使用 owlready 2 从 dataframe 将新个体添加到现有本体

Question

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I have the following dataframe

import pandas as pd

data = [['onto.modify', 'onto.ModificationAction1']]
df = pd.DataFrame(data, columns=['queries', 'corpus'])

       queries                corpus
0      onto.modify            onto.ModificationAction1

The elements of corpus column are Individuals of a particular Class of an ontology called onto

I want to add the elements of the queries column as individuals to the same Class that the elements of the corpus column belong to.

For example if the onto.ModificationAction1 belong to the onto.Thing class the same must be for the onto.modify

Initially, I loop over the corpus columns to find in which Class each Individual belongs to:

for elements in df["corpus"]:
    print (element.is_a)

However, I get back:

AttributeError: 'str' object has no attribute 'is_a'

So how to solve this error and eventually perform what I am describing above in the example?

Answer 1

Error happens because values in your dataframe are strings, not individuals. You have to look up an individual based on its name using search() or search_one() (see documentation ). This code should do the job:

import pandas as pd
import owlready2

data = [['onto.modify', 'onto.ModificationAction1']]
df = pd.DataFrame(data, columns=['queries', 'corpus'])

onto = owlready2.get_ontology("http://test.org/onto.owl")


class Action(owlready2.Thing):
    namespace = onto


modification_action = Action(name="ModificationAction1")

for row in df.iterrows():
    row_series = row[1]
    # Trow away ontology name, get only individual name
    corpus_individual_name = row_series['corpus'].split('.', 1)[1]
    # Find individual
    corpus_individual = onto.search_one(iri=onto.base_iri + corpus_individual_name)
    # Get individual classes
    corpus_classes = corpus_individual.is_a
    # Trow away ontology name, get only individual name
    query_individual_name = row_series['queries'].split('.', 1)[1]
    # Create new individual with first class of old individual
    new_individual = corpus_classes[0](name=query_individual_name)
    # In case old individual is multiclass, add remaining classes to new individual
    for corpus_class in corpus_classes[1:]:
        new_individual.is_a.append(corpus_class)

for i in onto.individuals():
    print(i, i.is_a)

You can see the new individual in the output along with its class.

onto.ModificationAction1 [onto.Action]
onto.modify [onto.Action]

PS: I'm assuming here that you have only one ontology -- onto . If not, you should either 1) Have a lookup dictionary for ontologies to map "onto" into actual ontology object/IRI, or 2) instead of “onto.” prefix specify full IRI in your dataframe and lookup ontology by IRI.