Building the System: Follow-up, monitoring & adaptive management

Does impact assessment (IA) end when the license has been granted? While societal resources tend to focus on rigorous project approvals, what happens to the project, to the public and to the environment once approval is granted? Follow up and monitoring are often an afterthought for legislators, public servants and proponents. But they are critical to public confidence and to ensuring that proponents live up to their commitments in a rapidly changing world."This report draws from research funded by the Impact Assessment Agency as part of the Social Sciences and Humanities Research Council of Canada Knowledge Mobilization Grant on Informing Best Practice in Environmental and Impact Assessment.

An Approach to Transform Public Administration into SOA-based Organizations

Nowadays, Service-Oriented Architectures (SOA) is widely spread in private organizations. However, when transferring this knowledge to Public Administration, it is realized that it has not been transformed in terms of its legal nature into organizations capable to operate under the SOA paradigm. This fact prevents public administration bodies from offering the efficient services they have been provided by different boards of governments. A high-level framework to perform this transformation is proposed. Taking it as starting point, an instance of a SOA Target Meta-Model can be obtained by means of an iterative and incremental process based on the analysis of imperatives and focused on the particular business context of each local public administration. This paper briefly presents a practical experience consisting in applying this process to a Spanish regional public administration.Junta de Andalucía TIC-578

Goal-Oriented Requirements Engineering: State of the Art and Research Trend

The Goal-Oriented Requirements Engineering (GORE) is one approach that is widely used for the early stages of software development. This method continues to develop in the last three decades. In this paper, a literature study is conducted to determine the GORE state of the art. The study begins with a Systematic Literature Review (SLR) was conducted to determine the research trend in the last five years. This study reviewed 126 papers published from 2016 to 2020.  The research continues with the author's search for scientific articles about GORE. There are 26 authors who actively publish GORE research results. Twenty-six authors were grouped into seven groups based on their relation or co-authoring scientific articles. An in-depth study of each group resulted in a holistic mapping of GORE research.  Based on the analysis, it is known that most research focuses on improving GORE for an automated and reliable RE process, developing new models/frameworks/methods originating from GORE, and implementing GORE for the RE process. This paper contributes to a holistic mapping of the GORE approach. Through this study, it is known the various studies that are being carried out and research opportunities to increase automation in the entire RE process

Legal compliance by design (LCbD) and through design (LCtD) : preliminary survey

1st Workshop on Technologies for Regulatory Compliance co-located with the 30th International Conference on Legal Knowledge and Information Systems (JURIX 2017). The purpose of this paper is twofold: (i) carrying out a preliminary survey of the literature and research projects on Compliance by Design (CbD); and (ii) clarifying the double process of (a) extending business managing techniques to other regulatory fields, and (b) converging trends in legal theory, legal technology and Artificial Intelligence. The paper highlights the connections and differences we found across different domains and proposals. We distinguish three different policydriven types of CbD: (i) business, (ii) regulatory, (iii) and legal. The recent deployment of ethical views, and the implementation of general principles of privacy and data protection lead to the conclusion that, in order to appropriately define legal compliance, Compliance through Design (CtD) should be differentiated from CbD

HOW AGILE IS YOUR IT DEPARTMENT? – DEVELOPMENT AND APPLICATION OF AN FRAMEWORK-INDEPENDENT AGILE SCALING MATURITY MODEL

Many IT departments seek to capitalize on the benefits of agile development by scaling agile practices. To manage the complex scaling, established approaches and frameworks promise guidance. However, although existing works envision a clear target state, they lack relevant capabilities along the scaling process, especially for vertical agile scaling. Managers need these capabilities to assess their company’s status quo and develop a clear scaling roadmap. Thus, within this work, we use the Design Science Research paradigm to build and evaluate a framework-independent agile scaling maturity model that provides management with a tool for ex-ante identification and evaluation of agile scaling capabilities in five maturity stages. To evaluate our model, we applied it at KUKA IT, the IT department of an international provider of automation solutions. As a result, this work provides insights into the application and outlines how IT departments can operationalize and utilize our model to guide agile scaling

Major Indian ICT firms and their approaches towards achieving quality

Of the three basic theories of innovation: the entrepreneur theory, the technology-economics theory and the strategic theory, the third one seems to be highly appropriate for the analysis of recent growth of the information and communication technology (ICT) industry in many developing countries including India. The central measure for achieving quality by the various major Indian ICT firms is widely agreed to have been the adoption of Six Sigma Methodology and various other approaches like Total Quality Management (TQM), Supply Chain Management (SCM), Customer Relationship Management (CRM), etc. It is apparent that the main objective of the firms chosen has been to increase the pace of innovation activities, irrespective of their different areas of product specialisation. Its success also depends largely on the overall improvement in infrastructure, besides active market interaction. To enable both the above, a brief highlight on the establishment of interaction and learning sites (ILSs) in every regional State in India comes to the foreground. The chapter concludes with a mention of the elements observed to be missing among the firms under consideration, and, thereby, delineating the scope for their further improvement.

Goal-oriented requirements engineering: an extended systematic mapping study.

Over the last two decades, much attention has been paid to the area of goal-oriented requirements engineering (GORE), where goals are used as a useful conceptualization to elicit, model, and analyze requirements, capturing alternatives and conflicts. Goal modeling has been adapted and applied to many sub-topics within requirements engineering (RE) and beyond, such as agent orientation, aspect orientation, business intelligence, model-driven development, and security. Despite extensive efforts in this field, the RE community lacks a recent, general systematic literature review of the area. In this work, we present a systematic mapping study, covering the 246 top-cited GORE-related conference and journal papers, according to Scopus. Our literature map addresses several research questions: we classify the types of papers (e.g., proposals, formalizations, meta-studies), look at the presence of evaluation, the topics covered (e.g., security, agents, scenarios), frameworks used, venues, citations, author networks, and overall publication numbers. For most questions, we evaluate trends over time. Our findings show a proliferation of papers with new ideas and few citations, with a small number of authors and papers dominating citations; however, there is a slight rise in papers which build upon past work (implementations, integrations, and extensions). We see a rise in papers concerning adaptation/variability/evolution and a slight rise in case studies. Overall, interest in GORE has increased. We use our analysis results to make recommendations concerning future GORE research and make our data publicly available

FIN-DM: finantsteenuste andmekaeve protsessi mudel

Andmekaeve hõlmab reeglite kogumit, protsesse ja algoritme, mis võimaldavad ettevõtetel iga päev kogutud andmetest rakendatavaid teadmisi ammutades suurendada tulusid, vähendada kulusid, optimeerida tooteid ja kliendisuhteid ning saavutada teisi eesmärke. Andmekaeves ja -analüütikas on vaja hästi määratletud metoodikat ja protsesse. Saadaval on mitu andmekaeve ja -analüütika standardset protsessimudelit. Kõige märkimisväärsem ja laialdaselt kasutusele võetud standardmudel on CRISP-DM. Tegu on tegevusalast sõltumatu protsessimudeliga, mida kohandatakse sageli sektorite erinõuetega. CRISP-DMi tegevusalast lähtuvaid kohandusi on pakutud mitmes valdkonnas, kaasa arvatud meditsiini-, haridus-, tööstus-, tarkvaraarendus- ja logistikavaldkonnas. Seni pole aga mudelit kohandatud finantsteenuste sektoris, millel on omad valdkonnapõhised erinõuded. Doktoritöös käsitletakse seda lünka finantsteenuste sektoripõhise andmekaeveprotsessi (FIN-DM) kavandamise, arendamise ja hindamise kaudu. Samuti uuritakse, kuidas kasutatakse andmekaeve standardprotsesse eri tegevussektorites ja finantsteenustes. Uurimise käigus tuvastati mitu tavapärase raamistiku kohandamise stsenaariumit. Lisaks ilmnes, et need meetodid ei keskendu piisavalt sellele, kuidas muuta andmekaevemudelid tarkvaratoodeteks, mida saab integreerida organisatsioonide IT-arhitektuuri ja äriprotsessi. Peamised finantsteenuste valdkonnas tuvastatud kohandamisstsenaariumid olid seotud andmekaeve tehnoloogiakesksete (skaleeritavus), ärikesksete (tegutsemisvõime) ja inimkesksete (diskrimineeriva mõju leevendus) aspektidega. Seejärel korraldati tegelikus finantsteenuste organisatsioonis juhtumiuuring, mis paljastas 18 tajutavat puudujääki CRISP- DMi protsessis. Uuringu andmete ja tulemuste abil esitatakse doktoritöös finantsvaldkonnale kohandatud CRISP-DM nimega FIN-DM ehk finantssektori andmekaeve protsess (Financial Industry Process for Data Mining). FIN-DM laiendab CRISP-DMi nii, et see toetab privaatsust säilitavat andmekaevet, ohjab tehisintellekti eetilisi ohte, täidab riskijuhtimisnõudeid ja hõlmab kvaliteedi tagamist kui osa andmekaeve elutsüklisData mining is a set of rules, processes, and algorithms that allow companies to increase revenues, reduce costs, optimize products and customer relationships, and achieve other business goals, by extracting actionable insights from the data they collect on a day-to-day basis. Data mining and analytics projects require well-defined methodology and processes. Several standard process models for conducting data mining and analytics projects are available. Among them, the most notable and widely adopted standard model is CRISP-DM. It is industry-agnostic and often is adapted to meet sector-specific requirements. Industry- specific adaptations of CRISP-DM have been proposed across several domains, including healthcare, education, industrial and software engineering, logistics, etc. However, until now, there is no existing adaptation of CRISP-DM for the financial services industry, which has its own set of domain-specific requirements. This PhD Thesis addresses this gap by designing, developing, and evaluating a sector-specific data mining process for financial services (FIN-DM). The PhD thesis investigates how standard data mining processes are used across various industry sectors and in financial services. The examination identified number of adaptations scenarios of traditional frameworks. It also suggested that these approaches do not pay sufficient attention to turning data mining models into software products integrated into the organizations' IT architectures and business processes. In the financial services domain, the main discovered adaptation scenarios concerned technology-centric aspects (scalability), business-centric aspects (actionability), and human-centric aspects (mitigating discriminatory effects) of data mining. Next, an examination by means of a case study in the actual financial services organization revealed 18 perceived gaps in the CRISP-DM process. Using the data and results from these studies, the PhD thesis outlines an adaptation of CRISP-DM for the financial sector, named the Financial Industry Process for Data Mining (FIN-DM). FIN-DM extends CRISP-DM to support privacy-compliant data mining, to tackle AI ethics risks, to fulfill risk management requirements, and to embed quality assurance as part of the data mining life-cyclehttps://www.ester.ee/record=b547227