Artificial Intelligence for open data or open data for artificial intelligence?

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

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

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)

Image source: https://commons.wikimedia.org/wiki/File:Sustainable_Development_Goals.svg

Source: https://social-innovation.hitachi/en-in/knowledge-hub/collaborate/smart-sustainable-cities/
smart city
smart city
smart city
sustainable
city
sustainable
city
sustainable
city
sustainable
city
sustainable
city
sustainable
city
sustainable
city

✓ 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

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”
(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)

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

Source: Saheb, T., & Saheb, T. Topical Review of Artificial Intelligence National Policies: A Mixed Method Analysis. Available at SSRN 4208097.

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

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)

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

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

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?

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

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.).

Artificial Intelligence for open data or open data for artificial intelligence?

Image source: https://blog.orvium.io/fair-principles-in-scientific-data/

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?

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

OPEN DATA AND AI – MAGIC DUO:
IS IT ALWAYS ABOUT UNICORNS AND ICE CREAM?

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

✓ 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).
SEVERAL OTHERS RISKS
https://www.bmz-digital.global/en/overview-of-initiatives/fair-forward/

QUALITY OVER QUANTITY
[also new meaning]

ARTIFICIAL INTELLIGENCE FOR OPEN DATA
OR

ARTIFICIAL INTELLIGENCE FOR OPEN DATA
AND

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/

REFERENCES
✓ Saheb, T., & Saheb, T. Topical Review of Artificial Intelligence National Policies: A Mixed Method Analysis. Available at SSRN 4208097.
✓ John, S., Mishra, S., & Samuel, J. Catalyzing the Information Economy: Moving Towards Strategic Expansions of Open Data-Driven Value Creation.
✓ Perera, V. H., Moriña, A., Sánchez-Díaz, N., & Spinola-Elias, Y. (2021). Technological Platforms for Inclusive Practice at University: A Qualitative Analysis from the Perspective of Spanish Faculty
Members. Sustainability, 13(9), 4755.
✓ Ni, M. (2022). Digital Participation for Inclusive Growth: A Case Study of Singapore’s Collaborative Digital Governance Model. In Design for Vulnerable Communities (pp. 323-337). Springer, Cham.
✓ Saheb, T., & Amini, B. (2021). The impact of artificial intelligence analytics in enhancing digital marketing: the role of open big data and AI analytics competencies.
✓ Walter, M., Lovett, R., Maher, B., Williamson, B., Prehn, J., Bodkin‐Andrews, G., & Lee, V. (2021). Indigenous data sovereignty in the era of big data and open data. Australian Journal of Social Issues, 56(2), 143-
156.
✓ Werder, K., Ramesh, B., & Zhang, R. (2022). Establishing Data Provenance for Responsible Artificial Intelligence Systems. ACM Transactions on Management Information Systems (TMIS), 13(2), 1-23.
✓ Lnenicka, M., & Nikiforova, A. (2021). Transparency-by-design: What is the role of open data portals?. Telematics and Informatics, 61, 101605.
✓ 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.
✓ Elliott, K., Price, R., Shaw, P., Spiliotopoulos, T., Ng, M., Coopamootoo, K., & van Moorsel, A. (2021). Towards an equitable digital society: artificial intelligence (AI) and corporate digital responsibility
(CDR). Society, 58(3), 179-188.
✓ Zhao, W. W. (2018, September). How to improve corporate social responsibility in the era of artificial intelligence?. In IOP Conference Series: Earth and Environmental Science (Vol. 186, No. 6, p. 012036). IOP
Publishing.
✓ Guamán, D. S., Del Alamo, J. M., & Caiza, J. C. (2021). GDPR compliance assessment for cross-border personal data transfers in android apps. IEEE Access, 9, 15961-15982.
✓ Yakovleva, S. (2022). EU’s trade policy on cross-border data flows in the global landscape: navigating the thin line between liberalizing digital trade,“digital sovereignty” and multilateralism.
✓ Jiménez-Luna, J., Grisoni, F., Weskamp, N., & Schneider, G. (2021). Artificial intelligence in drug discovery: Recent advances and future perspectives. Expert opinion on drug discovery, 16(9), 949-959.
✓ Medaglia, R., Gil-Garcia, J. R., & Pardo, T. A. (2021). Artificial intelligence in government: taking stock and moving forward. Social Science Computer Review, 08944393211034087.
✓ Ingrams, A., Kaufmann, W., & Jacobs, D. (2022). In AI we trust? Citizen perceptions of AI in government decision making. Policy & Internet, 14(2), 390-409.
✓ Valle-Cruz, D., Fernandez-Cortez, V., & Gil-Garcia, J. R. (2022). From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource
allocation. Government Information Quarterly, 39(2), 101644.
✓ Castro, D., & New, J. (2016). The promise of artificial intelligence. Center for Data Innovation, 115(10), 32-35.
✓ Valle-Cruz, D. (2019). Public value of e-government services through emerging technologies. International Journal of Public Sector Management.
✓ Criado, J. I., & Gil-Garcia, J. R. (2019). Creating public value through smart technologies and strategies: From digital services to artificial intelligence and beyond. International Journal of Public Sector
Management.
✓ Coglianese, C., & Lehr, D. (2016). Regulating by robot: Administrative decision making in the machine-learning era. Geo. LJ, 105, 1147.
✓ Hartmann, K., & Wenzelburger, G. (2021). Uncertainty, risk and the use of algorithms in policy decisions: a case study on criminal justice in the USA. Policy Sciences, 54(2), 269-287.
✓ Janssen, M., Hartog, M., Matheus, R., Yi Ding, A., & Kuk, G. (2022). Will algorithms blind people? The effect of explainable AI and decision-makers’ experience on AI-supported decision-making in
government. Social Science Computer Review, 40(2), 478-493.
✓ Young, M. M., Himmelreich, J., Bullock, J. B., & Kim, K. C. (2019). Artificial intelligence and administrative evil. Perspectives on Public Management and Governance, 4(3), 244-258.
✓ Valle-Cruz, D., García-Contreras, R., & Muñoz-Chávez, J. P. (2022, June). Mind the Gap: Towards an Understanding of Government Decision-Making based on Artificial Intelligence. In DG. O 2022: The 23rd
Annual International Conference on Digital Government Research (pp. 226-234).

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