@inproceedings{fdi:010084430,
  title = {{I}dentifying explicit and tacit knowledge in a life science knowledge base [poster]},
  author = {{S}aoud, {J}. and {G}utierrez, {A}. and {H}uchard, {M}. and {S}ilvie, {P}ierre and {M}artin, {P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}n alternative to the use of synthetic pesticides and antibiotics in agriculture is to spray local plants extracts, in aqueous or essential oil form. {T}o this end, the {K}nomana knowledge base [1] compiles various knowledge sets on plant use such as the 42000 descriptions of pesticidal plant uses for plant, animal, and public health presented in the literature. {A}s the {O}ne {H}ealth approach dictates to be aware of the additional uses of these pesticidal plants to prevent their unintended effects on the animal, the human, and their environment, the challenge for the domain experts (e.g. entomologist, pathologist) is thus to identify the pesticidal plants in {K}nomana considering the {O}ne {H}ealth approach. {W}ith the aim to present knowledge to the expert using a compact and comprehensive formalism, in [2], we computed the {D}uquenne-{G}uigues basis ({DGB}) of implications on an excerpt of {K}nomana, in which each plant is described using its taxonomy (i.e. species, genus, and family), to be consumed as food, and to be used in medical care. {T}he {DGB} method is based on {F}ormal {C}oncept {A}nalysis ({FCA}) and provides a cardinality-minimal set of non-redundant implications. {B}y considering a reduced knowledge set, this work identifed 3 types of knowledge elements in the implications: knowledge on plant use at diverse taxonomy levels (e.g. {P}lants from {M}eliaceae family are not consumed as food), plant taxonomy (e.g. {A} plant from {S}alvia genus is from {L}amiaceae family), and side effect of the knowledge set, e.g. a plant from the {P}iperaceae family is from the genus {P}iper. {T}his latter illustration is not in accordance with taxonomic referential and thus informs on the extend of knowledge inserted in {K}nomana. {M}oreover, as plant taxonomy is known by the experts, removing it from the implications eases their reading but makes it tacit knowledge. {I}mplementing this method to select pesticidal plants requires to consider {K}nomana as a multidimensional (ternary) dataset, and thus to use the extension of {FCA} devoted to this kind of knowledge discovery, i.e. {R}elational {C}oncept {A}nalysis ({RCA}). {T}herefore, computing the {DGB} of implications based on {RCA} provides linked set of implications which includes the existential quantifer. {C}onverting this formulation as practical expression is a need for the domain experts. {T}his poster describes the product line that formulates {K}nomana knowledge on pesticidal plants as implications, from which the implicit knowledge elements were removed and the side effects are highlighted to alert the expert. {T}his product line was developed using the library fca4j from {C}ogui software (http://www.lirmm.fr/cogui/), that provides the {RCA} based {DGB} of implications, and using a post-process which differentiates the 3 types of knowledge elements within the implications. {A}s an illustration, this poster presents the implications on {S}podoptera frugiperda, a highly polyphagous insect that is close to invade {S}outh of {E}urope. {T}he perspective of this work is to identify pesticidal {E}uropean plants species that share chemical components similarities with plants used to control this pest in its native area.},
  keywords = {},
  numero = {},
  pages = {1  multigr.},
  booktitle = {},
  year = {2021},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084430},
}