Images, Ontology, and Uncertain Knowledge

We would first of all like to thank Thor Grünbaum and Andrea Raballo for their thoughtful and lively commentary on our work. We would also like to thank Daniel Rubin for taking this opportunity to describe in detail some of the research carried out in this domain since our paper was first written. Although their commentaries may seem to fall on opposite ends of the critical scale, so to speak, taken together they provide an opportunity to take stock of the progress that has been made in this endeavor as well as some of the challenges that remain to be overcome. In this short response, we focus primarily on what we believe to be the most serious of Grünbaum and Raballo's criticisms to our work, arguing that our position is far more modest than their characterization suggests and is indeed rather closer to the one they themselves claim to be entirely unobjectionable. Our aim here is to argue that the advances to be made in this endeavor—even if they are unobjectionable—are far from trivial as Grünbaum and Raballo claim.

Turning to Grünbaum and Raballo's commentary, we believe there are three principle criticisms around which their arguments turn. The first two concern the very possibility of implementing some form of applied ontology in the psychiatric domain, regardless of the form this application would take. Their third criticism concerns the particular ontological framework we have applied, adapted from Roman Ingarden's ontological aesthetics. We first treat Grünbaum and Raballo's general criticisms, followed by the more specific. Where possible, we also turn to Rubin's commentary for further demonstration of our main points.

The first of the general criticisms Grünbaum and Raballo put forward is that, although our applied ontology is intended to aid researchers and medical practitioners in the field of neuroimaging, the current state of the art essentially forbids us from making any advances here. According to them, "there is no well-established consensus about what exactly pictures of patterns of brain activation are showing us about the brain and its role in the performance of cognitive tests" (2011, 306). Because of this lack of clear consensus on the relationships between the physical structures of the imaged brain and the nature of the experience these images are intended to provide some measurement of, they suggest such a knowledge base of neuroimages would be unable to gain an ontological foothold. We would respond, however, that if, as they claim, "unlike x-rays of fractured bones, in psychiatry the relation between the brain image and the disease entity is highly problematic" (2011, 306), this is no argument against introducing a data management tool such as the one we have described. It is, on the contrary, only further evidence of its necessity. It is precisely because of this lack of consensus that the vast amount of image data being accrued needs to be readily accessible and stored in a format that is flexible enough to facilitate the wide and evolving interests and uncertainties of the researchers working in this domain, which is today being carried out at an explosive pace. As Rubin notes, "although nonimage data are easily processed by machines, image data are generally not exploited directly—images typically are stored in archives, and only particular data needed for the study of the in which the images were originally acquired are generally available for subsequent analysis" (2011, 311). Addressing this limited access was one of the principle motivations behind the development of our imaging ontology framework.

The second general claim Grünbaum and Raballo make is that, in the absence of a general consensus among practitioners, the scope of the general biomedical imagining ontology we outline, were it applied to the psychiatric domain, would be too limited to be useful. Grünbaum and Raballo are absolutely correct when they state that, "one of the key features of a knowledge representation system is that with the right software it should be able to generate sounds and practically valuable inferences from...