2012 Annual Report - Advanced Biomedical Information Technology Core

This material is based upon work supported in part by the following funding agencies and grant awards: • Lilly Endowment, for its support of the Indiana Genomics Initiative (INGEN) – 2000; Indiana Metabolomics and Cytomics Initiative (METACyt); Indiana Pervasive Computing Research (IPCRES) initiative and Pervasive Technology Institute (1999 and 2008 respectively) • National Science Foundation under grants 01116050 MRI: Creation of the AVIDD Data Facility: A Distributed Facility for Managing, Analyzing and Visualizing Instrument-Driven Data (Michael A. McRobbie, PI); 0521433 MRI: Acquisition of a High-Speed, High Capacity Storage System to Support Scientific Computing: The Data Capacitor (Craig A. Stewart, PI); 0521433 ABI Development: National Center for Genome Analysis Support (Craig A. Stewart, PI) • National Institutes of Health NIAAA awards U24 AA014818-01 (Craig A. Stewart, PI) and U24 AA014818-04 (William K. Barnett, PI) Informatics Core for the Collaborative Initiative on Fetal Alcohol Spectrum Disorder • Subcontracts through the following NIH grant awards: 5P40RR024928 (Kenneth Cornetta, PI), 2U01AA014809 (Tatiana Foroud, PI), 1DP2OD007363-01 (Alexander Niculescu, PI), UL1RR025761-01 (Anantha Shekhar, PI), 3UL1RR025761-04S2 (Anantha Shekhar, PI), and 3UL1RR025761-04S3 (Anantha Shekhar, PI) • Funding from the general funds of Indiana University Any opinions expressed in this document are those of the authors and do not necessarily reflect the views of the funding agencies above

Decentralized Enforcement of Artifact Lifecycles

International audienceArtifact-centric workflows describe possible executions of a business process through constraints expressed from the point of view of the documents exchanged between principals. A sequence of manipulations is deemed valid as long as every document in the workflow follows its prescribed lifecycle at all steps of the process. So far, establishing that a given workflow complies with artifact lifecycles has mostly been done through static verification, or by assuming a centralized access to all artifacts where these constraints can be monitored and enforced. We present in this paper an alternate method of enforcing document lifecycles that requires neither static verification nor single-point access. Rather, the document itself is designed to carry fragments of its history, protected from tampering using hashing and public-key encryption. Any principal involved in the process can verify at any time that a document's history complies with a given lifecycle. Moreover, the proposed system also enforces access permissions: not all actions are visible to all principals, and one can only modify and verify what one is allowed to observe

Decentralized Enforcement of Artifact Lifecycles

International audienceArtifact-centric workflows describe possible executions of a business process through constraints expressed from the point of view of the documents exchanged between principals. A sequence of manipulations is deemed valid as long as every document in the workflow follows its prescribed lifecycle at all steps of the process. So far, establishing that a given workflow complies with artifact lifecycles has mostly been done through static verification, or by assuming a centralized access to all artifacts where these constraints can be monitored and enforced. We present in this paper an alternate method of enforcing document lifecycles that requires neither static verification nor single-point access. Rather, the document itself is designed to carry fragments of its history, protected from tampering using hashing and public-key encryption. Any principal involved in the process can verify at any time that a document's history complies with a given lifecycle. Moreover, the proposed system also enforces access permissions: not all actions are visible to all principals, and one can only modify and verify what one is allowed to observe

Collaborative Virtual Enterprise Environment and Decision Mining

This paper will present some meaningful insights into the analysis and modeling phases of an Enterprise Virtual Environment (EVE) prototype. The main goal of EVE is to provide an environment for collaborative decisions using a DSS-like approach. In the second part, the proposed architecture of the system will be introduced. This system is developed primarily to simulate decision situations in the academic training of students. The second goal of the system is to provide us with user activity logs that will be the starting point of decision pattern mining process. In the third part of the paper, we will provide evidence regarding the possibility of: mining decision models from user activity logs; comparing different decision making strategies of users; and building decision reference models.Enterprise Virtual Environment, Decision Simulation, DSS Analysis and Modeling, Decision Mining, Decision Analysis, Decision Models

Structuring research methods and data with the research object model:genomics workflows as a case study

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e. g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as "which particular data was input to a particular workflow to test a particular hypothesis?", and "which particular conclusions were drawn from a particular workflow?". Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well. Availability: The Research Object is available at http://www.myexperiment.org/packs/428 The Wf4Ever Research Object Model is available at http://wf4ever.github.io/r