People of ACM European Chapters - Athena Vakali

February 11, 2021

How did you initially become interested in data and web science?

My original studies in mathematics and computer science were my initial inspirations for a career in science and research. The recent growth of data and web science disciplines have attracted my interest, since they extend current knowledge to new scientific territories.

Given the rapid emergence of web platforms, services, and applications, it soon became evident that data is a valuable asset that opens new scientific and innovation horizons. We now have the opportunity to proceed from data to knowledge pathways such that data correlations can reveal hidden information that can be valuable in multiple settings and sectors. Data analytics, in particular, can uncover important insights about all aspects of real life in both private and public sectors.

Exciting new norms for opening data and knowledge demand specific data and web science principles, methods, visualizations, and explanations, which are now cutting-edge interdisciplinary objectives for all data scientists. All these aspects have triggered my high interest in this field. My vision is to encourage and motivate the next generation of bright young researchers to progress and excel, with high data and web science ethical standards, in order to establish socially good and sustainable data-driven solutions.

In your area of research, what recent advance/emerging subfield will yield important advances in the years ahead?

As the demand for data science solutions and skills steadily increases, it will drive many breakthrough changes. We now need a solid data and web science background as a major driver to ensure next-generation digital services that will offer human-centric applications and services, strongly connected to our societies and communities. Augmented analytics and analytics “on the fly” is among the advanced knowledge acquisition subfields that should evolve to support embedded automated processes in a changing AI and data-driven world.

For example, smart vehicles and connected unmanned aerial vehicles will demand solid and qualitative data analytics, since their critical decision making will be highly data-driven. Ambient sensing and Internet of Everything (IoE) tolerance are key, as applications intersect with many aspects of human and industrial activities which produce and consume data. Data crucial features that include explainability, ethics, privacy, security and resilience should be safeguarded, especially in the new human-machine symbiosis. We need to empower the research and innovation developments with cautious data protection rules applied under emerging and unforeseen novel domains at which human activity is central, such as in the critical cases emerging in the many “Internet of” (Internet of Health, Internet of Sports, Internet of People, Internet of Trust, etc.) areas.

Will you tell us about some of the activities of the Greek ACM-W Chapter?

The Greek Chapter of ACM-W was established in July 2018 with the vision of fostering gender mainstreaming, as well as enhancing and advocating for gender balance in computer-related scientific fields and professional sectors of Greek society. Its founding members—39 women from academia, research institutions, and the computing industry—cover a wide range of professionals all over Greece and abroad. As of mid-2020, the Chapter's overall member base has exceeded 195 individuals of all genders. Satellite ACM-W chapters have also been promoted among student communities, such as the ACM-W Student Chapter at the Aristotle University of Thessaloniki in Greece.

The Greek ACM-W Chapter organizes every year, since 2019, the Summit on Gender Equality in Computing. The Summit aims at promoting gender-equal access to computer-related scientific frontiers, equally encouraging and educating women and men to achieve their goals and utilize their potential in digital professions. The goal of the Summit is also to celebrate and disseminate the achievements of computer professionals in a fair and gender-equal way. The community has shown its resilience during the pandemic, by organizing the 2nd Summit on Gender Equality in Computing in June 2020 as a fully online conference. Through a series of activities (including invited talks, a workshop, a panel, and an industry session), attendees had the opportunity to become acquainted with current and emerging topics and important achievements in computer science. Also during the Covid pandemic, other forms of activities were supported, such as a speed-mentoring event organized by our local ACM-W Student Chapter at which several Greek ACM-W Chapter members participated and encouraged younger scientists.

What advice would you offer a younger colleague just starting out in the computing field?

Skilled data scientists are in high demand in many of the world's most advanced and fast- expanding markets. Virtually all industries are seeking to harness the power of data, in order to understand and extract valuable knowledge to make their business more intelligent, competitive and sustainable. Domains such as healthcare, manufacturing, e-commerce and finance—but also governments and public services—are investing heavily in data science. A young data scientist now has many different paths that can lead to a rewarding career. It is challenging to predict the future and the emergence of rapidly-evolving data technologies; however, younger data scientists who gain advanced hard and soft skills will be ready to embark on careers in tomorrow’s data science ecosystems. These skills should be carefully advanced with a high-quality educational and soft skills development plan. Specialized MSc courses and PhD programmes can offer to a candidate a valuable set of skills and acquaintance with state-of-the-art and emerging data science and data technologies.

Data science education should be aligned with knowledge in the areas of machine learning, since data feed the algorithms, and the many roles of algorithm developer, data engineer, business intelligence analyst, or enterprise analytics manager have their own continuous learning demands. Such credentials are highly sought after in the overall ecosystem of markets, industries, academia, and policymaking stakeholders.

Beyond the scientific knowledge that is necessary, being a successful data and web scientist requires many soft skills such as communication capabilities, teamwork flexibility, interdisciplinarity, creative thinking and insightful data interpretation. Younger data scientists who have these hard and soft skills should also be ready to adapt, to evolve, to risk and to support their data-driven solutions throughout their careers. Above all, it is important to always seek data authenticity, integrity and quality. I’m confident that communities of young data scientists will proceed with a data science agenda aimed at ethical and social good.