Introduction:Ecosystem goods and services(EGS)studies have had little impact on policy processes and real-world decision-making due to limited understanding of the interactions and feedbacks among ecological,social an...Introduction:Ecosystem goods and services(EGS)studies have had little impact on policy processes and real-world decision-making due to limited understanding of the interactions and feedbacks among ecological,social and economic processes.Here we present an inter-and transdisciplinary analysis of global change impacts on EGS provision in a European mountain region.Our aim is to evaluate the projected influence of ecological,economic and social drivers on future EGS provision and to show possible ways to address the predominant limitations of EGS studies.Methods:The integrated findings from ecological experiments,mechanistic models of landscape dynamics,socio-economic land-use models,policy analysis and transdisciplinary stakeholder interactions are presented consecutively.Four regionally downscaled global change scenarios,for a case study region near Visp,Switzerland(350 km2),were used to examine the impacts of climate and socio-economic changes on four ecosystem services,i.e.,food provision,timber production,net greenhouse gas emissions and protection from natural hazards.Results:Our simulation results reveal four key aspects that influence the future provision of mountain EGS.First,we show the high spatial and temporal heterogeneity of EGS provision even in a small case study region.Second,we find that climate change impacts are much more pronounced for forest EGS,while changes to agricultural EGS result primarily from shifts in economic conditions.Third,our modeling results reveal the complex trade-offs associated with the different scenarios.Fourth,simulations illustrate the importance of interactions between environmental shifts and economic decisions.We discuss our simulation results with respect to both existing policy networks and transdisciplinary stakeholder interactions.Conclusion:We describe a framework based on experiments and observations that effectively supports the integration of ecological processes into an integrative modeling chain of EGS provision in mountain regions,the political decision-making process and also transdisciplinary stakeholder interactions.展开更多
The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access...The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.展开更多
The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access...The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.展开更多
基金This work was supported by the CCES(Competence Centre Environment and Sustainability of the ETH Domain,Switzerland)as part of the Mountland project.
文摘Introduction:Ecosystem goods and services(EGS)studies have had little impact on policy processes and real-world decision-making due to limited understanding of the interactions and feedbacks among ecological,social and economic processes.Here we present an inter-and transdisciplinary analysis of global change impacts on EGS provision in a European mountain region.Our aim is to evaluate the projected influence of ecological,economic and social drivers on future EGS provision and to show possible ways to address the predominant limitations of EGS studies.Methods:The integrated findings from ecological experiments,mechanistic models of landscape dynamics,socio-economic land-use models,policy analysis and transdisciplinary stakeholder interactions are presented consecutively.Four regionally downscaled global change scenarios,for a case study region near Visp,Switzerland(350 km2),were used to examine the impacts of climate and socio-economic changes on four ecosystem services,i.e.,food provision,timber production,net greenhouse gas emissions and protection from natural hazards.Results:Our simulation results reveal four key aspects that influence the future provision of mountain EGS.First,we show the high spatial and temporal heterogeneity of EGS provision even in a small case study region.Second,we find that climate change impacts are much more pronounced for forest EGS,while changes to agricultural EGS result primarily from shifts in economic conditions.Third,our modeling results reveal the complex trade-offs associated with the different scenarios.Fourth,simulations illustrate the importance of interactions between environmental shifts and economic decisions.We discuss our simulation results with respect to both existing policy networks and transdisciplinary stakeholder interactions.Conclusion:We describe a framework based on experiments and observations that effectively supports the integration of ecological processes into an integrative modeling chain of EGS provision in mountain regions,the political decision-making process and also transdisciplinary stakeholder interactions.
文摘The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.
基金supported by Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.
