Ontologies & Reasoning in Enterprise Applications

This is a revised manuscript after a "reject and resubmit".

In the first round (reviews below), the paper was submitted as a full paper.

Solicited review by Rama Akkiraju:

This paper discusses the arguments and business case for using ontologies and semantic technologies in enterprise applications. As someone who had worked in this area and made unsuccesful attempts to commercialize the technologies developed in this space in a large enterprise integration company I agree with the arguments made by the authors to a large extent. The arguments made and business case discussed are valid. If I were to write a paper on my own experiences, the arguments would look very similar. In addition to the arguments made in the paper, I'd point out two more reasons for the lack of adoption of semantic technologies which need highlighting. Lack of adoption of semnatic technologies in the past few years is attributable to the lack of tools that offer higher levels of abstraction. OWL and other semantic languages are very complex to an average user/developer. The audience for most ontology editing tools even today is power users who know OWL and XML and logic programming. This is not the audience who is expected to create ontologies. Often, subject matter experts of domains are the most suitable people for authoring ontologies. They usually have no technical expertise in complex and deep computer science subjects. So, the entire tooling in ontology domain catered to the wrong audience to start with. This led to the lackluster adoption of semantic technologies.

Another reason for lack of adoption of semantic technologies is the need to build ontologies upfront. This in combination with tools that do not cater to the right audience, makes it very hard to get started with anything. Learning ontologies from domain dictionaries and to build them over time is looked at as a solution. This area of 'ontology learning' is not discussed in the paper. It needs a mention and citing of some papers. Here is one reference to ontology learning.

Hui Guo, Anca Ivan, Rama Akkiraju, Richard Goodwin: Learning Ontologies to Improve the Quality of Automatic Web Service Matching ICWS 2008: 337-344

Solicited review by anonymous reviewer:

The paper discusses the advantages and the challenges of using ontology & reasoning technologies in enterprise applications and presents two previous projects that set out to address some of the challenges. While the paper lucidly delineates several concepts – for example, the eight value-adding features in the first part of the paper, I think the paper does not include enough research contribution to warrant publish.

Firstly, the claims made in the paper are often made without referencing supporting evidence and data. As a result of the lack evidence, the claims in the paper sound speculative and subjective. For example, Section 4, which illustrates the benefits of using ontology, does not present any evidence aside from a few short introductory sentences that loosely reference existing projects.

Second, the paper's claims are often overly broad generalizations that need to be much more focused and specific. For example, Section 4 starts with the sentence, "arbitrary combination of value-adding features can create new business scenarios", and then presents two use-cases without any further elaboration. Rather than broadly referencing "new business", the paper should instead list the specific areas that would benefit and why. The description of the use cases in Section 4, for example, could be improved by discussing 1) problems that each use case sought to solve 2) how ontology-based solutions were implemented in each case 3) actual benefits acquired from the ontology-based solutions. Additionally, rather than vaguely claiming that ontology-based solutions "improves productivity and EIM" in Section 4, the paper should reference specific statistic that highlight improvements in key aspects of productivity and EIM that were achieved through ontology-based solutions.

Finally, the paper needs more insights and analysis, as opposed to simply enumerating the pros and cons of ontology-based technologies, which have already been discussed extensively in the existing literature. With that in mind, Section 6 in particular could be improved considerably. Instead of introducing the authors' past projects, it should thoroughly survey the existing solutions to the challenges and provide novel insights concerning what aspects of the challenges have been addressed and how, and which problems researchers still need to address, etc.

Overall, the paper needs to venture further into the realm of original analysis, and do more than simply reiterate what is already known. In order to achieve this, the paper should contain more concrete evidence and data from scientific methods and more insights and analysis from the author