User:Bryankjh/VALCRI

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.