Related papers: On the Challenges of Collaborative Data Processing
User experience (UX) has undergone a revolution in collaborative practices, due to tools that enable quick feedback and continuous collaboration with a varied team across a design's lifecycle. However, it is unclear how this shift in…
Large-scale databases of human activity in social media have captured scientific and policy attention, producing a flood of research and discussion. This paper considers methodological and conceptual challenges for this emergent field, with…
Wikidata is one of the most edited knowledge bases which contains structured data. It serves as the data source for many projects in the Wikimedia sphere and beyond. Since its inception in October 2012, it has been increasingly growing in…
Wikipedia is the largest online encyclopedia, used by algorithms and web users as a central hub of reliable information on the web. The quality and reliability of Wikipedia content is maintained by a community of volunteer editors. Machine…
With the advent of open source software, a veritable treasure trove of previously proprietary software development data was made available. This opened the field of empirical software engineering research to anyone in academia. Data that is…
In this paper, we propose a data collaboration analysis method for distributed datasets. The proposed method is a centralized machine learning while training datasets and models remain distributed over some institutions. Recently, data…
In recent decades the analysis of data has become increasingly computational. Correspondingly, this has changed how scientific and statistical work is shared. For example, it is now commonplace for underlying analysis code and data to be…
Large scientific collaborations, often with hundreds or thousands of members, are an excellent opportunity for a case study in best practices implemented while developing open source hardware. Using a publicly available design of timing…
The development of digital humanities necessitates scholars to adopt more data-intensive methods and engage in multidisciplinary collaborations. Understanding their collaborative data behaviors becomes essential for providing more curated…
The vast amount of data produced everyday (so-called 'digital traces') and available nowadays represent a gold mine for the social sciences, especially in a computational context, that allows to fully extract their informational and…
Crowdsourced data supports real-time decision-making but faces challenges like misinformation, errors, and contributor power concentration. This study systematically examines trust management practices across platforms categorised as…
Big data have the characteristics of enormous volume, high velocity, diversity, value-sparsity, and uncertainty, which lead the knowledge learning from them full of challenges. With the emergence of crowdsourcing, versatile information can…
This article first lists reasons why - in the long term or when creating a new knowledge base (KB) for general knowledge sharing purposes - collaboratively building a well-organized KB does/can provide more possibilities, with on the whole…
A simple dynamical model of collective edit activity of Wikipedia articles and their content evolution is introduced. Based on the recent empirical findings, each editor in the model is characterized by an ability to make content edit,…
Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with…
Social media is nearly ubiquitous in modern life, raising concerns about its societal impacts -- from mental health and polarization to violence and democratic disruption. Yet research on its causal effects is still inconclusive: Various…
In recent years there has been an increasing trend in which data scientists and domain experts work together to tackle complex scientific questions. However, such collaborations often face challenges. In this paper, we aim to decipher this…
Wikidata is one of the most important sources of structured data on the web, built by a worldwide community of volunteers. As a secondary source, its contents must be backed by credible references; this is particularly important as Wikidata…
Recently, we have been witnessing huge advancements in the scale of data we routinely generate and collect in pretty much everything we do, as well as our ability to exploit modern technologies to process, analyze and understand this data.…
The discovery of phenomena in social networks has prompted renewed interests in the field. Data in social networks however can be massive, requiring scalable Big Data architecture. Conversely, research in Big Data needs the volume and…