Maturity Model for Interoperability Potential Measurement

Interoperability potential concerns the preparation level of an enterprise to establish an efficient collaboration with possible part- ners. In order to improve their interoperability, enterprises need to know witch level of maturity they have achieved. This article pro- poses a complete maturity model composed by a methodology and a reference set of parameters to measure interoperability potential. In order to clarify the proposal, an example of application in a real case is described.Campos, C.; Chalmeta, R.; Grangel, R.; Poler Escoto, R. (2013). Maturity Model for Interoperability Potential Measurement. Information Systems Management. 30(3):218-234. doi:10.1080/10580530.2013.794630S218234303Alfaro, J. J., Rodriguez-Rodriguez, R., Verdecho, M. J., & Ortiz, A. (2009). Business process interoperability and collaborative performance measurement. International Journal of Computer Integrated Manufacturing, 22(9), 877-889. doi:10.1080/09511920902866112Sabucedo, L. Á., & Rifón, L. A. (2010). Managing Citizen Profiles in the Domain of e-Government: The cPortfolio Project. Information Systems Management, 27(4), 309-319. doi:10.1080/10580530.2010.514181Berre, A.-J., Elvesæter, B., Figay, N., Guglielmina, C., Johnsen, S. G., Karlsen, D., … Lippe, S. (s. f.). The ATHENA Interoperability Framework. Enterprise Interoperability II, 569-580. doi:10.1007/978-1-84628-858-6_62Blanc, S., Ducq, Y., & Vallespir, B. (2007). Evolution management towards interoperable supply chains using performance measurement. Computers in Industry, 58(7), 720-732. doi:10.1016/j.compind.2007.05.011Campos, C., Martí, I., Grangel, R., Mascherpa, A. and Chalmeta, R. A methodological proposal for the development of an interoperability framework.Model Driven Interoperability for Sustainable Information Systems (MDISIS′08) (CAiSE′08). Vol. 340, pp.47–57. CEUR-WS. http://ceur-ws.org/Vol-340/paper04.pdfChalmeta, R., & Grangel, R. (2005). Performance measurement systems for virtual enterprise integration. International Journal of Computer Integrated Manufacturing, 18(1), 73-84. doi:10.1080/0951192042000213164Doumeingts, G. and Chen, D. Basic concepts and approaches to develop interoperability of enterprise applications.PRO-VE,IFIP Conference Proceedings. Edited by: Camarinha-Matos, L. M. and Afsarmanesh, H. Vol. 262, pp.323–330. Norwell, MA: Kluwer.Duque, A., Campos, C., Jimenez-Ruiz, E. and Chalmeta, R. An ontological solution to supprot interoperability in the textile industry.Second IFIP WG 5.8 International Workshop, IWEI 2009. Edited by: Poler, M. V. S. R. Vol. 38, pp.38–51. New York: Springer.Guédria, W., Naudet, Y., & Chen, D. (2008). Interoperability Maturity Models – Survey and Comparison –. Lecture Notes in Computer Science, 273-282. doi:10.1007/978-3-540-88875-8_48Hoving, R. (2007). Information Technology Leadership Challenges — Past, Present, and Future. Information Systems Management, 24(2), 147-153. doi:10.1080/10580530701221049Palomares, N., Campos, C., & Palomero, S. (2010). How to Develop a Questionnaire in Order to Measure Interoperability Levels in Enterprises. Enterprise Interoperability IV, 387-396. doi:10.1007/978-1-84996-257-5_36Walsham, G. (1995). Interpretive case studies in IS research: nature and method. European Journal of Information Systems, 4(2), 74-81. doi:10.1057/ejis.1995.

Challenges in Survey Research

While being an important and often used research method, survey research has been less often discussed on a methodological level in empirical software engineering than other types of research. This chapter compiles a set of important and challenging issues in survey research based on experiences with several large-scale international surveys. The chapter covers theory building, sampling, invitation and follow-up, statistical as well as qualitative analysis of survey data and the usage of psychometrics in software engineering surveys.Comment: Accepted version of chapter in the upcoming book on Contemporary Empirical Methods in Software Engineering. Update includes revision of typos and additional figures. Last update includes fixing two small issues and typo

Circular-grating surface-emitting DBR laser array for free-space applications

The operation of a 2 \ufffd 2 circular-grating surface-emitting distributed Bragg reflector laser array is demonstrated. An InGaAs/GaAs multiquantum well structure with an etch-stop layer is used. A threshold current of ~20 mA is measured for each laser in the array. High power output with accurate wavelength control was obtained.NRC publication: Ye

A case study in agility and evolving the long-lived software system

Understanding how to effectively evolve long-lived software systems is of ongoing interest. Agile development methods are regarded as best practice by industry for software teams, and empiricists regard studying long-lived agile projects and Scrum teams as priorities. In this paper we explore, through empirical study, and with consideration to organisational context, a case study of a successful, long-lived software project team, implementing Scrum techniques. We apply both qualitative and quantitative analysis, incorporating a questionnaire of 24 professionals and project source code repository analysis. Survey respondents felt, in general, that agile led to desirable project outcomes and fostered effective communication. However, some specific cautions were identified. Diverse process, toolset and software were used to meet project needs. Evolutionary themes observed in the system source code repository included language type fragmentation and growing support for the web stack. Continued codebase growth was measured after a transition to Scrum. Three frontiers for future innovation were discovered: to explore development toolsets with integration as an agile enabler, automating agile and business process interfaces and, strategic evolution of language fragmented architectures, in the agile context.Shannon Fehlmann, Katrina Falkne

Can You Trust Your Data? Establishing the Need for a Measurement and Analysis Infrastructure Diagnostic

An organization's measurement and analysis infrastructure directly impacts the quality of the decisions made by people at all organizational levels. Ensuring information quality is a challenge for most organizations—partly because they might not be fully aware of their own data quality levels. Without this information, they cannot know the full business impact of poor or unknown data quality or determine how to begin improving their data. This report describes common errors in measurement and analysis and the need for a criterion-based assessment method that will allow organizations to evaluate key characteristics of their measurement programs