As digital libraries make the dissemination of research publications easier, they also enable the propagation of invalid or unreliable knowledge. Examples of relevant problems include: retraction and unknowing/unintentional citation and reuse of retracted papers; propagation of errors in literature and scientific databases; non-reproducible papers; known domain-specific issues such as cell line contamination; bias in research datasets and publications; systematic reviews that come up with different conclusions for the same problem at the same time. In the digital environment, which facilitates broad interdisciplinary reuse beyond the originating scientific community, marking known problems and tracing the impact on dependent and follow-on works is an important, but under-addressed problem. Further, context-specific information inside a paper may not be immediately reusable when extracted by automated processes, leading to apparent contradictions. Current mitigating approaches use the underlying reasoning for information retrieval, develop new infrastructures analyzing the reasoning or certainty of statements, or use visualization to highlight possible discrepancies. There were 9 papers submitted for peer-review to this workshop. Out of these, 6 papers were accepted for this volume, 3 as regular papers and 3 as short papers.
Florian Boudin, University of Nantes, France Gully Burns, Chan Zuckerberg Initiative, USA Joel Chan, University of Maryland, USA Tim Clark, University of Virginia, USA Jennifer D’Souza, Leibniz Information Centre for Science and Technology University Library (TIB), Germany Edward Fox, Virginia Tech, USA Nancy Green, University of North Carolina Greensboro, USA Hermann Kroll, Technical University of Braunschweig, Germany Allard Oelen, L3S Research Center, Germany Halie Rando, University of Colorado Anschutz Medical Campus, USA Thomas Stoeger, Northwestern University, USA
Markus Stocker, Leibniz Information Centre for Science and Technology, Germany