What Other Factors Might Impact Building Trust in Government Decisions Based on Decision Support Systems, Except for Transparency and Explainability?

Decision Support Systems (DSS) are increasingly being used to support operational decision-making using large amounts of data. One key aspect to successful adoption is that the user trusts the DSS. Large contributors to trust often mentioned in literature and practice are transparency and explainability. But what happens when a DSS is transparent and explainable by design? What other contributors to trust are relevant is the main focus of this paper, in the context of Dutch governmental subject-matter experts designing and working with DSSs. We used a Mixed-Method Sequential Explanatory Design in which a survey was conducted to gather empirical data. The findings present 20 focal points contributing toward trust in DSS. These focal points require future research, specifically on considering these for development by the design of a DSS. Ultimately, this could help in increasing the adoption of DSSs in general

Ecological mechanisms and effectiveness of bioremediation in Alaska

Thesis (Ph.D.) University of Alaska Fairbanks, 2014What drives microbial community structure and function is a fundamental question of microbial ecology. Soil microbial communities have wide ranging metabolic capabilities, which include performing oxidation-reduction reactions responsible for cycling of nutrients and organic compounds and biodegradation of pollutants. One major determinant of microbial function in soils is vegetation type. Considering plants are diverse in chemical composition, they impact the quantity and quality of carbon and nutrients available to microbes through root turnover, root leachates, as well as by altering pH and soil microclimate (moisture, temperature). Rhizosphere interactions, in the form of phytoremediation, can be capitalized upon to provide a potentially cost effective method for detoxifying contaminated soils using plants and associated soil microorganisms. The remote locations and cold climate of Alaska provide unique challenges associated with phytoremediation such as finding effective plant species that can achieve successful site clean-up despite the extreme environmental conditions that includes minimal site management. Here we investigate the potential mechanisms and related effectiveness of microbial communities and native boreal vegetation associated with contaminant degradation and biogeochemical cycling. We examined three different soil systems to understand how dominant vegetation type, historical treatment and contamination shape the microbial community structure and functional potential. First, we used stable isotope probing to understand how microbial communities act in concert to biotransform the recalcitrant contaminants, polychlorinated biphenyls. Second, we sought to understand if dominant vegetation type controls microbial community structure and function either through direct impacts of plant root exudates and detritus or indirectly through the influence of plants on soil chemistry, composition, and structure. Finally, we conducted a forensic investigation of a petroleum contaminated site with no active site management for 15 years to assess the long-term effects of phytoremediation on soil petroleum concentrations, microbial community and vegetation colonization. The results of these experiments provide novel insights into the mechanisms of contaminant removal in boreal forest soils and the role of plants in ecosystem resilience to contamination, and demonstrates that phytoremediation using native and local plants can be an effective means to treat petroleum contaminated soils.Chapter 1: Introduction -- Chapter 2: Aromatic compound processing in PCB-contaminated soil: carbon flow through the microbial ecosystem -- Chapter 3: Microbial community structure and functional potential associated with four boreal forest vegetation types -- Chapter 4: Long-term effects of nutrient addition and phytoremediation on diesel and crude oil contaminated soils in subarctic Alaska -- Chapter 5: Conclusions

Translating Business Process Models to Class Diagrams

Choreography of business processes can track messages between different services. At the time of writing, there are no guidelines t o d raw a U ML C lass D iagram f rom t he Business Process Choreography. This paper reports an experiment using a set of guidelines. Objective: Evaluate the subjects’ performance and perceptions when applying the BPc2Class-guidelines and BPc2Class-discovery process. Method: To measure the performance and user perception of both ways of mapping the processes, a comparative experiment was conducted with 38 subjects. The subjects, being master students, solved a process case in the first session and a guidelines case in the second session. A survey was filled in by the subjects to measure the user perception variables. Results: The results indicated that the guidelines showed significantly better results in five out of the six measured variables. Conclusion: Based on the findings and limitations of this research the use of guidelines looks promising, but future research is necessary to further generalize the conclusion

Future Challenges in Decision Mining at Governmental Institutions

Decisions are made in fast-changing situations. To cope with this, decision mining could be utilized to support the decision-making process. Decision mining is an emerging field which could support an organizations decision-making process. For proper utilization of decision mining, possible challenges should be identified to take into account when mining decisions. As such, two focus groups were conducted where we identified 11 main challenges that seven Dutch governmental institutions deemed important and which should be taken into consideration when mining decisions. The identified challenges are depicted further together with existing literature and the coded observations. The identified challenges could be utilized as future research directions and are discussed as such

A Classification of Modification Categories for Business Rules

Business rules play a critical role in an organization’s daily activities. With the increased use of business rules (solutions) the interest in modelling guidelines that address the manageability of business rules has increased as well. However, current research on modelling guidelines is mainly based on a theoretical view of modifications that can occur to a business rule set. Research on actual modifications that occur in practice is limited. The goal of this study is to identify modifications that can occur to a business rule set and underlying business rules. To accomplish this goal we conducted a grounded theory study on 229 rules set, as applied from March 2006 till June 2014, by the National Health Service. In total 3495 modifications have been analysed from which we defined eleven modification categories that can occur to a business rule set. The classification provides a framework for the analysis and design of business rules management architectures

An Explorative Study Into Situational Artefact Construction in Business Rules Management

The implementation of software products is a time-consuming activity and requires specific expertise to be completed successfully. This is especially the case in research fields where there is no or little tool support available, such as Business Rules Management (BRM) and Business Rules Management Solutions (BRMS). Tool support is essential to successfully guide the organizational implementation of a BRMS. Motivated by the diversity of organizational structures and their BRMS implementation contexts, we design a situational-aware framework for the organizational implementation of BRMS. The framework is based on the theory of situational artefact construction. Using situational artefact construction, we study 13 BRMS implementation cases distributed over the financial and public sectors in the Netherlands. Based on the results of the cases analysed we present a framework with three main artefacts that are a stepping-stone towards further research on situational implementation methodology in the BRM field

Business Rules Management and Decision Mining - Filling in the Gaps

Proper decision-making is one of the most important capabilities of an organization. Adequately managing these decisions is therefore of high importance. Business Rules Management (BRM) is an approach that helps in managing decisions and underlying business logic. However, questions still arise if the decisions are properly improved based on decision data. Decision Mining (DM) could complement BRM capabilities in order to improve towards effective and efficient decision-making. In this study, we propose the integration of BRM and DM through a simulation using a government and a healthcare case. During this simulation, three entry points are presented that describe how decision-related data should be utilized between BRM capabilities and DM phases to be able to integrate them. The presented results provide a basis from which more technical research on the three DM phases can be further explored