A-posteriori provenance-enabled linking of publications and datasets via crowdsourcing

This paper aims to share with the digital library community different opportunities to leverage crowdsourcing for a-posteriori capturing of dataset citation graphs. We describe a practical approach, which exploits one possible crowdsourcing technique to collect these graphs from domain experts and proposes their publication as Linked Data using the W3C PROV standard. Based on our findings from a study we ran during the USEWOD 2014 workshop, we propose a semi-automatic approach that generates metadata by leveraging information extraction as an additional step to crowdsourcing, to generate high-quality data citation graphs. Furthermore, we consider the design implications on our crowdsourcing approach when non-expert participants are involved in the process<br/

Crowdsourcing Paper Screening in Systematic Literature Reviews

Literature reviews allow scientists to stand on the shoulders of giants, showing promising directions, summarizing progress, and pointing out existing challenges in research. At the same time conducting a systematic literature review is a laborious and consequently expensive process. In the last decade, there have a few studies on crowdsourcing in literature reviews. This paper explores the feasibility of crowdsourcing for facilitating the literature review process in terms of results, time and effort, as well as to identify which crowdsourcing strategies provide the best results based on the budget available. In particular we focus on the screening phase of the literature review process and we contribute and assess methods for identifying the size of tests, labels required per paper, and classification functions as well as methods to split the crowdsourcing process in phases to improve results. Finally, we present our findings based on experiments run on Crowdflower

Unproceedings of the Fourth .Astronomy Conference (.Astronomy 4), Heidelberg, Germany, July 9-11 2012

The goal of the .Astronomy conference series is to bring together astronomers, educators, developers and others interested in using the Internet as a medium for astronomy. Attendance at the event is limited to approximately 50 participants, and days are split into mornings of scheduled talks, followed by 'unconference' afternoons, where sessions are defined by participants during the course of the event. Participants in unconference sessions are discouraged from formal presentations, with discussion, workshop-style formats or informal practical tutorials encouraged. The conference also designates one day as a 'hack day', in which attendees collaborate in groups on day-long projects for presentation the following morning. These hacks are often a way of concentrating effort, learning new skills, and exploring ideas in a practical fashion. The emphasis on informal, focused interaction makes recording proceedings more difficult than for a normal meeting. While the first .Astronomy conference is preserved formally in a book, more recent iterations are not documented. We therefore, in the spirit of .Astronomy, report 'unproceedings' from .Astronomy 4, which was held in Heidelberg in July 2012.Comment: 11 pages, 1 figure, .Astronomy 4, #dotastr

Innovation Initiatives in Large Software Companies: A Systematic Mapping Study

To keep the competitive advantage and adapt to changes in the market and technology, companies need to innovate in an organised, purposeful and systematic manner. However, due to their size and complexity, large companies tend to focus on maintaining their business, which can potentially lower their agility to innovate. This study aims to provide an overview of the current research on innovation initiatives and to identify the challenges of implementing the initiatives in the context of large software companies. The investigation was performed using a systematic mapping approach of published literature on corporate innovation and entrepreneurship. Then it was complemented with interviews with four experts with rich industry experience. Our study results suggest that, there is a lack of high quality empirical studies on innovation initiative in the context of large software companies. A total of 7 studies are conducted in such context, which reported 5 types of initiatives: intrapreneurship, bootlegging, internal venture, spin-off and crowdsourcing. Our study offers three contributions. First, this paper represents the map of existing literature on innovation initiatives inside large companies. The second contribution is to provide an innovation initiative tree. The third contribution is to identify key challenges faced by each initiative in large software companies. At the strategic and tactical levels, there is no difference between large software companies and other companies. At the operational level, large software companies are highly influenced by the advancement of Internet technology. Large software companies use open innovation paradigm as part of their innovation initiatives. We envision a future work is to further empirically evaluate the innovation initiative tree in large software companies, which involves more practitioners from different companies

Crowdsourcing Linked Data on listening experiences through reuse and enhancement of library data

Research has approached the practice of musical reception in a multitude of ways, such as the analysis of professional critique, sales figures and psychological processes activated by the act of listening. Studies in the Humanities, on the other hand, have been hindered by the lack of structured evidence of actual experiences of listening as reported by the listeners themselves, a concern that was voiced since the early Web era. It was however assumed that such evidence existed, albeit in pure textual form, but could not be leveraged until it was digitised and aggregated. The Listening Experience Database (LED) responds to this research need by providing a centralised hub for evidence of listening in the literature. Not only does LED support search and reuse across nearly 10,000 records, but it also provides machine-readable structured data of the knowledge around the contexts of listening. To take advantage of the mass of formal knowledge that already exists on the Web concerning these contexts, the entire framework adopts Linked Data principles and technologies. This also allows LED to directly reuse open data from the British Library for the source documentation that is already published. Reused data are re-published as open data with enhancements obtained by expanding over the model of the original data, such as the partitioning of published books and collections into individual stand-alone documents. The database was populated through crowdsourcing and seamlessly incorporates data reuse from the very early data entry phases. As the sources of the evidence often contain vague, fragmentary of uncertain information, facilities were put in place to generate structured data out of such fuzziness. Alongside elaborating on these functionalities, this article provides insights into the most recent features of the latest instalment of the dataset and portal, such as the interlinking with the MusicBrainz database, the relaxation of geographical input constraints through text mining, and the plotting of key locations in an interactive geographical browser