Milo: A generic repository for experimental data Gully APC Burns, Information Sciences Institute, [gully@usc.edu] Alan Ruttenberg, ScienceCommons, [alanruttenberg@gmail.com] Gwen Jacobs, Montana State University, [gwenajacobs@gmail.com] Introduction Disease foundations, such as the Michael J Fox Foundation for Parkinson’s disease Research (‘MJFF’) and the Kinetics foundation (‘KinF’), are continually attempting to improve the impact and utility of the knowledge generated by their funding. As is the case with any centralized funding body, the only effective, generalized medium for disseminating scientific data is through traditional publishing mechanisms. Here, valuable data is presented only as summaries (in figures or tables embedded in the text of the papers), more often than not without providing access to the raw data generated within the study. If access to the data is provided within a publication as ‘supplementary data’, there are currently no standardized formats or structures for the delivery of this data. Given the power of modern computers and the representational capabilities of current semantic approaches, we propose a solution to this challenging problem. The purpose of this project is to develop a proof-of-concept application for a semantically-enabled data repository designed to support meta-analysis across individual studies. This system will be populated with data from a MJFF/KinF-funded study to demonstrate the viability of the system for real data of interest. Within our team, we will include (a) members of the study’s research group and (b) foundation administrators. It is crucial for the success of this project that we are able to demonstrate the viability of this approach by measuring system usability. By working closely with Foundation-sponsored stakeholders, we will use these metrics to drive development of the system in service of the goal of building a system that is suitable for everyday use. Within this preliminary project, we have the following primary goals: (A) To develop a basic, no-frills experimental data curation system process and information system prototype for MJFF grantees. The basic framework we will use is provided by the NeuroSys project, now in its 7 th year of federal funding within Gwen Jacobs’ group at Montana State University (MH064416). NeuroSys has been rebuilt as a foundation of tools called ‘Yogo’ which we will seek to leverage and extend within this application. (B) The core idea of the project is based around a practical knowledge engineering framework (described below) based on a relatively simple model of experimental design. This too is being developed under federal funding (GM083871) to be used for the curation of the scientific literature. This project explicitly extends this framework’s action to apply to primary research data as an underlying design rationale for the data model of the Yogo platform. We will incorporate this strategy into a workflow (described in detail later) that permits a scientist to submit a protocol for an experiment to the Foundation; which may then be transcribed into a formal representation that generates data spreadsheets or forms to be filled in by the scientist and subsequently loaded into a centralized