CLOSED Call for Papers: Special Issue on Collaborative Aspects of Open Data in Software Engineering
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Submissions Due: 7 May 2021
Submissions due: 7 May 2021
Publication: January/February 2022
High-quality data is becoming increasingly important for software engineers in the design and implementation of today’s software, for example, as an input to machine-learning algorithms and visualization- and analytics-based features. Open data–data shared under a license that gives users the right to study, process, and distribute the data to anyone and for any purpose–offers a mechanism for addressing this need. Data may be crowdsourced, shared by government agencies, or shared between commercial entities.
By sharing the data openly and collaborating on its development, enrichment, and maintenance, organizations can both raise the quality of the data and accelerate their product innovation, while also lowering the related maintenance costs. The sharing of open data can also help to catalyze new entrepreneurial efforts, increase transparency and accountability, and transform incumbents as well as public organizations through improved decisions and services.
With this theme issue of IEEE Software, we invite papers with a focus on the collaborative aspects of open data in software engineering and how these aspects can help or hinder practitioners within both private and public organizations to exploit the potential benefits. We ask for original articles that provide new ideas, methods, and insightful experiences that can guide and support software engineers in the collaboration and co-development of open data. We invite in-depth case studies, experience reports, and analytical contributions, aiming to shed light in this multifaceted topic, covering any collaborative aspects of open data in software engineering. Topics include, but are not limited to:
Challenges and solutions for open-data practice. For example, processes, methods, and tools that enable the collection, production, reproduction, enrichment, publication, brokerage, and co-development of open data between various actors, including governments, researchers, companies, citizens, journalists, students, NGOs, librarians, and intermediaries
Policies, governance, and decision-making for how to collect, produce, publish, share, and co-develop open data
Identifying and sharing data with different levels of openness and guidance for stakeholders’ decisions in this respect
The role of public, private, and societal stakeholders in the collection, production, sharing, brokerage, co-development, and usage of open data
The role of open standards in enabling the collection, production, reproduction, enrichment, publication, brokerage, and co-development of open data
Measures and metrics of data quality, as well as characteristics of collaboration and co-development, such as its productiveness, robustness, and diversity among the collaborating actors
Similarities and potential lessons learned from the collaborative practices present in Open Source Software communities and other types of communities or ecosystems
Legal and ethical aspects of open data, particularly in relation to the privacy and integrity of data providers
Issues related to the needs for data for artificial intelligence and machine learning research and practice, and which role open data may play in this context
Manuscripts must not exceed 3,000 words, including figures and tables, which count for 250 words each. Submissions in excess of these limits may be rejected without refereeing. The articles we deem within the theme and scope will be peer reviewed and are subject to editing for magazine style, clarity, organization, and space. Be sure to include the name of the theme you’re submitting for.
Articles should have a practical orientation and be written in a style accessible to practitioners. Overly complex, purely research-oriented or theoretical treatments aren’t appropriate. Articles should be novel. IEEE Software doesn’t republish material published previously in other venues, including other periodicals and formal conference or workshop proceedings, whether previous publication was in print or electronic form.