A cost model for ontology engineering

In this report we propose a methodology for cost estimation for ontologies and analyze cost factors implied in the engineering process. We examine the appropriateness of a COCOMO-like parametric approach to ontology cost estimation and propose a non-calibrated ontology cost model, which is to be continuously refined along with the collection of empiric data on person month efforts invested in developing ontologies in real-world projects. We further describe the human-driven evaluation of the cost drivers described in the parametric model on the basis of the cost models’ quality framework by Boehm[5

Ontology based software engineering - software engineering 2.0

This paper describes the use of ontologies in different aspects of software engineering. This use of ontologies varies from support for software developers at multiple sites to the use of an ontology to provide semantics in different categories ofsoftware, particularly on the web. The world's first and only software engineering ontology and a project management ontology in conjunction with a domain ontology are used to provide support for software development that is taking place at multiple sites. Ontologies are used to provide semantics to deal with heterogeneity in the representation of multiple information sources, enable the selection and composition of web services and grid resources, provide the shared knowledge base for multiagent systems, provide semantics and structure for trust and reputation systems and privacy based systems and codification of shared knawledge within different domains in business, science, manufacturing, engineering and utilities. They, therefore, bring a new paradigm to software engineering through the use of semantics as a central mechanism which will revolutionize the way software is developed and consumed in the future leading to the development of software as a service bringing about the dawn of software engineering 2.0

Ontology Engineering Cost Estimation with ONTOCOM

Techniques for reliably estimating development efforts are a fundamental requirement for a wide-scale dissemination of ontologies in business contexts. In this report we account for the similarities and differences between software and ontology engineering in order to establish the appropriateness of applying software cost models to ontologies. We present a parametric approach to cost estimation for ontology development – ONTOCOM – and analyze various cost factors implied in the ontology engineering process

Collaborative analysis of multi-gigapixel imaging data using Cytomine

Motivation: Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries. Results: We developed Cytomine to foster active and distributed collaboration of multidisciplinary teams for large-scale image-based studies. It uses web development methodologies and machine learning in order to readily organize, explore, share and analyze (semantically and quantitatively) multi-gigapixel imaging data over the internet. We illustrate how it has been used in several biomedical applications

Doctor of Philosophy

dissertationClinical research plays a vital role in producing knowledge valuable for understanding human disease and improving healthcare quality. Human subject protection is an obligation essential to the clinical research endeavor, much of which is governed by federal regulations and rules. Institutional Review Boards (IRBs) are responsible for overseeing human subject research to protect individuals from harm and to preserve their rights. Researchers are required to submit and maintain an IRB application, which is an important component in the clinical research process that can significantly affect the timeliness and ethical quality of the study. As clinical research has expanded in both volume and scope over recent years, IRBs are facing increasing challenges in providing efficient and effective oversight. The Clinical Research Informatics (CRI) domain has made significant efforts to support various aspects of clinical research through developing information systems and standards. However, information technology use by IRBs has not received much attention from the CRI community. This dissertation project analyzed over 100 IRB application systems currently used at major academic institutions in the United States. The varieties of system types and lack of standardized application forms across institutions are discussed in detail. The need for building an IRB domain analysis model is identified. . iv In this dissertation, I developed an IRB domain analysis model with a special focus on promoting interoperability among CRI systems to streamline the clinical research workflow. The model was evaluated by a comparison with five real-world IRB application systems. Finally, a prototype implementation of the model was demonstrated by the integration of an electronic IRB system with a health data query system. This dissertation project fills a gap in the research of information technology use for the IRB oversight domain. Adoption of the IRB domain analysis model has potential to enhance efficient and high-quality ethics oversight and to streamline the clinical research workflow

Mining Hypernyms Semantic Relations from Stack Overflow

Communication between a software development team and business partners is often a challenging task due to the different context of terms used in the information exchange. The various contexts in which the concepts are defined or used create slightly different semantic fields that can evolve into information and communication silos. Due to the silo effect, the necessary information is often inadequately forwarded to developers resulting in poorly specified software requirements or misinterpreted user feedback. Communication difficulties can be reduced by introducing a mapping between the semantic fields of the parties involved in the communication based on the commonly used terminologies. Our research aims to obtain a suitable semantic database in the form of a semantic network built from the Stack Overflow corpus, which can be considered to encompass the common tacit knowledge of the software development community. Terminologies used in the business world can be assigned to our semantic network, so software developers do not miss features that are not specific to their world but relevant to their clients. We present an initial experiment of mining semantic network from Stack Overflow and provide insights of the newly captured relations compared to WordNet

Some Information Systems Research Trends over the Past Decade

In order to gain an understanding of the recent evolution and the current state of information systems (IS) development research, three sub-topic areas within IS development, were examined: IS development methodology, IS architecture, and IS design and modeling. Relevant papers were selected from the Association for Information Systems (AIS) basket of eight journals. Using these articles, an empirical method based on author keywords was used to identify categorical research trends in each of the three areas. Research trends observed in each of the categories over the past decade are discussed

Pay-As-You-Go Software Artifacts Managemen

One of the major challenges in software engineering research is to manage software artifacts effectively. However, software artifacts are often changed during software development, the full, one-time integration technique is not feasible to manage such heterogeneity and evolving data. In this paper, we concern about the application of dataspace techniques, which emphasize the idea of pay-as-you-go data management, to software artifacts management. To this end, we present a loosely structured data model based on the current dataspace models to describe software artifacts, and a strategy to query this model. We also present how to gradually add semantics to query processing for improving the precision and recall of query results. Furthermore, the validity of our work is proved by experiment. Finally, the differences between our work and traditional work are discussed

Data completeness in healthcare: A literature survey.

As the adoption of eHealth has made it easier to access and aggregate healthcare data, there has been growing application for clinical decisions, health services planning, and public health monitoring with daily collected data in clinical care. Reliable data quality is a precursor of the aforementioned tasks. There is a body of research on data quality in healthcare, however, a clear picture of data completeness in this field is missing. This research aims to identify and classify current research themes related to data completeness in healthcare. In addition, the paper presents problems with data completeness in the reviewed literature and identifies methods that have been adopted to address those problems. This study has reviewed 24 papers (January 2011–April 2016) published in information and computing sciences, biomedical engineering, and medicine and health sciences journals. The paper uncovers three main research themes, including design and development, evaluation, and determinants. In conclusion, this paper improves our understanding of the current state of the art of data completeness in healthcare records and indicates future research directions.N

The transcriptional repressor complex FRS7-FRS12 regulates flowering time and growth in Arabidopsis

Most living organisms developed systems to efficiently time environmental changes. The plant-clock acts in coordination with external signals to generate output responses determining seasonal growth and flowering time. Here, we show that two Arabidopsis thaliana transcription factors, FAR1 RELATED SEQUENCE 7 (FRS7) and FRS12, act as negative regulators of these processes. These proteins accumulate particularly in short-day conditions and interact to form a complex. Loss-of-function of FRS7 and FRS12 results in early flowering plants with overly elongated hypocotyls mainly in short days. We demonstrate by molecular analysis that FRS7 and FRS12 affect these developmental processes in part by binding to the promoters and repressing the expression of GIGANTEA and PHYTOCHROME INTERACTING FACTOR 4 as well as several of their downstream signalling targets. Our data reveal a molecular machinery that controls the photoperiodic regulation of flowering and growth and offer insight into how plants adapt to seasonal changes