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Jaihyun Park

Rethinking Reuse in Data Lifecycle in the Age of Large Language Models

In the world we are living in, a digital world, some data slips past our awareness, but very little data ever truly disappears. As we, information scientists, are concerned with reproducibility and responsibility of research, data lifecycle models have been developed to manage the complexity. To foster open, transparent, and collaborative science, data is often archived in a repository at the end of the project according to such data lifecycle models. This is often followed by the last step of the lifecycle models, data reuse. Traditionally, this model is cyclical, with reused data leading to new questions and fueling subsequent rounds of research.

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Translation
Zhuoren Jiang

Can AI Help to Predict the Scholarly Impact of New Scientific Papers?

This study explores how artificial intelligence (AI), specifically deep representation learning, can predict the scholarly impact of new scientific papers without relying on citation data. Using the SciBERT model, the research introduces two key indicators—Topicality (τ) and Originality (σ)—to estimate the potential impact of newly published papers. The approach is validated using the COVID-19 Open Research Dataset, demonstrating that papers with high topicality or originality are more likely to gain scholarly attention. The findings suggest that AI can complement traditional citation-based metrics, particularly for early-stage research, offering insights into knowledge creation dynamics and interdisciplinary research potential.

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Translation
Angelica Lo Duca

Transforming Data Visualization into Data Storytelling: The S-DIKW Framework

In a landscape saturated with data, the challenge lies in making information meaningful. How data is structured, visualized, and contextualized determines whether it merely informs or truly influences perception and decision-making. However, raw data alone does not communicate meaning. Traditional data visualizations, such as bar charts, scatter plots, and heat maps, often fail to engage audiences emotionally and cognitively. This is where data storytelling emerges as a transformative approach.

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Translation
Fatima Espinoza Vasquez

Transforming Ourselves, Transforming Inequity: Reimagining Partnerships for Information Justice

Thinking of communities as “information poor” misrepresents the reality of systemic exclusion. Instead, marginalized communities have been intentionally and unintentionally excluded from mainstream information infrastructures. This exclusion is not due to a lack of knowledge on the part of marginalized communities but rather a reflection of structural barriers that limit access to institutionalized information flows. We need to recognize the existence and prevalence of information precarity, and then we need to radically alter how we plan and carry out projects, research, and outreach with—not for—marginalized communities.

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EducationTranslation
Meghan Dowell

The Cost of Clicks: Cultivating Data-Awareness and Ethical LMS Practices in Higher Education 

Many educational institutions use learning management systems (LMSs), which may track and analyze a student’s every click, assignment submission, and even location; this also makes them useful for learning analytics, the collection and analysis of student data in the name of supporting learning and teaching. While students may know that LMSs collect their data, they often don’t understand the extent of just how much data these systems collect! Yet, it’s not hard to imagine what the scope of LMS data collection means for student privacy. This imbalance highlights the urgent need for greater transparency and critical data education in the use of educational technologies. 

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Translation
Manika Saha

Understanding Cyberbullying targeting women in Bangladesh from complex social-ecological lens

Our analysis raises critical questions: Why do segments of the general public express such hostility towards women in digital spaces? Are these sentiments a mere reflection of broader societal attitudes, or are they amplified by the affordances of online anonymity and lack of accountability? What structural interventions are necessary to dismantle these patterns of digital violence? Understanding these underlying factors is imperative to formulating sustainable strategies to combat cyberbullying.

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