Pseudonymization is a data management and de-identification procedure by which personally identifiable information fields within a data record are replaced by one or more artificial identifiers, or pseudonyms. A single pseudonym for each replaced field or collection of replaced fields makes the data record less identifiable while remaining suitable for data analysis and data processing. Pseudonymization (or pseudonymisation, the spelling under European guidelines) is one way to comply with the European Union's General Data Protection Regulation (GDPR) demands for secure data storage of personal information. Pseudonymized data can be restored to its original state with the addition of information which allows individuals to be re-identified. In contrast, anonymization is intended to prevent re-identification of individuals within the dataset. Clause 18, Module Four, footnote 2 of the Adoption by the European Commission of the Implementing Decisions (EU) 2021/914 "requires rendering the data anonymous in such a way that the individual is no longer identifiable by anyone ... and that this process is irreversible." == Impact of Schrems II ruling == The European Data Protection Supervisor (EDPS) on 9 December 2021 highlighted pseudonymization as the top technical supplementary measure for Schrems II compliance. Less than two weeks later, the EU Commission highlighted pseudonymization as an essential element of the equivalency decision for South Korea, which is the status that was lost by the United States under the Schrems II ruling by the Court of Justice of the European Union (CJEU). The importance of GDPR-compliant pseudonymization increased dramatically in June 2021 when the European Data Protection Board (EDPB) and the European Commission highlighted GDPR-compliant pseudonymization as the state-of-the-art technical supplementary measure for the ongoing lawful use of EU personal data when using third country (i.e., non-EU) cloud processors or remote service providers under the "Schrems II" ruling by the CJEU. Under the GDPR and final EDPB Schrems II Guidance, the term pseudonymization requires a new protected "state" of data, producing a protected outcome that: Protects direct, indirect, and quasi-identifiers, together with characteristics and behaviors; Protects at the record and data set level versus only the field level so that the protection travels wherever the data goes, including when it is in use; and Protects against unauthorized re-identification via the mosaic effect by generating high entropy (uncertainty) levels by dynamically assigning different tokens at different times for various purposes. The combination of these protections is necessary to prevent the re-identification of data subjects without the use of additional information kept separately, as required under GDPR Article 4(5) and as further underscored by paragraph 85(4) of the final EDPB Schrems II guidance: Article 4(5) "Definitions" of the GDPR defines pseudonymization as "the processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person." "Use Case 2: Transfer of pseudonymised Data Paragraph 85(4)" of the final EDPB Schrems II Guidance requires that “the controller has established by means of a thorough analysis of the data in question – taking into account any information that the public authorities of the recipient country may be expected to possess and use – that the pseudonymised personal data cannot be attributed to an identified or identifiable natural person even if cross-referenced with such information." GDPR-compliant pseudonymization requires that data is "anonymous" in the strictest EU sense of the word – globally anonymous – but for the additional information held separately and made available under controlled conditions as authorized by the data controller for permitted re-identification of individual data subjects. Clause 18, Module Four, footnote 2 of the Adoption by the European Commission of the Implementing Decision (EU) 2021/914 "requires rendering the data anonymous in such a way that the individual is no longer identifiable by anyone, in line with recital 26 of Regulation (EU) 2016/679, and that this process is irreversible." Before the Schrems II ruling, pseudonymization was a technique used by security experts or government officials to hide personally identifiable information to maintain data structure and privacy of information. Some common examples of sensitive information include postal code, location of individuals, names of individuals, race and gender, etc. After the Schrems II ruling, GDPR-compliant pseudonymization must satisfy the above-noted elements as an "outcome" versus merely a technique. == Data fields == The choice of which data fields are to be pseudonymized is partly subjective. Less selective fields, such as birth date or postal code are often also included because they are usually available from other sources and therefore make a record easier to identify. Pseudonymizing these less identifying fields removes most of their analytic value and is therefore normally accompanied by the introduction of new derived and less identifying forms, such as year of birth or a larger postal code region. Data fields that are less identifying, such as date of attendance, are usually not pseudonymized. This is because too much statistical utility is lost in doing so, not because the data cannot be identified. For example, given prior knowledge of a few attendance dates it is easy to identify someone's data in a pseudonymized dataset by selecting only those people with that pattern of dates. This is an example of an inference attack. The weakness of pre-GDPR pseudonymized data to inference attacks is commonly overlooked. A famous example is the AOL search data scandal. The AOL example of unauthorized re-identification did not require access to separately kept "additional information" that was under the control of the data controller as is now required for GDPR-compliant pseudonymization, outlined below under the section "New Definition for Pseudonymization Under GDPR". Protecting statistically useful pseudonymized data from re-identification requires: a sound information security base controlling the risk that the analysts, researchers or other data workers cause a privacy breach The pseudonym allows tracking back of data to its origins, which distinguishes pseudonymization from anonymization, where all person-related data that could allow backtracking has been purged. Pseudonymization is an issue in, for example, patient-related data that has to be passed on securely between clinical centers. The application of pseudonymization to e-health intends to preserve the patient's privacy and data confidentiality. It allows primary use of medical records by authorized health care providers and privacy preserving secondary use by researchers. In the US, HIPAA provides guidelines on how health care data must be handled and data de-identification or pseudonymization is one way to simplify HIPAA compliance. However, plain pseudonymization for privacy preservation often reaches its limits when genetic data are involved (see also genetic privacy). Due to the identifying nature of genetic data, depersonalization is often not sufficient to hide the corresponding person. Potential solutions are the combination of pseudonymization with fragmentation and encryption. An example of application of pseudonymization procedure is creation of datasets for de-identification research by replacing identifying words with words from the same category (e.g. replacing a name with a random name from the names dictionary), however, in this case it is in general not possible to track data back to its origins. == New definition under GDPR == Effective as of May 25, 2018, the EU General Data Protection Regulation (GDPR) defines pseudonymization for the very first time at the EU level in Article 4(5). Under Article 4(5) definitional requirements, data is pseudonymized if it cannot be attributed to a specific data subject without the use of separately kept "additional information". Pseudonymized data embodies the state of the art in Data Protection by Design and by Default because it requires protection of both direct and indirect identifiers (not just direct). GDPR Data Protection by Design and by Default principles as embodied in pseudonymization require protection of both direct and indirect identifiers so that personal data is not cross-referenceable (or re-identifiable) via the "mosaic effect" without access to "additional information" that is kept separately by the controller. Because access to separately kept "additional information" is required
Law practice management software
Law practice management software is software designed to manage the business operations of a law firm. This can include software that manages cases, client intake, court communications, electronic discovery, time tracking, trust accounting, and billing. == Features of law practice management software == Common features of practice management software include: Case management Time tracking Document assembly Contact management Calendaring Docket management Client portal Contract Management Court Case Status Tracker Trust accounting == Examples of law practice management software == Smokeball LEAP Legal Software PracticeEvolve Dye & Durham
Visual Expert
Visual Expert is a static code analysis tool, extracting design and technical information from software source code by reverse-engineering, used by programmers for software maintenance, modernization or optimization. It is designed to parse several programming languages at the same time (PL/SQL, Transact-SQL, PowerBuilder...) and analyze cross-language dependencies, in addition to each language's source code. Visual Expert checks source code against hundreds of code inspection rules for vulnerability assessment, bug fix, and maintenance issues. == Features == Cross-references exploration: Impact Analysis, E/R diagrams, call graphs, CRUD matrix, dependency graphs. Software documentation: a documentation generator produces technical documentation and low-level design descriptions. Inspect the code to detect bugs, security vulnerabilities and maintainability issues. Native integration with Jenkins. Reports on duplicate code, unused objects and methods and naming conventions. Calculates software metrics and source lines of code. Code comparison: finds differences between several versions of the same code. Performance analysis: identifies code parts that slow down the application because of their syntax - it extracts statistics about code execution from the database and combines it with the static analysis of the code. == Usage == Visual Expert is used in several contexts: Change impact analysis: evaluating the consequences of a change in the code or in a database. Avoiding negative side effects when evolving a system. Static Application Security Testing (SAST): detecting and removing security issues. Continuous Integration / Continuous Inspection : adding a static code analysis job in a CI/CD workflow to automatically verify the quality and security of a new build when it is released. Program comprehension: helping programmers understand and maintain existing code, or modernize legacy systems. Transferring knowledge of the code, from one programmer to another. Software sizing: calculating the size of an application, or a piece of code, in order to estimate development efforts. Code review: improving the code by finding and removing code smells, dead code, code causing poor performances or violations of coding conventions. == Limitations == As a static code analyzer, Visual Expert is limited to the programming languages supported by its code parsers - Oracle PL/SQL, SQL Server Transact-SQL, PowerBuilder. A preliminary reverse engineering is required. Visual Expert does it automatically, but its duration depends on the size of the code parsed. Users must wait for the parsing completion prior to using the features, or schedule it in advance. They must also allocate sufficient hardware resources to support their volume of code. Visual Expert is based on a client/server architecture: the code analysis is running on a Windows PC - preferably a server. The information extracted from the code is stored in a RDBMS, communicating with a client application installed on the programmer's computer - no web client is available. This requires that the code, the parsers, the RDBMS and the programmers’ computers are connected to the same LAN or VPN. == History == 1995- 1998 - Prog and Doc - Initial version distributed on the French market 2001 - Visual Expert 4.5 2003 - Visual Expert 5 2007 - Visual Expert 5.7 2010 - Visual Expert 6.0 2015 - Visual Expert 2015 - Server component added to schedule code analyses 2016 - Visual Expert 2016 - Oracle PL/SQL code parser, code inventory (lines of code, number of objects…) 2017 - Visual Expert 2017 - SQL Server T-SQL code parser, Code comparison, CRUD matrix 2018 - Visual Expert 2018 - DB Code Performance Analysis, integration with TFS 2019 - Visual Expert 2019 - Generation of E/R diagrams from the code 2020 - Visual Expert 2020 - Object dependency matrix, naming consistency verification, integration with GIT and SVN 2021 - Visual Expert 2021 - Continuous Code Inspection, integration with Jenkins 2022 - Visual Expert 2022 - Support for cloud-based repositories and large volumes of code 2023 - Visual Expert 2023 - Performance tuning for PowerBuilder 2024 - Visual Expert 2024 - New web UI to simplify deployment and use among large teams. 2025 - Visual Expert 2025 - AI-based features to explain code, generate comments, and optimize queries
Quickly (software)
Quickly is a framework for creating software programs for a Linux distribution using Python, PyGTK, Glade Interface Designer and Desktop Couch. It then allows for easy publishing using bzr and Launchpad. Quickly is designed to speed up the start of new projects with the use of templates, not only for programs but for any type of project. These templates are used to automate project configuration and maintenance. Delegating into templates and not into a specific library allows projects created using Quickly not to require dependencies on any particular library or runtime of Quickly itself. The project was started by Rick Spencer after his frustration as a beginner Ubuntu developer. == Updates == Last available software update is on 2013-01-31 for Ubuntu 11.04.
ShowDocument
ShowDocument is an online web application that allows multiple users to conduct web meetings, upload, share and review documents from remote locations. The service was developed by the HBR Labs company, established in 2007. == Features == Users can collaborate on and review documents in real time, with annotations and text being visible to all users and accessible for co-editing. The idea of every user being able to annotate can cause conflicts within the sessions, and so main navigation options are under the "presenter"'s control - which can be given to a different user as well. An earlier version of the application, by contrast, had allowed all users to navigate and edit at once, causing the system to drop all incomplete edits. It is possible to draw and write on a virtual whiteboard, and to stream a YouTube video to a group in full synchronization. A feature also exists for co-browsing of Google Maps. Entering an open session in the application can be done with a given code number, or by receiving a link through an Email message. Different file formats can be uploaded and saved either online or offline, such as PDF. A PDF file's text cannot be edited - text is edited through the separate text editor. Although the platform contains a text chat, it is not intended to replace instant messaging software, as there are no extensive messaging features. The application has a paid and free version, with the free version having a few limitations: audio and video options are disabled, number of participants is limited and sessions are time-limited. == Development == ShowDocument was first developed in 2007. On September 8, 2009, HBR labs released a new update which included features such as secure online document storage and mobile device support.
Stencil buffer
A stencil buffer is an extra data buffer, in addition to the color buffer and Z-buffer, found on modern graphics hardware. The buffer is per pixel and works on integer values, usually with a depth of one byte per pixel. The Z-buffer and stencil buffer often share the same area in the RAM of the graphics hardware. In the simplest case, the stencil buffer is used to limit the area of rendering (stenciling). More advanced usage of the stencil buffer makes use of the strong connection between the Z-buffer and the stencil buffer in the rendering pipeline. For example, stencil values can be automatically increased/decreased for every pixel that fails or passes the depth test. The simple combination of depth test and stencil modifiers make a vast number of effects possible (such as stencil shadow volumes, Two-Sided Stencil, compositing, decaling, dissolves, fades, swipes, silhouettes, outline drawing, or highlighting of intersections between complex primitives) though they often require several rendering passes and, therefore, can put a heavy load on the graphics hardware. The most typical application is still to add shadows to 3D applications. It is also used for planar reflections. Other rendering techniques, such as portal rendering, use the stencil buffer in other ways; for example, it can be used to find the area of the screen obscured by a portal and re-render those pixels correctly. The stencil buffer and its modifiers can be accessed in computer graphics by using APIs like OpenGL, Direct3D, Vulkan or Metal. == Architecture == The stencil buffer typically shares the same memory space as the Z-buffer, and typically the ratio is 24 bits for Z-buffer + 8 bits for stencil buffer or, in the past, 15 bits for Z-buffer + 1 bit for stencil buffer. Another variant is 4 + 24, where 28 of the 32 bits are used and 4 ignored. Stencil and Z-buffers are part of the frame buffer, coupled to the color buffer. The first chip available to a wider market was 3Dlabs' Permedia II, which supported a one-bit stencil buffer. The bits allocated to the stencil buffer can be used to represent numerical values in the range [0, 2n-1], and also as a Boolean matrix (n is the number of allocated bits), each of which may be used to control the particular part of the scene. Any combination of these two ways of using the available memory is also possible. == Stencil test == Stencil test or stenciling is among the operations on the pixels/fragments (Per-pixel operations), located after the alpha test, and before the depth test. The stencil test ensures undesired pixels do not reach the depth test. This saves processing time for the scene. Similarly, the alpha test can prevent corresponding pixels to reach the stencil test. The test itself is carried out over the stencil buffer to some value in it, or altered or used it, and carried out through the so-called stencil function and stencil operations. The stencil function is a function by which the stencil value of a certain pixel is compared to a given reference value. If this comparison is logically true, the stencil test passes. Otherwise not. In doing so, the possible reaction caused by the result of comparing three different state-depth and stencil buffer: Stencil test is not passed Stencil test is passed but not the depth test Both tests are passed (or stencil test is passed, and the depth is not enabled) For each of these cases, different operations can be set over the examined pixel. In the OpenGL stencil functions, the reference value and mask, respectively, define the function glStencilFunc. In Direct3D each of these components is adjusted individually using methods SetRenderState devices currently in control. This method expects two parameters, the first of which is a condition that is set and the other its value. In the order that was used above, these conditions are called D3DRS_STENCILFUNC, D3DRS_STENCILREF, and D3DRS_STENCILMASK. Stencil operations in OpenGL adjust glStencilOp function that expects three values. In Direct3D, again, each state sets a specific method SetRenderState. The three states that can be assigned to surgery are called D3DRS_STENCILFAIL, D3DRENDERSTATE_STENCILZFAIL, and D3DRENDERSTATE_STENCILPASS. == Z-fighting == Due to the lack of precision in the Z-buffer, coplanar polygons that are short-range, or overlapping, can be portrayed as a single plane with a multitude of irregular cross-sections. These sections can vary depending on the camera position and other parameters and are rapidly changing. This is called Z-fighting. There exist multiple solutions to this issue: - Bring the far plane closer to restrict the scene's depth, thus increasing the accuracy of the Z-buffer, or reducing the distance at which objects are visible in the scene. - Increase the number of bits allocated to the Z-buffer, which is possible at the expense of memory for the stencil buffer. - Move polygons farther apart from one another, which restricts the possibilities for the artist to create an elaborate scene. All of these approaches to the problem can only reduce the likelihood that the polygons will experience Z-fighting, and do not guarantee a definitive solution in the general case. A solution that includes the stencil buffer is based on the knowledge of which polygon should be in front of the others. The silhouette of the front polygon is drawn into the stencil buffer. After that, the rest of the scene can be rendered only where the silhouette is negative, and so will not clash with the front polygon. == Shadow volume == Shadow volume is a technique used in 3D computer graphics to add shadows to a rendered scene. They were first proposed by Frank Crow in 1977 as the geometry describing the 3D shape of the region occluded from a light source. A shadow volume divides the virtual world in two: areas that are in shadow and areas that are not. The stencil buffer implementation of shadow volumes is generally considered among the most practical general-purpose real-time shadowing techniques for use on modern 3D graphics hardware. It has been popularised by the video game Doom 3, and a particular variation of the technique used in this game has become known as Carmack's Reverse. == Reflections == Reflection of a scene is drawn as the scene itself transformed and reflected relative to the "mirror" plane, which requires multiple render passes and using of stencil buffer to restrict areas where the current render pass works: Draw the scene excluding mirror areas – for each mirror lock the Z-buffer and color buffer Render visible part of the mirror Depth test is set up so that each pixel is passed to enter the maximum value and always passes for each mirror: Depth test is set so that it passes only if the distance of a pixel is less than the current (default behavior) The matrix transformation is changed to reflect the scene relative to the mirror plane Unlock the Z-buffer and color buffer Draw the scene, but only the part of it that lies between the mirror plane and the camera. In other words, a mirror plane is also a clipping plane Again locks color buffer, depth test is set so that it always passes, reset stencil for the next mirror. == Planar Shadows == While drawing a plane of shadows, there are two dominant problems: The first concerns the problem of deep struggle in case the flat geometry is not awarded on the part covered with the shadow of shadows and outside. See the section that relates to this. Another problem relates to the extent of the shadows outside the area where the plane there. Another problem, which may or may not appear, depending on the technique, the design of more polygons in one part of the shadow, resulting in darker and lighter parts of the same shade. All three problems can be solved geometrically, but because of the possibility that hardware acceleration is directly used, it is a far more elegant implementation using the stencil buffer: 1. Enable lights and the lights 2. Draw a scene without any polygon that should be projected shadows 3. Draw all polygons which should be projected shadows, but without lights. In doing so, the stencil buffer, the pixel of each polygon to be assigned to a specific value for the ground to which they belong. The distance between these values should be at least two, because for each plane to be used two values for two states: in the shadows and bright. 4. Disable any global illumination (to ensure that the next steps will affect only individual selected light) For each plane: For each light: 1. Edit a stencil buffer and only the pixels that carry a specific value for the selected level. Increase the value of all the pixels that are projected objects between the date of a given level and bright. 2. Allow only selected light for him to draw level at which part of her specific value was not changed. == Spatial shadows == Stencil buffer implementation of spatial drawing shadows is any shadow of a geometric body that its volume includes part of the scene that is
Twproject
Twproject (say: T W Project) is a web-based project and groupware management tool created by Open Lab, an Italian software house founded in 2001. It won the 17th Jolt Productivity Award in 2007 in the project management category. In March 2019 it becomes property of Twproject company. It has widespread use in universities as a teaching tool in project management courses. It is used by Oracle Corporation, Prada, Calzedonia, General Electric and many other companies from corporations to small start-ups. == History == April 2001 - The idea of Teamwork came to Open-Lab founders from a need to overcome the PM tools used at that time. It was built in Microsoft ASP and Adobe Flash November 2002 - Open-Lab decide to move from Flash to HTML and from ASP to Java-JSP. Teamwork 2 development is started. June 2004 - Teamwork 2 released, using top open-source technologies like Hibernate, jBlooming, dynamic CSS, Ajax 7 January 2005 - Teamwork goes open source, under LGPL license; remains such until June 2006 (18 months): it is a hit application on SourceForge, with 38.000 downloads, covered by greeting but starving April 2005 - Open-Lab takes the decision to change commercial strategy to finance development of Teamwork version 3 6 June 2006 - Teamwork 3 is finally out (15 months development). New interface, many new features, agile support and much more 27 March 2007 - Teamwork wins the 2007 JOLT Productivity Awards for project management category July 2007 - Teamwork 4 development started: new interface, extended use of new HTML capabilities, JS-oriented interface, start using jQuery February 2009 - Teamwork 4.0 is out February 2010 - Teamwork 4.4: public project pages, Chinese interface. jQuery is getting more space in Teamwork December 2010 - Teamwork 4.6: released Mobile module available for iPhone, Android, BlackBerry. Intensive usage of jQuery June 2011 - Teamwork 4.7: released Issue Kanban / Organizer January 2012 - Teamwork 5.0 development started. Lighter interface, extensive usage of dynamic pages, easier installer and first time approach. Learning curve highly reduced. A jQuery Gantt editor included and released free for the community July 2012 - Teamwork 5 released and also the free online Gantt editor November 2012 - Teamwork 5.1 with new trees and improved model for staffing March 2013 - Teamwork 5.2 with stronger support for customizations and Japanese interface. April 2014 - Teamwork has changed its name in Twproject because the domain teamwork.com has been purchased by Teamwork. April 2013 - Twproject 5.4 with a redesigned more powerful Gantt chart. August 2015 - Twproject 5 finale release. September 2015 - Twproject 6 with a completely redesigned user interface. March 2019 - A new company Twproject srl has been spun off. September 2021 - Twproject 7 has been released introducing WBS based management and workload management. == Features == Project & task management (with Microsoft Project import/export), and JSON format Gantt editor. Uses jQuery Gantt components Time tracking. Several entry points: dashboard, weekly view, issues, start/stop buttons Resource planning with weekly/monthly view, work load overview, unavailability from agenda Issue tracking & planning(with Kanban), e-mail integration, task dedicated inboxes Dashboard configuration, with customizable portlets and layout Message boards Scrum module Meeting and minute management, attached documents Agenda (Integrates with iCal, Microsoft Outlook, Microsoft Entourage, and Google Calendar) Document management, remote file systems link with NTFS, FTP, SVN, S3 (Dropbox, Google drive) Mobile application for iPhone, iPad, Android, Blackberry, Windows phone == Integration == A complete JSON API is available for integrations. The applications runs in Java JDK 8+ on the Hibernate object/relational mapping. The standard distribution uses Apache Tomcat 9, but can run on any J2EE application server. Twproject is tested on these DB servers: MySQL, Oracle, SQL Server, PostgreSql, HSQLDB, but as uses Hibernate can run on many others. There is simple graphical step-by-step installer for Windows, Mac, Linux, .zip/.tar.gz/.rpm packages.