In the United States, most members of the public don't know about the federal rulemaking process and don't participate even on major issues that affect them, like consumer-debt collection practices or airline passenger rights. Our team of researchers at Cornell set out to address this gap, working with federal agencies to take public comment during live, ongoing federal agency rulemakings while developing and testing an online platform paired with live human facilitation.
This poster will present our work in progress in the development of a series of data masking standards and applications for the compliance of security policies in the context of open government data. Our current efforts focus on the feasibility analysis to use data masking technologies in datasets processing, access and download.
As a typical practice of Open Government Data, OnTheMap for Emergency Management Shows potential impact on jobs/workers and population for hurricanes, tropical storms, fires, floods, snow and freezing rain probability and disaster declaration areas based on real-time geographic data of disaster events are automatically updated. We can explore that Open Government Data can not only help city agencies make decision on staffing, communication and deployment of resource, but also improve city's resilience and recovery, to improve our ability to protect life, property and environment.
Scholars and practitioners around the world frequently talk about the importance of focusing on the citizen when developing e-government applications. However, there is no clarity in terms of how much of the benefits from the use of information technologies impact citizens and/or government agencies. Based on a review of exiting literature, this poster identifies diverse results of electronic government and analyzes to what extent those results impact citizens and/or government agencies. We think that this understanding is a key aspect to develop and study better user-centered approaches. Results have been categorized in three clusters: (1) for users, (2) for government agencies, and (3) for both.
Edimara Luciano, Marie Anne Macadar, Guilherme Wiedenhöft
390 - 391
IT Governance must be part of e-governance initiatives as a way to promote long-term solutions and increment their effectiveness. We suggest a conceptual model to understand the demands in an integrated way focused on long–term solutions in order to add organicity and transparency throughout the process and to reduce the complexity. The higher the complexity, the higher the transaction costs, which may compromise future investments on new e-government initiatives.
Rosario Pérez Morote, Carolina Pontones Rosa, Martin Reynolds
392 - 393
Practice intelligence (PI) is a new notion that refers to the learned expertise of sense making of problem spaces and the aligned learned expertise relating to appropriate decision/action in a particular problem space. Exploring Practice Intelligence in E-government research involves to specify and codify into academic knowledge the internal cognitive structures of designing and synthesizing the information used by e-government policy makers and practitioners.
Businesses already entered social networks and use them actively as communication, marketing, sales, and customer support channels. In the recent years, municipalities and state administrations started to use social networks to reach their constituents although this practice is not consistent. The research is devoted on a development of a platform that allows to monitor and to analyze the presence of municipalities in Facebook. Some initial results are presented. The presence in Facebook of 264 municipalities in Bulgaria was monitored and analyzed in years 2014 and 2016. The platform http://socialpresence.azurewebsites.net/ is open to monitor and analyze municipalities' presence and performance in Facebook of municipalities all over the world.
This workshop is a working meeting of the Smart Cities Smart Government Research-Practice Consortium. The main goal of the workshop is to continue conversations started since 2012. This workshop will build on SCSGRP Consortium meetings held at dg.o 2015, IFIP/egov 2015, and HICSS 2016.
With the comprehensive digitalization of the workplace and of privacy, we face complex challenges. Information Security awareness is a necessary response. In the workshop we demonstrate analogue game-based awareness learning in a three phases procedure for the digital world.
There is much potential for open and big data to be used for addressing societal challenges of today. This drives a new kind of partnership called “data collaborative” emphasizing the value of data for public good. Data collaboratives stand for cross-sector partnerships, whereby organizations in the private or public sector disclose their data, as an act of good will, in order to contribute to a societal cause (such as e.g. healthcare, humanitarian, or other policy issues). In this workshop we focus on this emerging topic which so far has deserved little attention in research. In our previous research an initial framework of influential factors for data collaboratives was introduced. The workshop objective is to validate and refine this initial framework by inviting participants to take part in an interactive live polling exercise and assess a number of propositions about influential factors.
Efthimios Tambouris, Marijn Janssen, Evangelos Kalampokis, Bill Roberts, Paul Hermans, Jamie Whyte, Trevor Alcorn, Konstantinos Tarabanis
407 - 408
Opening up data is a political priority worldwide. Linked open data is considered as the most mature technology for publishing and reusing open data. A large number of open data is numerical and actually concerns statistics. In the literature, statistical data have been heavily studied using the data cube model. Recently, ICT tools have emerged aiming to exploit linked open data technologies for providing advanced visualizations and analytics of open statistical data residing in geographically dispersed open data portals. The aim of this panel is to discuss the potential and challenges of open statistical data.