The Resource Description Framework (RDF) is a method to describe and exchange graph data. It was originally designed as a data model for metadata by the World Wide Web Consortium (W3C). It provides a variety of syntax notations and formats, of which the most widely used is Turtle (Terse RDF Triple Language). RDF is a directed graph composed of triple statements. An RDF graph statement is represented by: (1) a node for the subject, (2) an arc from subject to object, representing a predicate, and (3) a node for the object. Each of these parts can be identified by a Internationalized Resource Identifier (IRI). An object can also be a literal value. This simple, flexible data model has a lot of expressive power to represent complex situations, relationships, and other things of interest, while also being appropriately abstract. RDF was adopted as a W3C recommendation in 1999. The RDF 1.0 specification was published in 2004, and the RDF 1.1 specification in 2014. SPARQL is a standard query language for RDF graphs. RDF Schema (RDFS), Web Ontology Language (OWL) and SHACL (Shapes Constraint Language) are ontology languages that are used to describe RDF data. == Overview == The RDF data model is similar to classical conceptual modeling approaches (such as entity–relationship or class diagrams). It is based on the idea of making statements about resources (in particular web resources) in expressions of the form subject–predicate–object, known as triples. The subject denotes the resource; the predicate denotes traits or aspects of the resource, and expresses a relationship between the subject and the object. For example, one way to represent the notion "The sky has the color blue" in RDF is as the triple: a subject denoting "the sky", a predicate denoting "has the color", and an object denoting "blue". Therefore, RDF uses subject instead of object (or entity) in contrast to the typical approach of an entity–attribute–value model in object-oriented design: entity (sky), attribute (color), and value (blue). RDF is an abstract model with several serialization formats (being essentially specialized file formats). In addition the particular encoding for resources or triples can vary from format to format. This mechanism for describing resources is a major component in the W3C's Semantic Web activity: an evolutionary stage of the World Wide Web in which automated software can store, exchange, and use machine-readable information distributed throughout the Web, in turn enabling users to deal with the information with greater efficiency and certainty. RDF's simple data model and ability to model disparate, abstract concepts has also led to its increasing use in knowledge management applications unrelated to Semantic Web activity. A collection of RDF statements intrinsically represents a labeled, directed multigraph. This makes an RDF data model better suited to certain kinds of knowledge representation than other relational or ontological models. As RDFS, OWL and SHACL demonstrate, one can build additional ontology languages upon RDF. == History == The initial RDF design, intended to "build a vendor-neutral and operating system- independent system of metadata", derived from the W3C's Platform for Internet Content Selection (PICS), an early web content labelling system, but the project was also shaped by ideas from Dublin Core, and from the Meta Content Framework (MCF), which had been developed during 1995 to 1997 by Ramanathan V. Guha at Apple and Tim Bray at Netscape. A first public draft of RDF appeared in October 1997, issued by a W3C working group that included representatives from IBM, Microsoft, Netscape, Nokia, Reuters, SoftQuad, and the University of Michigan. In 1999, the W3C published the first recommended RDF specification, the Model and Syntax Specification ("RDF M&S"). This described RDF's data model and an XML serialization. Two persistent misunderstandings about RDF developed at this time: firstly, due to the MCF influence and the RDF "Resource Description" initialism, the idea that RDF was specifically for use in representing metadata; secondly that RDF was an XML format rather than a data model, and only the RDF/XML serialisation being XML-based. RDF saw little take-up in this period, but there was significant work done in Bristol, around ILRT at Bristol University and HP Labs, and in Boston at MIT. RSS 1.0 and FOAF became exemplar applications for RDF in this period. The recommendation of 1999 was replaced in 2004 by a set of six specifications: "The RDF Primer", "RDF Concepts and Abstract", "RDF/XML Syntax Specification (revised)", "RDF Semantics", "RDF Vocabulary Description Language 1.0", and "The RDF Test Cases". This series was superseded in 2014 by the following six "RDF 1.1" documents: "RDF 1.1 Primer", "RDF 1.1 Concepts and Abstract Syntax", "RDF 1.1 XML Syntax", "RDF 1.1 Semantics", "RDF Schema 1.1", and "RDF 1.1 Test Cases". == RDF topics == === Vocabulary === The vocabulary defined by the RDF specification is as follows: ==== Classes ==== ===== rdf ===== rdf:XMLLiteral the class of XML literal values rdf:Property the class of properties rdf:Statement the class of RDF statements rdf:Alt, rdf:Bag, rdf:Seq containers of alternatives, unordered containers, and ordered containers (rdfs:Container is a super-class of the three) rdf:List the class of RDF Lists rdf:nil an instance of rdf:List representing the empty list ===== rdfs ===== rdfs:Resource the class resource, everything rdfs:Literal the class of literal values, e.g. strings and integers rdfs:Class the class of classes rdfs:Datatype the class of RDF datatypes rdfs:Container the class of RDF containers rdfs:ContainerMembershipProperty the class of container membership properties, rdf:_1, rdf:_2, ..., all of which are sub-properties of rdfs:member ==== Properties ==== ===== rdf ===== rdf:type an instance of rdf:Property used to state that a resource is an instance of a class rdf:first the first item in the subject RDF list rdf:rest the rest of the subject RDF list after rdf:first rdf:value idiomatic property used for structured values rdf:subject the subject of the RDF statement rdf:predicate the predicate of the RDF statement rdf:object the object of the RDF statement rdf:Statement, rdf:subject, rdf:predicate, rdf:object are used for reification (see below). ===== rdfs ===== rdfs:subClassOf the subject is a subclass of a class rdfs:subPropertyOf the subject is a subproperty of a property rdfs:domain a domain of the subject property rdfs:range a range of the subject property rdfs:label a human-readable name for the subject rdfs:comment a description of the subject resource rdfs:member a member of the subject resource rdfs:seeAlso further information about the subject resource rdfs:isDefinedBy the definition of the subject resource This vocabulary is used as a foundation for RDF Schema, where it is extended. === Serialization formats === Several common serialization formats are in use, including: Turtle, a compact, human-friendly format. TriG, an extension of Turtle to datasets. N-Triples, a very simple, easy-to-parse, line-based format that is not as compact as Turtle. N-Quads, a superset of N-Triples, for serializing multiple RDF graphs. JSON-LD, a JSON-based serialization. N3 or Notation3, a non-standard serialization that is very similar to Turtle, but has some additional features, such as the ability to define inference rules. RDF/XML, an XML-based syntax that was the first standard format for serializing RDF. RDF/JSON, an alternative syntax for expressing RDF triples using a simple JSON notation. RDF/XML is sometimes misleadingly called simply RDF because it was introduced among the other W3C specifications defining RDF and it was historically the first W3C standard RDF serialization format. However, it is important to distinguish the RDF/XML format from the abstract RDF model itself. Although the RDF/XML format is still in use, other RDF serializations are now preferred by many RDF users, both because they are more human-friendly, and because some RDF graphs are not representable in RDF/XML due to restrictions on the syntax of XML QNames. With a little effort, virtually any arbitrary XML may also be interpreted as RDF using GRDDL (pronounced 'griddle'), Gleaning Resource Descriptions from Dialects of Languages. RDF triples may be stored in a type of database called a triplestore. === Resource identification === The subject of an RDF statement is either a uniform resource identifier (URI) or a blank node, both of which denote resources. Resources indicated by blank nodes are called anonymous resources. They are not directly identifiable from the RDF statement. The predicate is a URI which also indicates a resource, representing a relationship. The object is a URI, blank node or a Unicode string literal. As of RDF 1.1 resources are identified by Internationalized Resource Identifiers (IRIs); IRIs are a generalization of URIs. In Semantic Web applications, and in re
AI Mode
AI Mode is a search feature used within Google Search. In March 2025, Google introduced an experimental "AI Mode" within its search platform, enabling users to input complex, multi-part queries and receive comprehensive, AI-generated responses. This feature uses Google's Gemini model, which enhances the system's reasoning capabilities and supports multimodal inputs, including text, images, and voice. Users need to be signed in to be able to use the image generation features. Initially, AI Mode was available to Google One AI Premium subscribers in the United States, who could access it through the Search Labs platform. This phased rollout allowed Google to gather user feedback and refine the feature before a broader release.
Microsoft Forms
Microsoft Forms (formerly Office 365 Forms) is an online survey creator, part of Microsoft 365. == Usage == Forms allows users to create surveys and quizzes with automatic marking. The data can be exported to Microsoft Excel, Power BI dashboards and viewed live using the Present feature. == Phishing and fraud == Due to a wave of phishing attacks utilizing Microsoft 365 in early 2021, Microsoft uses algorithms to automatically detect and block phishing attempts with Microsoft Forms. Also, Microsoft advises Forms users not to submit personal information, such as passwords, in a form or survey. It also place a similar advisory underneath the “Submit” button in every form created with Forms, warning users not to give out their password.
FarPoint Spread
FarPoint Spread is a suite of Microsoft Excel-compatible spreadsheet components available for .NET, COM, and Microsoft BizTalk Server. Software developers use the components to embed Microsoft Excel-compatible spreadsheet features into their applications, such as importing and exporting Microsoft Excel files, displaying, modifying, analyzing, and visualizing data. Spread components handle spreadsheet data at the cell, row, column, or worksheet level. This article is about the last FarPoint edition of the Spread product line. Spread is now developed by GrapeCity, Inc. Since the acquisition, Spread for Biztalk Server has been removed from the product line and SpreadJS, a JavaScript version, has been added. == History == 1991 Spread released as a DLL control as the initial product offering from FarPoint Technologies, Inc. 1990s Spread VBX released. Spread ActiveX released. These components are now known as Spread COM. 2003 Spread for Windows Forms released as a completely new managed C# version prompted by the launch of Visual Studio .NET. 2003 Spread for Web Forms (now Spread for ASP.NET) released. 2006 Spread for BizTalk released. 2009 FarPoint Technologies acquired by GrapeCity. == Versions == Spread for Windows Forms: 5.0 Spread for Web Forms: 5.0 Spread COM: 8.0 Spread for BizTalk: 3.0 === Spread for Windows Forms === FarPoint Spread for Windows Forms is a Microsoft Excel-compatible spreadsheet component for Windows Forms applications developed using Microsoft Visual Studio and the .NET Framework. Developers use it to add grids and spreadsheets to their applications, and to bind them to data sources. In version 4.0, new cell types were added to display barcodes and fractions, and exports for XML and PDF were added. === Spread for ASP.NET === FarPoint Spread for ASP.NET is a Microsoft Excel-compatible spreadsheet component for ASP.NET applications. Developers use it to add grids and spreadsheets to their applications, === Spread for COM === FarPoint Spread 8 COM allows COM and ActiveX applications to incorporate spreadsheet features. In the 1997 book Visual Basic 5 for Windows for Dummies, Wally Wang lists an early version of Spread COM in Chapter 35: The Ten Most Useful Visual Basic Add-On Programs. === Spread for BizTalk === FarPoint Spread for BizTalk Server allows developers to integrate Microsoft Excel documents into Microsoft BizTalk applications. Spread for BizTalk Server includes two components: Spreadsheet Pipeline Disassembler - Parses data from Microsoft Excel (XLS and Excel 2007 XML, CSV, TXT) documents into XML data for processing through Microsoft BizTalk Server receive pipelines. Spreadsheet Pipeline Assembler - Assembles data from Microsoft BizTalk applications into Microsoft Excel (XLS or Excel 2007 XML) or PDF documents for transport through Microsoft BizTalk Server send pipelines. Developers find it a useful tool for organizations with Microsoft BizTalk Server Enterprise Application Integration. Prior to this release, BizTalk users wanting to use Excel data had to manually open the files and copy and paste data between the two applications. == Features == These features are common to all versions. Predefined cell types, including: currency date time number percent regular expression button check box combo box hyperlink image Formula support, including: cross-sheet referencing over 300 built-in functions Import and export: import to Microsoft Excel-compatible files export to Microsoft Excel-compatible files export to HTML files export to XML files Design-time spreadsheet designer Data-binding with customizable options Hierarchical data views, with parent rows and child views Grouping of rows or columns Sorting by row or column on multiple keys Cell spanning Multiple row and column headers Bound and unbound modes == Version-Specific Features == === Spread for Windows Forms === Support for Microsoft Visual Studio 2010 Support for Windows Azure AppFabric Integrated chart control Custom cell types Cell notes Child controls Splitter bars Built-in and custom skins and styles PDF export Microsoft Excel 2007 XML Support (Office Open XML, XLSX) Floating Formula Bar Range Selection for Formula Automatic Completion (type ahead) === Spread for ASP.NET === Support for Microsoft Visual Studio 2010 Support for Windows Azure AppFabric Integrated chart control AJAX-enabled Support for Open Document Format (ODF) files Multiple edits on multiple rows without server round trips Client-side column and row resizing Load on demand, which loads data from the server as needed for viewing Native Microsoft Excel import and export In-cell editing Multiple edits on multiple rows without server round trips Client-side column and row resizing Multiple sheets Searching Filtering Validations Cell spans PDF export === Spread COM === Custom cell types Cell notes Virtual mode for data loading Unicode support Customizable printing Text tips Import and export: Microsoft Excel 97 Excel 2000 Excel 2007 (requires the .NET Framework) Enhanced printing 64 bit DLL === Spread for BizTalk === Integration of Microsoft Excel data into Microsoft BizTalk applications Design-time spreadsheet schema wizard and spreadsheet format designer == Supported document formats == Adobe Portable Document Format PDF (.pdf) HTML Web Page (.html) Microsoft Excel Workbook (.xls) Plain Text (.txt) Comma-Separated Values (.csv) Open Document Format (Spread for ASP.NET)
Multicloud
Multicloud (also written as multi-cloud or multi cloud) is a term with varying interpretations, generally referring to a system using multiple cloud computing providers. According to ISO/IEC 22123-1: "multi-cloud is a cloud deployment model in which a customer uses public cloud services provided by two or more cloud service providers". Multi-cloud can involve various deployment models, including public, private, and hybrid clouds, and multiple service models, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Multicloud incorporates workload, data, traffic, and workflow portability options, which can result in varying implementation complexity. When effectively implemented, multicloud solutions can enhance architectural resilience, reduce dependence on a single vendor, and improve flexibility by leveraging services from different providers. However, multicloud strategies also present challenges, including increased operational complexity, security risks, higher costs, and integration difficulties. According to the 2024 State of the Cloud Report by Flexera, multi-cloud adoption has continued to rise in 2024. Enterprises increasingly silo applications into specific clouds and select best-fit services. Key use cases include data analysis in separate clouds and cross-cloud disaster recovery. == Advantages and challenges == There are several advantages to using a multicloud approach, including the ability to negotiate better pricing with cloud providers, the ability to quickly switch to another provider if needed, and the ability to avoid vendor lock-in. Multicloud can also be a good way to hedge against the risks of obsolescence, as it allows you to rely on multiple vendors and open standards, which can prolong the life of your systems. Additional benefits of the multicloud architecture include adherence to local policies that require certain data to be physically present within the area/country, geographical distribution of processing requests from physically closer cloud unit which in turn reduces latency and protect against disasters. Various issues and challenges also present themselves in a multicloud environment. Security and governance is more complicated, and more "moving parts" may create resiliency issues. == Difference between multicloud and hybrid cloud == Multicloud differs from hybrid cloud in that it refers to multiple cloud services from different vendors rather than multiple deployment modes (on-premises hardware, and public and private, cloud hosting). However, when considering a broad definition of multi-cloud, hybrid cloud can still be regarded as a special form of multi-cloud.
Image-based modeling and rendering
In computer graphics and computer vision, image-based modeling and rendering (IBMR) methods rely on a set of two-dimensional images of a scene to generate a three-dimensional model and then render some novel views of this scene. The traditional approach of computer graphics has been used to create a geometric model in 3D and try to reproject it onto a two-dimensional image. Computer vision, conversely, is mostly focused on detecting, grouping, and extracting features (edges, faces, etc.) present in a given picture and then trying to interpret them as three-dimensional clues. Image-based modeling and rendering allows the use of multiple two-dimensional images in order to generate directly novel two-dimensional images, skipping the manual modeling stage. == Light modeling == Instead of considering only the physical model of a solid, IBMR methods usually focus more on light modeling. The fundamental concept behind IBMR is the plenoptic illumination function which is a parametrisation of the light field. The plenoptic function describes the light rays contained in a given volume. It can be represented with seven dimensions: a ray is defined by its position ( x , y , z ) {\displaystyle (x,y,z)} , its orientation ( θ , ϕ ) {\displaystyle (\theta ,\phi )} , its wavelength ( λ ) {\displaystyle (\lambda )} and its time ( t ) {\displaystyle (t)} : P ( x , y , z , θ , ϕ , λ , t ) {\displaystyle P(x,y,z,\theta ,\phi ,\lambda ,t)} . IBMR methods try to approximate the plenoptic function to render a novel set of two-dimensional images from another. Given the high dimensionality of this function, practical methods place constraints on the parameters in order to reduce this number (typically to 2 to 4). == IBMR methods and algorithms == View morphing generates a transition between images Panoramic imaging renders panoramas using image mosaics of individual still images Lumigraph relies on a dense sampling of a scene Space carving generates a 3D model based on a photo-consistency check
Language Server Protocol
The Language Server Protocol (LSP) is an open, JSON-RPC-based protocol for use between source-code editors or integrated development environments (IDEs) and servers that provide "language intelligence tools": programming language-specific features like code completion, syntax highlighting and marking of warnings and errors, as well as refactoring routines. The goal of the protocol is to allow programming language support to be implemented and distributed independently of any given editor or IDE. In the early 2020s, LSP quickly became a "norm" for language intelligence tools providers. == History == LSP was originally developed for Microsoft Visual Studio Code and is now an open standard. On June 27, 2016, Microsoft announced a collaboration with Red Hat and Codenvy to standardize the protocol's specification. Its specification is hosted and developed on GitHub. == Background == Modern IDEs provide programmers with sophisticated features like code completion, refactoring, navigating to a symbol's definition, syntax highlighting, and error and warning markers. For example, in a text-based programming language, a programmer might want to rename a method read. The programmer could either manually edit the respective source code files and change the appropriate occurrences of the old method name into the new name, or instead use an IDE's refactoring capabilities to make all the necessary changes automatically. To be able to support this style of refactoring, an IDE needs a sophisticated understanding of the programming language that the program's source is written in. A programming tool without such an understanding—for example, one that performs a naive search-and-replace instead—could introduce errors. When renaming a read method, for example, the tool should not replace the partial match in a variable that might be called readyState, nor should it replace the portion of a code comment containing the word "already". Neither should renaming a local variable read, for example, end up altering identically-named variables in other scopes. Conventional compilers or interpreters for a specific programming language are typically unable to provide these language services, because they are written with the goal of either transforming the source code into object code or immediately executing the code. Additionally, language services must be able to handle source code that is not well-formed, e.g. because the programmer is in the middle of editing and has not yet finished typing a statement, procedure, or other construct. Additionally, small changes to a source code file which are done during typing usually change the semantics of the program. In order to provide instant feedback to the user, the editing tool must be able to very quickly evaluate the syntactical and semantical consequences of a specific modification. Compilers and interpreters therefore provide a poor candidate for producing the information needed for an editing tool to consume. Prior to the design and implementation of the Language Server Protocol for the development of Visual Studio Code, most language services were generally tied to a given IDE or other editor. In the absence of the Language Server Protocol, language services are typically implemented by using a tool-specific extension API. Providing the same language service to another editing tool requires effort to adapt the existing code so that the service may target the second editor's extension interfaces. The Language Server Protocol allows for decoupling language services from the editor so that the services may be contained within a general-purpose language server. Any editor can inherit sophisticated support for many different languages by making use of existing language servers. Similarly, a programmer involved with the development of a new programming language can make services for that language available to existing editing tools. Making use of language servers via the Language Server Protocol thus also reduces the burden on vendors of editing tools, because vendors do not need to develop language services of their own for the languages the vendor intends to support, as long as the language servers have already been implemented. The Language Server Protocol also enables the distribution and development of servers contributed by an interested third party, such as end users, without additional involvement by either the vendor of the compiler for the programming language in use or the vendor of the editor to which the language support is being added. LSP is not restricted to programming languages. It can be used for any kind of text-based language, like specifications or domain-specific languages (DSL). == Technical overview == When a user edits one or more source code files using a language server protocol-enabled tool, the tool acts as a client that consumes the language services provided by a language server. The tool may be a text editor or IDE and the language services could be refactoring, code completion, etc. The client informs the server about what the user is doing, e.g., opening a file or inserting a character at a specific text position. The client can also request the server to perform a language service, e.g. to format a specified range in the text document. The server answers a client's request with an appropriate response. For example, the formatting request is answered either by a response that transfers the formatted text to the client or by an error response containing details about the error. The Language Server Protocol defines the messages to be exchanged between client and language server. They are JSON-RPC preceded by headers similar to HTTP. Messages may originate from the server or client. The protocol does not make any provisions about how requests, responses and notifications are transferred between client and server. For example, client and server could be components within the same process exchanging JSON strings via method calls. They could also be different processes on the same or on different machines communicating via network sockets. == Registry == There are lists of LSP-compatible implementations, maintained by the community-driven Langserver.org or Microsoft.