Unlocking the Treasure Chest of Labor Market Information: Crucial Information for Job Seekers, Educators, and Employers in a Tough Economy

Quality labor market data and analysis is critical to developing effective market-driven workforce and economic strategies in states, regions, and localities. Such information can be complex, intimidating, and overwhelming to many users, however. This issue brief offers a framework for understanding workforce information, including a summary of the different types of consumers of information and their need for comprehensive data and analysis about the labor market. It identifies the publicly available information sources that produce the data and provides suggestions on how to identify and address the gaps between user needs and the availability of reliable and timely data and analytical capacity to enable effective and informed decision-making by data consumers. Finally, it recommends ways in which states and local areas can make workforce information more readily available to consumers who must make important decisions

An analytical framework to nowcast well-being using mobile phone data

An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we design a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that the diversity of mobility, defined in terms of entropy of the individual users' trajectories, exhibits (i) significant correlation with two different socio-economic indicators and (ii) the highest importance in predictive models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through the lens of Big Data by means of new statistical indicators that quantify and possibly "nowcast" the well-being and the socio-economic development of a territory

A Survey on Evaluation Factors for Business Process Management Technology

Estimating the value of business process management (BPM) technology is a difficult task to accomplish. Computerized business processes have a strong impact on an organization, and BPM projects have a long-term cost amortization. To systematically analyze BPM technology from an economic-driven perspective, we are currently developing an evaluation framework in the EcoPOST project. In order to empirically validate the relevance of assumed evaluation factors (e.g., process knowledge, business process redesign, end user fears, and communication) we have conducted an online survey among 70 BPM experts from more than 50 industrial and academic organizations. This paper summarizes the results of this survey. Our results help both researchers and practitioners to better understand the evaluation factors that determine the value of BPM technology

e-Social Science and Evidence-Based Policy Assessment : Challenges and Solutions

Peer reviewedPreprin

U.S. SDG Data Revolution Roadmap

One year after adopting the SDGs, in an addendum to its Open Government National Action Plan, the U.S. Government committed to develop an SDG Data Revolution Roadmap that "charts the future course of efforts to fill data gaps and build capacity to use data for decision-making and innovation to advance sustainable development." The U.S. Government's SDG Data Revolution Roadmap will outline the government's commitments-to-action from 2017-2018. With a deadline of June 2017, it will be developed by the U.S. Government "through an open and inclusive process that engages the full range of citizen, non-governmental, and private sector stakeholders."This report represents the beginning of that engagement process. On December 14, 2016, the Center for Open Data Enterprise and the Global Partnership for Sustainable Development Data convened a Roundtable to develop recommended priorities for the U.S. Government's SDG Data Revolution Roadmap The Roundtable brought together more than 40 stakeholders from government, civil society, and the private sector with expertise in achieving and promoting sustainable development

Simulation Models for Analyzing the Dynamic Costs of Process-aware Information Systems

Introducing process-aware information systems (PAIS) in enterprises (e.g., workflow management systems, case handling systems) is associated with high costs. Though cost estimation has received considerable attention in software engineering for many years, it is difficult to apply existing approaches to PAIS. This difficulty particularly stems from the inability of existing estimation techniques to deal with the complex interplay of the many technological, organizational and project-driven factors which emerge in the context of PAIS. In response to this problem, this paper proposes an approach which utilizes simulation models for investigating the dynamic costs of PAIS engineering projects. We motivate the need for simulation, discuss the development and execution of simulation models, and give an illustrating example. The present work has been accomplished in the EcoPOST project, which deals with the development of a comprehensive evaluation framework for analyzing PAIS engineering projects from a value-based perspective