Peer-production system or collaborative ontology engineering effort

Abstract

Wikidata promises to reduce factual inconsistencies across all Wikipedia language versions. It will enable dynamic data reuse and complex fact queries within the world's largest knowledge database. Studies of the existing participation patterns that emerge in Wikidata are only just beginning. What delineates most of the contributions in the system has not yet been investigated. Is it an inheritance from the Wikipedia peer-production system or the proximity of tasks in Wikidata that have been studied in collaborative ontology engineering? As a first step to answering this question, we performed a cluster analysis of participants' content editing activities. This allowed us to blend our results with typical roles found in peer-production and collaborative ontology engineering projects. Our results suggest very specialised contributions from a majority of users. Only a minority, which is the most active group, participate all over the project. These users are particularly responsible for developing the conceptual knowledge of Wikidata. We show the alignment of existing algorithmic participation patterns with these human patterns of participation. In summary, our results suggest that Wikidata rather supports peer-production activities caused by its current focus on data collection. We hope that our study informs future analyses and developments and, as a result, allows us to build better tools to support contributors in peer-production-based ontology engineering.

Wikidatians are Born: Paths to Full Participation in a Collaborative Structured Knowledge Base

“…This distinguishes Wikidata from previous examples of peerproduction systems, e.g. Wikipedia, and of collective ontology engineering projects, such as the ones mentioned in [12], and situates it at the intersection of the two typologies [24]. Previous analogue examples, e.g.…”

“…A similar distribution can be found also in the revision scope. Only < 2% has ever edited any Properties and Items functioning as classes [24] …”

Provenance Information in a Collaborative Knowledge Graph: An Evaluation of Wikidata External References

“…Beyond human editors, who can be registered or contribute anonymously, pieces of software called bots carry out a broad range of tasks, adding and maintaining content. Whereas human editors are the main contributors to the conceptual structure of Wikidata [18], bots perform more when it comes to adding and modifying content and can often add large batches of statements in one go [24]. No study has examined yet the differences between bot and human contributions in Wikidata in terms of quality.…”

NECKAr: A Named Entity Classifier for Wikidata

“…To the best of our knowledge, at the time of writing this paper, the most recent version of DBPedia was published in April 2016, and the latest evaluated version of YAGO in September 2015, whereas Wikidata provides a weekly data dump. Even though all three KBs (Wikidata, DBpedia, and YAGO3) are based on Wikipedia, Wikidata also contains information about entities and relationships that have not been simply extracted from Wikipedia (YAGO and DBpedia extract data predominantly from infoboxes) but collaboratively added by users (Müller-Birn et al 2015). Although the latter feature might raise concerns regarding the quality of the data in Wikidata, for example due to vandalism (Heindorf et al 2015), we find that the currentness of information far outweights these concerns when using Wikidata as basis for a named entity classifying framework and as a knowledge base in particular.…”