It is a fact that, when developing a new application, it is virtually impossible to reuse, as-is, existing datasets. This difficulty is the cause of additional costs, with the further drawback that the resulting application will again be hardly reusable. It is a negative loop which consistently reinforces itself and for which there seems to be no way out. iTelos is a general purpose methodology designed to break this loop. Its main goal is to generate reusable Knowledge Graphs (KGs), built reusing, as much as possible, already existing data. The key assumption is that the design of a KG should be done middle-out meaning by this that the design should take into consideration, in all phases of the development: (i) the purpose to be served, that we formalize as a set of competency queries, (ii) a set of pre-existing datasets, possibly extracted from existing KGs, and (iii) a set of pre-existing reference schemas, whose goal is to facilitate sharability. We call these reference schemas, teleologies, as distinct from ontologies, meaning by this that, while having a similar purpose, they are designed to be easily adapted, thus becoming a key enabler of itelos.
翻译:事实是,在开发新应用程序时,几乎不可能重新使用现有数据集。这一困难是造成额外费用的原因,因为由此而产生的应用程序将难以再使用。这是一个消极的循环,它不断强化自己,似乎没有出路。iTelos是一个旨在打破这一循环的通用方法。它的主要目标是产生可重复使用的知识图(KGs),并尽可能地重复使用已有数据。关键假设是,KG的设计应该达到中间意义,即设计应该在所有开发阶段都考虑到:(一) 要实现的目的,我们正式确定一套能力查询,(二) 一套可能从现有KGs提取的预存在的数据集,(三) 一套预先存在的参考系统,目的是便利可再利用性。我们称之为这些参考计划,即电算,有别于各种类型,这意味着,在进行这一设计时,可以很容易地将之变成一个关键目标。