T.F. Schuurmans
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1
A single-unit case study was conducted to gather qualitive information of the effects of data communities. The case study focussed on the Dutch open data community and consisted of two parts, a document analysis and in-depth interviews. The results of the analysis show how the Dutch community contributes to enhancing open data benefits, including (indirectly) creating more informed citizens, increasing the access to capacity and resources outside of the data publishing organisation and a higher problem-solving capacity. Furthermore, the interview participants agree to a large extent that communities contribute to intragovernmental collaboration and the use of collective intelligence to solve public problems. According to the interviewees, the community also (potentially) mitigates open data barriers such as the lack of interest in using open data (by governmental organisations). The interviewees stated that the community managers made sure every question that was posted got a sufficient answer within a reasonable amount of time and therefore the barrier stating that the data provider ignores requests and suggestions of data users could also be mitigated, as well as difficulties in the interaction with the data provider. Both researchers and most community users and managers argued that the community could also contribute to mitigating low engagement of public managers with open data and increasing the knowledge and skills of employees to use the open data. Lastly, according to the interview participants, the community can decrease difficulty in discovering/locating data and not being able to combine and connect datasets. The interviewees were also questioned about how institutional instruments could increase the value of the open data community. Although the participants concluded that the contribution of formal instruments (such as rules) is limited, they indicated informal rules (such as norms) and enforcing instruments (such as rewards) can contribute to the value that is created by an open data community.
The community-specific challenges identified in the analysis can contribute to the process of designing an open data community, because policy makers can compare scope and design choices with the empirical experiences. This thesis also provides an exploratory scientific contribution: this research provides insight into how open data communities can contribute to enhancing open data benefits and the mitigation of open data barriers. Although the results are promising, certain limitations are applicable to the research. The thesis only studied one open data community and the full list of open data benefits and barriers was reduced based upon an assessment of the author of the thesis. Last of all, the interviews focused on qualitative data. Combining the results of this thesis with other case studies can improve generalisability.
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A single-unit case study was conducted to gather qualitive information of the effects of data communities. The case study focussed on the Dutch open data community and consisted of two parts, a document analysis and in-depth interviews. The results of the analysis show how the Dutch community contributes to enhancing open data benefits, including (indirectly) creating more informed citizens, increasing the access to capacity and resources outside of the data publishing organisation and a higher problem-solving capacity. Furthermore, the interview participants agree to a large extent that communities contribute to intragovernmental collaboration and the use of collective intelligence to solve public problems. According to the interviewees, the community also (potentially) mitigates open data barriers such as the lack of interest in using open data (by governmental organisations). The interviewees stated that the community managers made sure every question that was posted got a sufficient answer within a reasonable amount of time and therefore the barrier stating that the data provider ignores requests and suggestions of data users could also be mitigated, as well as difficulties in the interaction with the data provider. Both researchers and most community users and managers argued that the community could also contribute to mitigating low engagement of public managers with open data and increasing the knowledge and skills of employees to use the open data. Lastly, according to the interview participants, the community can decrease difficulty in discovering/locating data and not being able to combine and connect datasets. The interviewees were also questioned about how institutional instruments could increase the value of the open data community. Although the participants concluded that the contribution of formal instruments (such as rules) is limited, they indicated informal rules (such as norms) and enforcing instruments (such as rewards) can contribute to the value that is created by an open data community.
The community-specific challenges identified in the analysis can contribute to the process of designing an open data community, because policy makers can compare scope and design choices with the empirical experiences. This thesis also provides an exploratory scientific contribution: this research provides insight into how open data communities can contribute to enhancing open data benefits and the mitigation of open data barriers. Although the results are promising, certain limitations are applicable to the research. The thesis only studied one open data community and the full list of open data benefits and barriers was reduced based upon an assessment of the author of the thesis. Last of all, the interviews focused on qualitative data. Combining the results of this thesis with other case studies can improve generalisability.
Fingermarks are trace evidence of great forensic importance, and their omnipresence makes them pivotal in crime investigation. Police and law enforcement authorities have exploited fingermarks primarily for personal identification, but crucial knowledge on when fingermarks were deposited is often lacking, thereby hindering crime reconstruction. Biomolecular constituents of fingermark residue, such as amino acids, lipids and proteins, may provide excellent means for fingermark age determination, however robust methodologies or detailed knowledge on molecular mechanisms in time are currently not available. Here, we address fingermark age assessment by: (i) drafting a first protein map of fingermark residue, (ii) differential studies of fresh and aged fingermarks and (iii), to mimic real-world scenarios, estimating the effects of donor contact with bodily fluids on the identification of potential age biomarkers. Using a high-resolution mass spectrometry-based proteomics approach, we drafted a characteristic fingermark proteome, of which five proteins were identified as promising candidates for fingermark age estimation. This study additionally demonstrates successful identification of both endogenous and contaminant proteins from donors that have been in contact with various bodily fluids. In summary, we introduce state-of-the-art proteomics as a sensitive tool to monitor fingermark aging on the protein level with sufficient selectivity to differentiate potential age markers from body fluid contaminants.