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Sharing and reusing data in research is a welcome and encouraged practice since it maximises the scientific outcomes given limited financial, material and human resources. Interdisciplinary research is usually benefitted from this practice, reuniting researchers and data from two or more disciplines to advance fundamental understanding or tackle problems whose solution is beyond the limit of an individual body of knowledge. In this work, we discuss the challenges of associating localisation with other data types, particularly genetic data, in a project involving Crop Science and Geospatial Information Science disciplines that aim to improve the understanding of how geographical, environmental and anthropocentric factors affect the genetic variation in a neglected and underutilised crop called Bambara groundnut.
This is an article intended for the OGRS2016 Collection - session Open computational landscape genetics