This is a review for Uli Sattler’s article on OWL the Web Ontology language. The title “OWL” looks a little strange in the table of contents, so I’d be inclined to change it to “The Web Ontology Language (OWL)”. Most of my comments are at this level, so indicates that the article is fine. I have only a few other comments.

As a background to how OWL works this K-Blog works for me. This article takes the reader on an introductory tour of OWL. It gives a genral background on OWL. It concentrates on the reasoning side of OWL – what a reasoner does. A few lines of introduction to say what the purpose the article is and what it wil not do would be useful. for instance, a guide to OWL exspressivity and modelling tips for OWL is not the purpose of this article. A link to Phil Lord’s KBlog on components and Matt Horridge’s on OWL syntax would be good.

Whilst OWL is probably the most prominent ontology language of the moment, within the biology context that is the topic of the Ontogenesis Kblog, the OBOF format should be mentioned (along with a link to the OBOF K-Blog). In this community, OBOF is very widely used and this should be acknowledged.

It would be useful to give a simple statement of what an axiom is. The word “model” and its meaning within the DL world may need more attention as well (or a warning to just overlook it). Model is used in this community in its much more general sense.

“where OWL and reasoning is used purely to make sure that the things said about classes and the resulting entailed class hierarchy are correct” – Is OWL natively used in SnoMED? I thought it used a DL, but not OWL as such. Also, “correct” needs care as it is checked for logical correctnesss rather than domain of interest correctnerss.

Minor:

• “are important: OWL comes in” → sentence change instead of colon.
• “, properties, and inviduals” → individuals
• “chose whatever relation you like” → choose
• “help us unterstand ” → understand
• “Coming back to Protege” → new paragraph at onset of this sentence.
• “currently recides in” → resides
• “Both have clearly advantages ” clearly have

reviewed by robert Stevens

School of Computer Science, University of Manchester.

This is a review for Uli Sattler’s article on OWL the Web Ontology language. The title “OWL” looks a little strange in the table of contents, so I’d be inclined to change it to “The Web Ontology Language (OWL)”. Most of my comments are at this level, so indicates that the article is fine. I have only a few other comments.

As a background to how OWL works this K-Blog works for me. This article takes the reader on an introductory tour of OWL. It gives a genral background on OWL. It concentrates on the reasoning side of OWL – what a reasoner does. A few lines of introduction to say what the purpose the article is and what it wil not do would be useful. for instance, a guide to OWL exspressivity and modelling tips for OWL is not the purpose of this article. A link to Phil Lord’s KBlog on components and Matt Horridge’s on OWL syntax would be good.

Whilst OWL is probably the most prominent ontology language of the moment, within the biology context that is the topic of the Ontogenesis Kblog, the OBOF format should be mentioned (along with a link to the OBOF K-Blog). In this community, OBOF is very widely used and this should be acknowledged.

It would be useful to give a simple statement of what an axiom is. The word “model” and its meaning within the DL world may need more attention as well (or a warning to just overlook it). Model is used in this community in its much more general sense.

“where OWL and reasoning is used purely to make sure that the things said about classes and the resulting entailed class hierarchy are correct” – Is OWL natively used in SnoMED? I thought it used a DL, but not OWL as such. Also, “correct” needs care as it is checked for logical correctnesss rather than domain of interest correctnerss.

Minor:

• “are important: OWL comes in” → sentence change instead of colon.
• “, properties, and inviduals” → individuals
• “chose whatever relation you like” → choose
• “help us unterstand ” → understand
• “Coming back to Protege” → new paragraph at onset of this sentence.
• “currently recides in” → resides
• “Both have clearly advantages ” clearly have

reviewed by robert Stevens

School of Computer Science, University of Manchester.

This is a review on community driven ontology development, by frank gibson and James Malone. this is a good article topic for the Ontogenesis Kblog — ontologies need to be used, and this usually means a community; though an ontology can be built by one person to be used in an application (so the users of the application ar the community and therefore somewhat indirect to the ontology). I think that starting the article with the (perhaps obvious) statement that if an ontology is to be used by a wider community then it meeds to engage that community would be good. There are few, if any, ontologies that are actually used widely that have small community engagement and/or are not collaboratively built in some way. It may be useful to distinguish between community involvement and collaboration. It is possible to have community engagement without collaborative authoring and it is possible to have collaborative authoring without community engagement (here I would say that feedback via issue trackers as OBO often do it is not collaborative authoring, but is a collaboration by commmunity engagement – and a useful one).

It might also be good to draw out the way many of the successful OBO ontologies do this sort of comunity driven aspect, especially where the dynamic nature of the authoring is an issue and what its consequences are. This might help talk about different types of engagement: Actual authoring; reporting of issues; etc. As the OBO process is pre-dominant in this field, it might be useful to describe their process more fully and this would link back to the drawing out of types of community engagement.

Finally, the article could do with some kind of conclusion, summary or wrapping up. Also, a further “how to” article on doing community driven development would be good.

Minor Comments

• with slightly different defintions. = definitions.
• – the The Open Biomedical Ontology = double word
• – Foundry acts as a registry = a repository actual holds the artefact a registary simply catalogues the thing; I suspect the OBO Foundary would be a repository, though I’m not the person to say.

by Robert Stevens

This is a review of What is an upper level ontology?

In this article, Robert nicely covers the different aspects that upper level ontologies need to consider to prescribe a coherent view of the world for its adopters.

Here are some specific comments that need to be addressed:

1. Instead of using electron as an example, i would use something more concrete – like a  car.

2. Explain the notation for ” )1,2)”

3. Elaborate on abstract entities – why are these important, and give some examples.

This is a review of What is an ontology? by Robert Stevens, Alan Rector and Duncan Hull

This article could be split quite neatly in two articles. One is an excellent article that begins about a third of the way through the full piece. It covers the technical aspects of ontology building: subsumption hierarchies; necessary vs necessary and sufficient conditions for class membership; disjointness; relations; upper ontologies and their usefulness in restricting the choice of appropriate relations. It draws heavily on upper ontologies developed by philosophers (at least some of them realists) and shows why they are useful. It concludes with a clear and strong case for why good ontologies are needed in the biosciences. I have no argument with this article.

The other is, to me at least, a rather confusing attempt to argue that ontologies consist of concepts, as opposed to statements about reality. I find these arguments difficult to square with some of the statements made in the rest of the article. However, I’m also not convinced that there is much difference between the author’s position and a realist stance. There argument hinges on the subtle issue of the reality of classes and they don’t make other arguments commonly made against a realist stance – for example, the ‘argument from intellectual modesty’ (Smith et al., 2006), or the belief that ontology terms should simply follow the use of terms in language. In fact, they clearly argue for ontology as a means to overcome the latter:

“Ontology should be distinguished from thesauri…”

“Human beings can give multiple labels to … categories. This habit of giving multiple labels to the same category and the same label to different categories (polysemy) leads to grave problems…”

Their argument begins with what strikes me as a cheap rhetorical trick designed to close down debate:

“The definition here will not suit a lot of people and upset many (especially use of the word “concept”); We make no apology for this situation, only noting that the argument can take up resources better used in helping biologists describe and use their data more effectively.”

If the authors think this discussion is a waste of resources, then why bother spending a few paragraphs making their case? I suspect that they do actually care about the argument because they worry about the implications of taking a realist stance. If so, it would have been interesting to hear some of those concerns (on the realist status of maths for example) made more explicit.

There is also a notable lack of reference to any sources of opposing argument. For those who wish to pursue this argument further, waste of time though it might be, some references to counter arguments would be good. Either of these references (or both) would do nicely:

Smith, et al., 2006. Towards a reference terminology for ontology research and development in the biomedical domain. Proceedings of KR-MED 2006

Smith, 2004. Beyond Concepts: Ontology as Reality Representation. Proceedings of FOIS 2004

Of the arguments against a realist stance, the weakest uses a straw man:

“… with a computer science ontology … there is less concern with a true account of reality as it is information that is being processed, not reality.”

Who could argue? Surely the question is whether the information being processed is making assertions about reality or not? The authors case would be stronger if this line were deleted.

The heart of their argument is stated here:

“As human beings, we put these objects into categories or classes. These categories are a description of that which is described in a body of data. The categories themselves are a human conception. We live in a world of objects, but the categories into which humans put them are merely a way of describing the world; they do not themselves exist.”

A perhaps pedantic point: are classes “described in a body of data”? I would have thought it more likely they are assertions about reality that are a reasonable scientific interpretation of a body of data. This confusion of data and its interpretation as assertions occurs consistently throughout the article.

More importantly, what might it mean to state that a class is real? Even the authors seem to agree that there is regularity in the universe, whether we observe it or not. For example, later in the article, they state that:

“Each instance of a ‘Helium’ object was not discovered in 1903; most helium atoms existed prior to that date, but humans discovered and labelled that category at that date.”

In 1903, humans discovered something that already existed: a class of atoms that share specific properties. Surely this means that a definition of the class ‘helium atom’ is making assertions about reality. Is this not different from some arbitrary class defined as including say: all helium atoms, horses, unicorns and two bedroom flats in North London?

This is not to say that there is only one true way to categorise any one object, or that there is a clean dividing line between classes we might be happy to define as Universals (Smith ), such as Helium atoms, and more contingent classes.

In the abstract, the authors argue that the debate over a realist vs a conceptual stance is a distraction that “… can take up resources better used in helping biologists describe and use their data more effectively.” Why might a realist stance be useful in helping scientists?

I believe that a realist stance is useful for ontologies made up of scientific assertions (for example, about chemistry, anatomy, or physiology), because it gives us a way to judge the quality of an ontology. If the ontology makes assertions that run counter to what we have good reason to believe is true, then it is misleading as a knowledge-base about science and its use in inference and grouping of annotations will produce results that we have good reason to believe are incorrect. Surely such an ontology would be bad – even when judged purely in practical terms.

Having said all this, I’m happy for this article to pass review for the Ontogenesis Knowledge Blog as long as the authors add references to opposing arguments. The authors may wish to consider taking into account my points with regard to the abstract and the apparent use of a straw-man argument. The article already provides an excellent introduction to the basic technical aspects of ontology building. With the addition of references to opposing arguments, the article and this review should provide a good starting point for those interested in exploring the realism vs conceptual(ism?) debate further.

Minor corrections:

foundary -> foundry

polysemy – missing initial bracket

License

This paper is an open access work distributed under the terms of the Creative Commons Attribution License 3.0, which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are attributed.

This is a review article

Comments

This is a clear, precise and well-written article describing the topic. It covers the motivation, process and technology of this approach for the development of a polyhierarchy while being clear that the axiomatisation necessary can have upfront costs. The article also makes clear use of figures demonstrating the use, as well as examples clarifying the more technical statements.

The latter half of the article addresses the issue of normalisation which is a development methodology that enables automatic maintenance of multiple inheritance ontologies. Well this is appropriate material for the article, it is not strictly necessary to completely normalize an ontology to use reasoning. The conclusions, in particular, could be improved in structure by saying that automatic maintaince can be supported by reasoning, and that normalisation exploits this fully.

Otherwise, an excellent article.

Minor Corrections

General

The section titles should use HTML headers, rather than the typographic markup used. Authors email should be hyperlinked.

Multiple Inheritance Ontologies

The effort is considerable, but worthy, as the automated reasoner is able to maintain the whole structure, avoiding human errors. Also, using such expressive axiomisation enables richer queries and other advantages.

Change to

is considerable requiring a richer axiomatisiation but worthwhile as the…

The more expressive axiomatisation also enables richer…

para 2 The difficult on maintaining -→ of maintaining

What is normalisation

Therefore, adequete and precise -→ However, adequete

OWL provides -→ Languages such as OWL provide

(e.g. part_of some (nucleus and (has_function only photosynthesis))

Would be nice to describe what this means in English.

“Normalised CL there” -→ what does CL mean in this context?

Advantages of …

Such modelling dynamic also results in a modular ontology -→ This modelling process

as such relation is the result of both having a common condition -→ as this relation is the result….

Conclusions

long term, a manual maintenance -→ long term, manual maintenance.

This is a review of the paper entitled Components of an Ontology, by Phil Lord.

This paper describes the three main components that can be found in an ontology (classes, instances, relations). Therefore it should be of interest to any newcomer to ontology development, as the confusion of which entities to use (especially instance vs. class) is a major problem when learning how to develop an ontology.

There is a difficult sentence at the end of introduction: “These components can be separated into two kinds; those that describe the Entities of the domain being described, and those which either enable the use of the ontology or describe the ontology itself.” There is no more references to such distinction in the rest of the paper. Also, it is not clear what are the components that describe the entities of the domain (axioms, individuals, classes?), the components that enable the use of the ontology (editors, APIs?) and the components that describe the ontology (metadata, metamodelling?).

The whole paper, although it describes general ontological components, has an OWL flavour, and the author should be explicit about it.

I would change the example for illustrating existential/universal, to an example where the class and the filler are different entities (not person/person), to make it more understandable.

I recommend accepting this paper.

This is a peer review of Ontological Annotation Of Data.

Overall, this is a very useful resource for people learning about how ontological annotations can be applied to data. There are just a few points below which, when addressed, should improve the overall clarity of the article.

As (strictly) Ontogenesis contains articles rather than blog posts, I suggest modifying the first sentence by removing the word “blogged”. I would also agree with the other reviewer that the links to articles should be replaced by DOIs before final publishing.

At the end of the last paragraph in the first section, you have the following large sentence: “When we consider the phenotype of the human from which samples were taken and the purpose of the study, and results generated by the study there are two axes of annotation to consider – that which relate to what is being assayed – the genetic content of the individual where the genes are, and what they may do, and the meta data about the individual: age, sex, physical characteristics, diseases they may have, and what was actually sampled – e.g. diseased or normal tissue, or peipheral blood.”

This sentence is a little long, and would be clearer with some changes. Perhaps making into two sentences, something like: “There are two axes of annotation when considering assays relating to the phenotype of the human from which samples were taken and the purpose of the study. The first axis is the genetic content of the individual, and what those genes may do. Secondly, annotation concerning the meta data about the individual: age, sex, physical characteristics, diseases they may have, and what was actually sampled – e.g. diseased or normal tissue, or peipheral blood.” This may need further re-wording to capture exactly what was meant.

When you describe GO, you have a note to yourself about a reference to GO: this needs to be added.

In the “Why do we do it” section, I would change “More or less specific annotation…” to “more specific or less specific annotation…” as the meaning is more clear that way. At the end of this same paragraph is the following sentence: “Annotations change over time  on the basis of emerging biological knowledge, and the content of the GO also changes as terms are added, or removed, annotations are therefore updated periodically.” In this case, the last bit of the sentence is difficult to understand. Perhaps change to something like “Annotations change over time on the basis of emerging biological knowledge. As a consequence, the annotation content of the GO is updated periodically as terms are added, or removed.”

Finally, to match how other articles are written, I don’t think you need to number your headings, especially as they aren’t all numbered in the first place. However, each heading should be a real HTML heading, e.g. <h2></h2> in order for the automated Table of Contents to be generated, as a TOC would be very useful in this type of article, which covers many topics.

This is a review of http://ontogenesis.knowledgeblog.org/2010/01/22/owl-syntaxes/.

The article provides an overview of a number of concrete OWL syntaxes. I would suggest including a brief summary of the strengths and weaknesses of the various syntaxes, or any issues that there may be — for example lists/collections in RDF or the limitations on triple based syntax.

There is some mention of tooling support (viz the OWL API), but it’s not clear what other tool support there is for the various syntaxes.

This is a review of What is an ontology?

This well written article spans both logical and philosophical considerations in Ontology so as to provides insight into the kinds of entities that are believed to exist and how we might formally represent them and the basic relations that may exist between them.

The discussion on relations relating to identity (transformedInto, derivedFrom) necessitates further explanation. Are the criterion for identity embedded in physical continuity or in the conscious self? Indeed, we observe that a from develops from a tadpole, the idea lies in the material *largely* persisting spatiotemporally, and that the gain and loss of parts (and the corresponding qualities) is gradual and acceptably identity-preserving.  Yet, we wonder whether the addition of even a single atom to a molecule through some chemical reaction maintains identity. To what extent does the gain or loss of parts become sufficiently important that it requires the distinction of forming a new entity? Perhaps more challenging is if we were to replace a person’s brain with another, we might perceive them to be the same individuals throughout the operations, but would this criterion for identity change if consciousness followed the brain? Then what might we say of identity? Important questions indeed for formal ontology and the representation of biological knowledge.