đź’ˇCase studies of Public and Open Data Ecosystems;

đź’ˇThe impact of Public and Open Data Ecosystems on Individuals, Organizations and Society.

The track welcomes both contributions covering the current state-of-the-art of public data ecosystems (what components constitute them, what are the relationships between these components, what makes an ecosystem resilient and sustainable), incl. individual case studies reflecting best or bad practices, as well as those addressing how these ecosystems can be transformed into more sustainable ecosystems that will “fuel” or “smartify” society (Information Society aka Society 4.0 to Super Smart Society aka Society 5.0 transition), cities and various areas of life.

The track is very in line with the conference theme of DGO 2024, namely: Internet of Beings – Transforming Public Governance, where, “the Internet of Beings focuses on digital technologies that enable integration, people-centric, and creation of open platforms for collaborative multi-user to co-create services and products” (as mentioned in the theme description). Public and open data ecosystems can be considered as such open platforms, where data providers and data users find each other and collaborate and co-create to develop services and products useful for society. While digital technologies enable the development of public and open data ecosystems, the adoption of such ecosystems has been fragmented.

Is your research related to any of the above topics? Then do not wait – submit!

🗓️🗓️🗓️Important Dates:

January 26, 2024: Papers, workshops, tutorials, and panels are due
Feb 1, 2021: Application deadline for doctoral colloquium
March 8, 2024: Author notifications (papers, workshops, tutorials, panels)

References:

Nikiforova, A. (2021). Smarter open government data for society 5.0: are your open data smart enough?. Sensors, 21(15), 5204.

Nikiforova, A., Flores, M. A. A., & Lytras, M. D. (2023). The role of open data in transforming the society to Society 5.0: a resource or a tool for SDG-compliant Smart Living?. In Smart Cities and Digital Transformation: Empowering Communities, Limitless Innovation, Sustainable Development and the Next Generation (pp. 219-252). Emerald Publishing Limited.

Lnenicka, M., Nikiforova, A., Luterek, M., Azeroual, O., Ukpabi, D., Valtenbergs, V., & Machova, R. (2022). Transparency of open data ecosystems in smart cities: Definition and assessment of the maturity of transparency in 22 smart cities. Sustainable Cities and Society, 82, 103906.

IFIP EGOV-CeDEM-EPART 2023 – retrospective on how it was? From Metaverse to wine tasting

It finally took place! EGOV2023 – IFIP EGOV-CeDEM-EPART â€“ one of the most recognized conference in e-Government, ICT and public administration and related topics (incl., Smart Cities, Sustainability, Innovation and many more) that lasted 3 days in charming city of Budapest (Hungary) is over, and I am here to reflect on it (just in a few words), since although these were just 3 days, they were very busy and full of insights, as well as activities, since every day I took another role, i.e., day#1 – presenter of the paper, day#2 – workshop organizer, day#3 – chair of two out of three sessions of “Emerging Issues and Innovations” track I co-chaired together with Marijn Janssen, Csaba Csaki and Francesco Mureddu. Not to forget, in this conference I am also a program committee of Open Data track.

Let me now provide a few insights on all these days, including my roles.

Let’s start with day#1… After conference opening by Ida Lindgren and Csaba Csaki – our local host, who did a great job – organized a very unique conference with exceptionally rich social programme, a brilliant keynote talk was delivered by Professor Yogesh K Dwivedi (possibly the most impactful researcher in the area) on Metaverse for Government and associated Challenges, Opportunities, as well as Future Research Agenda, as part of which the claim of a lack of studies on this topic was made. Luckily, our track “Emerging Issues and Innovations” has accepted one paper on Metaverse in digital government, which was the only at the conference, however, unfortunately, the discussion had not happened due to earlier departure of Yogesh and late arrival of authors. Anyway, almost immediately after the keynote the session, where I delivered a talk on HVD determination “Towards High-Value Datasets determination for data-driven development: a systematic literature review” (authors: Nikiforova, Rizun, Ciesielska, Alexopoulos, Miletić) took place. Just to remind you, I posted on this paper before – this is that paper, which has been already named “signal in the noise“, in which we asked ourselves and the current body of the knowledge (this is a systematic literature review-driven study):
âť“how is the value of the open government data perceived / defined? Are local efforts being made at the country levels to identify dataset that provide the most value to stakeholders of the local open data ecosystem?
âť“What datasets are considered to be of higher value in terms of data nature, data type, data format, data dynamism?
âť“What indicators are used to determine HVD?
âť“Whether there is a framework for determining country-specific HVD? I.e., is it possible to determine what datasets are of value and interest for their reuse & value creation, taking into account the specificities of the country, e.g., culture, geography, ethnicity, likelihood of crises and/or catastrophes.
Although neither OGD, nor the importance of data value are new topics, scholarly publications dedicated to HVD are very limited that makes study unique and constituting a call for action – probably this is also why it it is recommended for reading not only by us but also by The Living Library (by New York University, NYU Tandon School of Engineering, govlab). All in all, we have established some knowledge based, incl. several definitions of HVD, data-related aspects, stakeholders, some indicators and approaches that can now be used as a basis for establishing a discussion of what a framework for determining HVD should look like, which, along with the input we received from a series of international workshops as part of ICEGOV2022, ICOD2022 and DGO2023 with open data experts could enrich the common understanding of the goal, thereby contributing to the next open data wave.
👉Read the paper here
👉See slides here
👉Find supplementary data in open access at Zenodo here
Here I am very grateful to session attendees for raising a discussion around the topic, where some of those comments confirmed once more the correctness of both the problem statement and our future plans – thanks a lot!

Day#2 of started with another keynote talk, whcih this time delivered by Andras Koltay (President of the National Media and Infocommunications Authority and the Media Council of Hungary) on the protection of freedom of expression from social media platforms – very different but yet very insightful talk. Then, my second role of the workshop organizer and chair followed. As part of our workshop “PPPS’2023 – Proactive and Personalised Public Services: Searching for Meaningful Human Control in Algorithmic Government” (chairs: Anastasija Nikiforova, Nitesh Bharosa, Dirk Draheim, Kuldar Taveter). As part of this workshop, which took place in a hybrid mode (not an easy task), we initiated a discussion about personalised and Proactive Public Services, i.e.:
🎯talked about the concepts of public services, reactive and proactive models of public services, and models of their personalization;
🎯asked participants to share their views on public services and the levels of proactivity and personalisation of these services in their countries aiming to develop concepts for holistic proactive and personalised public service delivery;
🎯tried to establish a clearer vision of the â€śas-is” model and the necessary transition to the â€śto-be” model, their underlying factors, as well as pitfalls of which governments should be aware when designing, developing, and setting up proactive and personalised public services, trying to understand what are those emerging technologies that will likely have greater effect on public services in terms of both driving them or creating obstacles / barriers for their development and maintenance.
Read a bit more 👉 here
Special thanks to all participants, who attended and were very active (and survived)!

And now a few insights from day#3, when three sessions of our Emerging Issues and Innovations track (chairs: Marijn Janssen, Anastasija Nikiforova, Dr. Csaba Csaki, Francesco Mureddu) finally took place, where I was delighted to chair two of these sessions. Within these three sessions, 8 very diverse, but at the same time super interesting and insightful talks were delivered (predominantly from the United Nations University and Sweden), namely:
✍Metaverse vs. metacurse: The role of governments and public sector use cases by Charmaine Distor, Soumaya Ben Dhaou, & Morten Meyerhoff Nielsen that can be seen as a continuation of the keynote talk by Prof. Yogesh Dwivedi delivered at the 1st day;
✍Dynamic Capabilities and Digital Transformation in Public sector: Evidence from Brazilian case study by Larissa Magalhães;
✍Affording and constraining digital transformation: The enactment of structural change in three Swedish government agencies by Malin Tinjan, Robert Åhlén, Susanna Hammelev Jörgensen & Johan Magnusson
✍The Vicious Cycle of Magical Thinking: How IT Governance Counteracts Digital Transformation by Susanna H. Jörgensen, Tomas Lindroth, Johan Magnusson, Malin Tinjan, Jacob Torell & Robert Åhlen
✍Buridan’s Ass: Encapsulation as a Possible Solution to the Prioritization Dilemma of Digital Transformation by Johan Magnusson, Per Persson, Jacob Torell & Ingo Paas
✍Measuring digital transformation at the local level: assessing the current state of Flemish municipalities by Lieselot Danneels & Sarah Van Impe
✍Blockchain and the GDPR – the shift needed to move forward by Inês Campos Ruas, Soumaya Ben Dhaou & Zoran Jordanoski
✍Construct Hunting in GovTech Research: An Exploratory Data Analysis by Mattias Svahn, Aron Larsson, Eloisa Macedo and Jorge Bandeira
Read papers 👉 here, here & here
Big thanks go to both authors and presenters, as well as the audience, who was very active (even despite the fact that it was the very last day of the conference) and made these sessions a success!
And right after these two sessions, the third keynote by Laszlo Trautmann “The ethics of expertise – the political economy implications of AI”.


And the last but not the least, yet another social event – wine tasting at Etyeki Kúria Borászat / Winery, which was the perfect happy end of the EGOV2023!

Exceptional organization by Corvinus University of Budapest, Csaba Csaki and his team, International Federation for Information Processing (IFIP), Digital Government Society – cheers!🍷🍷🍷

📢New paper alert 📢“Predictive Analytics intelligent decision-making framework and testing it through sentiment analysis on Twitter data” or what people do and will think about ChatGPT?

This paper alert is dedicated to “Predictive Analytics intelligent decision-making framework and testing it through sentiment analysis on Twitter data” (authors: Otmane Azeroual, Radka Nacheva, Anastasija Nikiforova, Uta Störl, Amel Fraisse) paper, which is now publicly available in ACM Digital Library!

In this paper we present a predictive analytics-driven decision framework based on machine learning and data mining methods and techniques. We then demonstrate it in action by predicting sentiments and emotions in social media posts as a use-case choosing perhaps the trendiest topic – ChatGPT. In other words we check whether it is eternal love and complete trust or rather 🤬?

Why PA?

Predictive Analytics are seen to be useful in business, medical/ healthcare domain, incl. but not limited to crisis management, where, in addition to health-related crises, Predictive Analytics have proven useful in natural disasters management, industrial use-cases, such as energy to forecast supply and demand, predict the impact of equipment costs, downtimes / outages etc., aerospace to predict the impact of specific maintenance operations on aircraft reliability, fuel use, and uptime, while the biggest airlines – to predict travel patterns, setting ticket prices and flight schedules as well as predict the impact of, e.g., price changes, policy changes, and cancellations. And, of course, business process management and specifically retail, where Predictive Analytics allows retailers to follow customers in real-time, delivering targeted marketing and incentives, forecast inventory requirements, and configure their website (or store) to increase sales. It business process management area, in turn, Predictive Analytics give rise to what is called predictive process monitoring (PPM). Predictive Analytics uses were also found in Smart Cities and Smart Transportation domain, i.e. to support smart transportation services using open data, but also in education, i.e., to predict performance in MOOCs.

This popularity can be easily explained by examining their key strategic objectives, which IBM (Siegel, 2015) has summarized as: (1) competition – to secure the most powerful and unique stronghold of competitiveness, (2) growth – to increase sales and keep customers competitively, (3) enforcement – to maintain business integrity by managing fraud, (4) improvement – to advance core business capacity competitively, (5) satisfaction – to meet rising consumer expectations, (6) learning – to employ today’s most advanced analytics, (7) acting – to render business intelligence and analytics truly effective actionable. Marketing, sales, fraud detection, call center and core businesses of business units, same as customers and the enterprise as  a whole are expected to gain benefits, which makes PA a “must”.

And although according to (MicroStrategy, 2020), in 2020, 52% of companies worldwide used predictive analytics to optimize operations as part of business intelligence platform solution, although so far, predictive analytics have been used mostly by large companies (65% of companies with $100 million to $500 million in revenue, and 46% of companies under $10 million in revenue), with less adoption in medium-sized companies, not to say about small companies

Based on management theory and Gartner’s Business Intelligence and Performance Management Maturity Model, our framework covers four management levels of business intelligence – (a) Operational, (b) Tactical, (c) Strategic and (d) Pervasive. These are the levels that determine the need to manage data in organizations, transform them into information and turn them into knowledge, which is also the basis for making forecasts. The end result of applying it for business purposes is to generate effective solutions for each of these levels.

Sounds catchy? Read the paper here.

Many thanks to my co-authors – Radka and Otmane, who invited me to contribute to this study, and drove the entire process!

Cite paper as:

O. Azeroual, R. Nacheva, A. Nikiforova, U. Störl, and A. Fraisse. 2023. Predictive Analytics intelligent decision-making framework and testing it through sentiment analysis on Twitter data. In Proceedings of the 24th International Conference on Computer Systems and Technologies (CompSysTech ’23). Association for Computing Machinery, New York, NY, USA, 42–53. https://doi.org/10.1145/3606305.3606309