User:Bryankjh/sandbox

Response to peer reviews
Although I didn't get any peer reviews for my article yet, reading the guide and having a one-on-one conference with Professor Harris gave me lots of ideas on how I can further improve my edits to this article. One of the most important things I talked about with Professor Harris during the conference was the importance of maintaining neutrality in my article, so that one position does not seem to overpower another. I think I have to be careful that my potential criticisms section is not too overpowering, and some direct suggestions I received to help remedy this is by including more information about VALCRI, and even adding pictures of their logo would allow the article to seem a lot more neutral. I think one other important advice I got from the conference was to explore deeper into literature available about the numerous biases that can arise from data analysis and imaging software, especially in a law enforcement and crime prevention landscape.

Another important piece of feedback I received was increasing the frequency of citations that I use in my article. I will take this into consideration to ensure that there are more citations and references that I can add to the article and I will go over my article and use the Cite function more frequently so that there can be more hyperlinked citations on my article as a whole.

I think after this conference, my plan in my revisions it to improve the overall structure of the article so that it is layered and ordered in a logical manner. I also need to change the header of my Potential Roadblocks section so that it is more in line with other Wikipedia articles. I will explore the additional sources of literature that were recommended and see if I need to add any more sections so that I can paint a better context of visual analytics and some of the problems that can arise. I also plan to find one or two relevant pictures that I can add to the page, such as the logo of VALCRI. I'll continue to ensure that notability and grammatical errors are fixed and will keep an eye out on the Talk page in case I get additional suggestions.

Introduction
Original: Visual Analytics for Sense-making in CRiminal Intelligence analysis (VALCRI)is a software tool that helps investigators to find related or relevant information in several criminal databases. It is used by various police agencies.

Edited: Visual Analytics for Sense-making in Criminal Intelligence analysis (VALCRI) is a software tool that helps investigators to find related or relevant information in several criminal databases. The software uses big data processes to aggregate information from a wide array of different sources and formats and compiles it into visual and readable arrangements for users. It is used by various law enforcement agencies and aims to allow officials to utilize statistical information in their operations and strategy . 

Edit Summary: For this paragraph, I got rid of some of the basic notability issues, such as the capitalized R and errors in spacing. In addition, I linked this paragraph to another Wikipedia article for big data. I also added to each of the sentences and added 2 citations to this paragraph so that I could give a more in depth and holistic overview of what VALCRI was and how it was aimed to help law enforcement.

Automated Search
Original: The tool automatically searches the databases using dedicated search engines with one click. Normally, investigators would need to do an estimated 73 separate SQL queries for searching the various databases and this would take up to 3 days. The tool identifies similarities between cases, performs associative searching and comes up with reports in the same area and timeframe. 

Edited: VALCRI can automatically search numerous databases using dedicated search engines. Previously, investors would need to employ an average of 73 SQL queries and wait up to 3 days to find the right case studies . The tool utilizes machine learning mechanisms to screen through masses of unstructured data to identify similarities between cases, and performs associative searching to comes up with reports based on the search criteria of users.

Data Visualization
Another important feature of VALCRI is the ability to visualize and present data and information in visual formats such as maps, timelines, dispersion diagrams, and process charts. This creates an Analyst User Interface dashboard that is designed to be integrated within the workforce and allow for investigative reasoning based on database information. The visualizations are interactive and encourages cooperative input from human analysis.

VALCRI also employs algorithms such as PCA, MDS, and t-SNE to embed data points into graphical representations. This feature allows for the statistical and mathematical calculation of similarity and correlation levels between different crime data sets through different algorithmic models which each have their own strengths and weaknesses.

Edit Summary: I changed the original paragraph by changing notability by adjusting the sentence structure. I added a citation for the first sentence, and also liked a Wikipedia article regarding machine learning, which was one of the things that this article was originally flagged for. I also added two other paragraphs for this general section, because the original version only really listed one feature of VALCRI. I used my reading of different sources to add two other distinct features that VALCRI offers. I added a Wikipedia link to t-SNE which is a data embedding algorithm and also added two new citations for the paragraphs.

Legal and Ethical Challenges
During the development of VALCRI, an Independent Ethics Board (IEB) and Security, Privacy, and Legal Group (SEPL) was created to monitor potential ethical challenges and roadblocks that the project would introduce. With the specialists in these boards, there were numerous concerns that were identified in respect to potential ethics and legality issues.

One issue that was identified by these boards was potential complications with human privacy. With the advent of a comprehensive database system that would be able to share billions of different data points for law enforcement, VALCRI faces potential roadblocks in navigating through different regional policies and laws regarding data privacy and security. This potential issue has been addressed by VALCRI by creating a dedicated group supervising data management policy in the software.

Cognitive and Sense-making Bias
VALCRI's powerful data analysis capabilities offer criminal analysts a wider set of data points to base their conclusions off of. Vienna University of Technology's research based on 120 different case studies introduces the risk of cognitive and sense-making bias playing a significant role in influencing the conclusions that law enforcement agents draw on based on the visualizations provided by VALCRI. These risks can be mitigated in VALCRI by redesigning machine learning models and implementing de-biasing mechanisms such as Klein's data frame model so that it becomes easier to identify cognitive bias and adjust analysis objectives based on the findings.

Edit Summary: This is a new heading and the sections that I want to add for the VALCRI article. I think that one aspect that it is missing is the potential roadblocks and challenges that are implicated with the technology. I think it's important to have a section regarding some of the risks that VALCRI poses in order for the article as a whole to be comprehensive and neutral. For this heading, I added three paragraphs divided up into two overall sections regarding legal and ethical challenges and bias. I was able to link to two Wikipedia articles regarding privacy and data management and add a total of 4 different citations for this heading.

Final Draft Contribution Summary:

- Edited the two paragraphs present in the original article. Added five additional paragraphs that I think is necessary for the content to be holistic.

- Total of 14 citations (10 unique sourceS)

- Link to 5 additional Wikipedia articles

- The main goal of this contribution draft was to address the areas this article was flagged for, which included notability issues and the fact that it needs more links to other Wikipedia articles. I think I was able to accomplish this also added more content to the article as a whole.

Evaluating an Article
Information Privacy - Everything seems relevant to the topic. The only section that slightly distracted me was the US Safe Harbor program being made as its own separate section. There are some sources that are more than 15 years old but there is nothing specific that needs to be added and there does not seem to be any equity gaps. The article does a good job or remaining natural and there are no viewpoints that are underrepresented or overrepresented. The citation links works and the sources seem to come from diverse and credible sources. In the talk page, there are ongoing conversations about specific sections of the article, such as the "Information should be free" line. This article is rated as C-class and is a part of WikiProject Computing and WikiProject Internet.

컴퓨터 보안 - The content in this article is all directly relevant to the section and there were not parts that distracted me away from the central topic. The most recent source from the citation seem to be from 2018 and seems to be relatively well up to date. There is a neutral tone throughout the article and there are no major equity gaps or viewpoints that are overrepresented. All of the citation links work and come from peer-reviewed sources. In the talk page, there is a discussion about some of the changes that were made to this article, such as the added citations and changed links. This article is not rated yet and is part of the 위키프로젝트 컴퓨터 과학 WikiProject.

Choosing an Article
I decided to focus on the article VALCRI to edit. I think that there are lots of aspects to the article that can be improved. First, I can add a lot of sources to this article, and I can link it to more articles in Wikipedia, which is something that the article has already been flagged for. There are also lots of notability aspects that can be fixed as well, and this is something that is flagged in the article as well. Lastly, content-wise, there is a lot of stuff that I can add as it is currently just a total of 4 sentences.

Bibliography:

Wong, B. L., Leishi Zhang, and Ifan DH Shepherd. "VALCRI: Addressing european needs for information exploitation of large complex data in criminal intelligence analysis." (2014).

Schlehahn, Eva, et al. "The Operationalisation of Transparency in VALCRI." VALCRI White Paper Series(2017).

Duquenoy, P., et al. "Addressing Ethical Challenges of Creating New Technology for Criminal Investigation: The VALCRI Project." Societal Implications of Community-Oriented Policing and Technology. Springer, Cham, 2018. 31-38.

Marquenie, Thomas, and Fanny Coudert. "Roadmap for the Operationalization of Legal and Privacy Requirements in VALCRI." VALCRI White Paper Series (2017).

Marquenie, Thomas. "Data analytics in a police context–addressing legal issues in VALCRI." (2017).

Sacha, Dominik, et al. "Applying Visual Interactive Dimensionality Reduction to Criminal Intelligence Analysis." VALCRI White Paper Series 1 (2017).

Pohl, Margit, et al. "Sensemaking and cognitive bias mitigation in visual analytics." 2014 IEEE Joint Intelligence and Security Informatics Conference. IEEE, 2014.

Possible Articles
eRulemaking - I think that I can greatly improve the scope of this article. For the current breakdown, they give a brief background section as well as information on 2009 initiatives and reforms as well as third-party eRulemaking initiatives. I think that I can add a lot more on the background section and add a list of scholarly articles that I found through the UC Berkeley Library. I can talk more specifically about barriers to eRulemaking platform adoptions, machine learning and technical interfaces, as well as argument identification

Valcri - I think that this article can be improved in many ways. Their citation section needs improvement because most of the sources are lacking full citations. In addition, I can talk possibly about the analytic provenance of criminal intelligence analysis.

Article Evaluation
Valcri: Article Evaluation

- Everything seems relevant to the topic, and there is nothing that significantly distracts the audience away from the topic. In the very beginning, there is a small capitalization issue that is slightly disruptive and needs to be fixed.

- The article is slightly biased towards the side of VALCRI being a very efficient and useful software tool for law enforcement. I think an important perspective that needs to be added is its shortcomings and potential weaknesses compared to other mechanisms.

- As mentioned earlier, the viewpoint about how helpful VALCRI is seems to be overrepresented in this article.

- The links in the citation links redirect you to the References section of the Wikipedia article. Here, you notice that most of the References still need a full citation, so you have to press these links to see where the writer got the source.

- Each paragraph is correctly cited and sourced, but the citations are incomplete. The sources seem to be relatively neutral but there are no academic sources that discuss the other viewpoint of possible shortcomings of VALCRI, and this potential bias is not noticed.

- The information does not seem to be out of date.

- There are no conversations ongoing in the talk section about how to represent the topic. The only thing that is there is that this stub is of the following interest for WikiProject Crime.

- This article is rated as stub and is part of WikiProject Crime and WikiProject Software/Computing.

- We did not talk about this specific software or topic in class yet.

- Link to the evaluation put on Article Talk Page : Talk:VALCRI