NCSA Brown Dog is a research project to develop a method for easily accessing historic research data stored in order to maintain the long-term viability of large bodies of scientific research. It is supported by the National Center for Supercomputing Applications (NCSA) that is funded by the National Science Foundation (NSF). == History == Brown Dog is part of the DataNet partners program funded by NSF in 2008. DataNet was conceived to address the increasingly digital and data-intensive nature of science, engineering and education. Brown Dog is part of a follow-on effort called Data Infrastructure Building Blocks (DIBBs), focused on building software to support DataNet. The project was proposed by researchers at NCSA and the University of Illinois Urbana-Champaign as well as researchers from Boston University and the University of North Carolina at Chapel Hill. == Unstructured, uncurated, long tail data == Much scientific data is smaller, unstructured and uncurated and thus not easily shared. Such data is sometimes referred to as "long tail" data. This borrows a term from statistics and refers to the tail of the distribution of project sizes. The majority of smaller projects lack the resources to properly steward the data they produce. This so-called "long tail" data, both past and present, has the potential to inform future research in many study areas. Much of this data has become inaccessible due to obsolete software and file formats. The resulting impossibility of reviewing data from older research disrupts the overall scientific research project. == Approach == Brown Dog describes itself as the "super mutt" of software (thus the name "Brown Dog"), serving as a low-level data infrastructure to interface digital data content across the internet. Its approach is to use every possible source of automated help (i.e., software) in existence in a robust and provenance-preserving manner to create a service that can deal with as much of this data as possible. The project sees the broader impact of its work in its potential to serve the general public as a sort of "DNS for data", with the goal of making all data and all file formats as accessible as webpages are today. == Technology == Brown Dog seeks to address problems involving the use of uncurated and unstructured data collections through the development of two services: the Data Access Proxy (DAP) to aid in the conversion of file formats and the Data Tilling Services (DTS) for the automatic extraction of metadata from file contents. Once developed, researchers and general public users will be able to download browser plugins and other tools from the Brown Dog tool catalog. === Data Tilling Service === Data Tilling Service (DTS) will allow users to search data collections using an existing file to discover other similar files in a collection. A DTS search field will be appended to configured browsers where example files can be dropped. This tells DTS to search all the files under a given URL for files similar to the dropped file. For example, while browsing an online image collection, a user could drop an image of three people into the search field, and the DTS would return all images in the collection that also contain three people. If DTS encounters a foreign file format, it will utilize DAP to make the file accessible. DTS also indexes the data and extract and appends metadata to files and collections enabling users to gain some sense of the type of data they are encountering. This service runs on port 9443. === Data Access Proxy === Data Access Proxy (DAP) allows users to access data files that would otherwise be unreadable. Similar to an internet gateway or Domain Name Service, the DAP configuration would be entered into a user's machine and browser settings. Data requests over HTTP would first be examined by DAP to determine if the native file format is readable on the client device. If not, DAP converts the file into the best available format readable by the client machine. Alternatively, the user could specify the desired format themselves. This service runs on port 8184. == Use cases == Brown Dog targets three use cases proposed by groups within the EarthCube research communities. Developers and researchers from these communities will work together on use cases that span geoscience, engineering, biology and social science. === Long tail vegetation data in ecology and global change biology === This use case is led by Michael Dietze, Boston University Data on the abundance, species composition, and size structure of vegetation is critically important for a wide array of sub-disciplines in ecology, conservation, natural resource management, and global change biology. However, addressing many of the pressing questions in these disciplines will require that terrestrial biosphere and hydrologic models are able to assimilate the large amount of long-tail data that exists but is largely inaccessible. The Brown Dog team in cooperation with researches from Dietze's lab will facilitate the capture of a huge body of smaller research-oriented vegetation data sets collected over many decades and historical vegetation data embedded in Public Land Survey data dating back to 1785. This data will be used as initial conditions for models, to make sense of other large data sets and for model calibration and validation. === Designing green infrastructure considering storm water and human requirements === This use case is led by Barbara Minsker], University of Illinois at Urbana-Champaign]; William Sullivan, University of Illinois at Urbana-Champaign; Arthur Schmidt, University of Illinois at Urbana-Champaign. This case study involves developing novel green infrastructure design criteria and models that integrate requirements for storm water management and ecosystem and human health and well being. To address the scientific and social problems associated with the design of green spaces, data accessibility and availability is a major challenge. This study will focus on identified areas of the Green Healthy Neighborhood Planning region within the City of Chicago where existing local sewer performance is most deficient and where changes in impervious area through green infrastructure would be beneficial to under served neighborhoods. Brown Dog will be used to extract long-tail experimental data on human landscape preferences and health impacts. This data will be used to develop a human health impacts model that will then be linked together with a terrestrial biosphere model and a storm water model using Brown Dog technology. === Development and application for critical zone studies === This use case is led by Praveen Kumar, University of Illinois at Urbana-Champaign Critical Zone (CZ) is the "skin" of the earth that extends from the treetops to the bedrock that is created by life processes working at scales from microbes to biomes. The Critical Zone supports all terrestrial living systems. Its upper part is the bio-mantle. This is where terrestrial biota live, reproduce, use and expend energy, and where their wastes and remains accumulate and decompose. It encompasses the soil, which acts as a geomembrane through which water and solutes, energy, gases, solids, and organisms interact with the atmosphere, biosphere, hydrosphere, and lithosphere. A variety of drivers affect this bio-dynamic zone, ranging from climate and deforestation to agriculture, grazing and human development. Understanding and predicting these effects is central to managing and sustaining vital ecosystem services such as soil fertility, water purification, and production of food resources, and, at larger scales, global carbon cycling and carbon sequestration. The CZ provides a unifying framework for integrating terrestrial surface and near-surface environments, and reflects an intricate web of biological and chemical processes and human impacts occurring at vastly different temporal and spatial scales. The nature of these data create significant challenges for inter-disciplinary studies of the CZ because integration of the variety and number of data products and models has been a barrier. On the other hand, CZ data provides an excellent opportunity for defining, testing and implementing Brown Dog technologies. In this context "unstructured" data is viewed broadly as consisting of a collection of heterogeneous data with formats that reflect temporal and disciplinary legacies, data from emerging low cost open hardware based sensors and embedded sensor networks that lack well defined metadata and sensor characteristics, as well as data that are available as maps, images and text. == NSF Award == CIF21 DIBBs: Brown Dog was awarded in the winter of 2013 with a start date of October 1, 2013. Estimated expiration date is September 30, 2018. The award amount was $10,519,716.00, the largest DIBB award. The principal investigator is Kenton McHenry of NCSA at the University of Illinois at Urbana-Champaign. Coleaders are Jong Lee NCSA/UIU
RockMyRun
Rock My Run (stylized as RockMyRun; trademarked slogan: "The Best Running Music in the World™") is a mobile running/fitness app founded in 2011 that provides running and workout music in the form of DJ mixes. It is owned by Rock My World, Inc., a health and fitness technology company based in San Diego, California. The app allows users to listen to these professional DJ mixes on their smartphone while running or working out to enhance and motivate their performance. Rock My World, Inc. also developed the app Jolt.ai for the software Slack. == History == During the early stages of the company, Rock My World, Inc. raised more than $2 million in funding generated by the Irvine Company's The Vine SD and from institutional investors including Skullcandy, ZTE and Lighter Capital and were admitted to the Plug and Play Tech Center in Sunnyvale and to the tech incubator EvoNexus in San Diego. In an interview with co-founder and ex-Qualcomm staff Adam Riggs-Zeigen, he said that "from the beginning [their] big goal is to help people live healthier lives." == Features == The RockMyRun app contains thousands of mixes or "stations" produced by its professional DJs intended to increase enjoyment and performance during exercise. DJs who have provided mixes for the app include David Guetta, Zedd, Steve Aoki, Major Lazer and Afrojack. All of the music can be personalized based on the user's steps per minute, heart rate or ideal cadence allowing the user to "always hear the right music at the right time at the right tempo". All RockMyRun mixes are organized into stations to help users discover music that suits their needs. RockMyRun contains mixes of all genres and each station is categorized into their respective genres and displays tags to let users know the type of music contained in the mix. RockMyRun has two membership types; it is free as a standard member, but for uninterrupted listening and additional features, users can upgrade to a paid "Rockstar" membership. Since March 2023, couples can now be on the same RockMyRun playlists and "share" earbuds. This allows people to train together, easier. A group of DJs curate playlists for specific training needs and different energy levels. == Reception == RockMyRun has been featured on television programs such as The Today Show on two occasions and on The Rachael Ray Show, and in positive reviews by many publications and websites including The New York Times on four separate occasions, TIME, The Huffington Post, The Denver Post, Men's Fitness, Real Simple, The Vulcan Post, The L.A. Times, Glamour, Paste magazine, PCMag, Dubai Week, BetaNews, CNET, CNBC, Reuters, Insider, Tom's Guide and Yahoo! Tech. RockMyRun has also been mentioned/recommended in books/publications such as A Practical Guide to Teacher Wellbeing by Elizabeth Holmes and Applying Music in Exercise and Sport by Dr. Costas Karageorghis. Ultimate Ears placed RockMyRun at the top of their list at No. 1 on their "5 Favorite Workout Music Apps". In a positive review by David Strausser for AndroidGuys in 2015, he praised the app in a detailed review, saying "The mixes are incredible and the rates are reasonable. The app is quick, beautiful." In 2015, Jill Duffy of PC Magazine gave a review of the app, pointing out its key features, and stating that the app is great if you enjoy listening to different, or new music, that can match your tempo while running. Also in 2015, Digital Trends listed RockMyRun, as one of the best exercise music apps in the article "No need to make exercise playlists with these music apps". In 2018, Redbull.com recommended RockMyRun in preparation for the Wings for Life World Run in their article "10 essential hacks for running to work to get you in World Run shape". In 2019, The Fashion Spot included RockMyRun in their list of "The Best Workout Apps for People Who Hate to Work Out", saying: "RockMyRun matches music to the tempo of your running pace – the music literally follows your steps/heart rate. The app has thousands of mixes/music options along with tracking capabilities." Also in 2019, MakeUseOf.com included RockMyRun in their list of "The 7 Best Running and Workout Music Apps". In September 2022, VeryWellFit listed RockMyRun as the first of three "Other Playlist Options" in the article "How to Create a Running Playlist, According to Running Coaches". Tech Grapple recommended the app in "The best workout free music apps for iPhone and Android" saying that "RockMyRun is the best application that you can use during workout. It comes with amazing DJs to craft mixes that will keep you moving." == Partners == RockMyRun is partnered with the following brands/companies: C25K Del Taco JLab Audio iFit Active Network, LLC Night Nation Run (the world's first running music festival) Lady Foot Locker Mayweather Boxing + Fitness Mio Global Orangetheory Fitness Red Rock Apps Tapout Fitness
Scalable Coherent Interface
The Scalable Coherent Interface or Scalable Coherent Interconnect (SCI), is a high-speed interconnect standard for shared memory multiprocessing and message passing. The goal was to scale well, provide system-wide memory coherence and a simple interface; i.e. a standard to replace existing buses in multiprocessor systems with one with no inherent scalability and performance limitations. The IEEE Std 1596-1992, IEEE Standard for Scalable Coherent Interface (SCI) was approved by the IEEE standards board on March 19, 1992. It saw some use during the 1990s, but never became widely used and has been replaced by other systems from the early 2000s. == History == Soon after the Fastbus (IEEE 960) follow-on Futurebus (IEEE 896) project in 1987, some engineers predicted it would already be too slow for the high performance computing marketplace by the time it would be released in the early 1990s. In response, a "Superbus" study group was formed in November 1987. Another working group of the standards association of the Institute of Electrical and Electronics Engineers (IEEE) spun off to form a standard targeted at this market in July 1988. It was essentially a subset of Futurebus features that could be easily implemented at high speed, along with minor additions to make it easier to connect to other systems, such as VMEbus. Most of the developers had their background from high-speed computer buses. Representatives from companies in the computer industry and research community included Amdahl, Apple Computer, BB&N, Hewlett-Packard, CERN, Dolphin Server Technology, Cray Research, Sequent, AT&T, Digital Equipment Corporation, McDonnell Douglas, National Semiconductor, Stanford Linear Accelerator Center, Tektronix, Texas Instruments, Unisys, University of Oslo, University of Wisconsin. The original intent was a single standard for all buses in the computer. The working group soon came up with the idea of using point-to-point communication in the form of insertion rings. This avoided the lumped capacitance, limited physical length/speed of light problems and stub reflections in addition to allowing parallel transactions. The use of insertion rings is credited to Manolis Katevenis who suggested it at one of the early meetings of the working group. The working group for developing the standard was led by David B. Gustavson (chair) and David V. James (Vice Chair). David V. James was a major contributor for writing the specifications including the executable C-code. Stein Gjessing’s group at the University of Oslo used formal methods to verify the coherence protocol and Dolphin Server Technology implemented a node controller chip including the cache coherence logic. Different versions and derivatives of SCI were implemented by companies like Dolphin Interconnect Solutions, Convex, Data General AViiON (using cache controller and link controller chips from Dolphin), Sequent and Cray Research. Dolphin Interconnect Solutions implemented a PCI and PCI-Express connected derivative of SCI that provides non-coherent shared memory access. This implementation was used by Sun Microsystems for its high-end clusters, Thales Group and several others including volume applications for message passing within HPC clustering and medical imaging. SCI was often used to implement non-uniform memory access architectures. It was also used by Sequent Computer Systems as the processor memory bus in their NUMA-Q systems. Numascale developed a derivative to connect with coherent HyperTransport. == The standard == The standard defined two interface levels: The physical level that deals with electrical signals, connectors, mechanical and thermal conditions The logical level that describes the address space, data transfer protocols, cache coherence mechanisms, synchronization primitives, control and status registers, and initialization and error recovery facilities. This structure allowed new developments in physical interface technology to be easily adapted without any redesign on the logical level. Scalability for large systems is achieved through a distributed directory-based cache coherence model. (The other popular models for cache coherency are based on system-wide eavesdropping (snooping) of memory transactions – a scheme which is not very scalable.) In SCI each node contains a directory with a pointer to the next node in a linked list that shares a particular cache line. SCI defines a 64-bit flat address space (16 exabytes) where 16 bits are used for identifying a node (65,536 nodes) and 48 bits for address within the node (256 terabytes). A node can contain many processors and/or memory. The SCI standard defines a packet switched network. === Topologies === SCI can be used to build systems with different types of switching topologies from centralized to fully distributed switching: With a central switch, each node is connected to the switch with a ringlet (in this case a two-node ring). In distributed switching systems, each node can be connected to a ring of arbitrary length and either all or some of the nodes can be connected to two or more rings. The most common way to describe these multi-dimensional topologies is k-ary n-cubes (or tori). The SCI standard specification mentions several such topologies as examples. The 2-D torus is a combination of rings in two dimensions. Switching between the two dimensions requires a small switching capability in the node. This can be expanded to three or more dimensions. The concept of folding rings can also be applied to the Torus topologies to avoid any long connection segments. === Transactions === SCI sends information in packets. Each packet consists of an unbroken sequence of 16-bit symbols. The symbol is accompanied by a flag bit. A transition of the flag bit from 0 to 1 indicates the start of a packet. A transition from 1 to 0 occurs 1 (for echoes) or 4 symbols before the packet end. A packet contains a header with address command and status information, payload (from 0 through optional lengths of data) and a CRC check symbol. The first symbol in the packet header contains the destination node address. If the address is not within the domain handled by the receiving node, the packet is passed to the output through the bypass FIFO. In the other case, the packet is fed to a receive queue and may be transferred to a ring in another dimension. All packets are marked when they pass the scrubber (a node is established as scrubber when the ring is initialized). Packets without a valid destination address will be removed when passing the scrubber for the second time to avoid filling the ring with packets that would otherwise circulate indefinitely. === Cache coherence === Cache coherence ensures data consistency in multiprocessor systems. The simplest form applied in earlier systems was based on clearing the cache contents between context switches and disabling the cache for data that were shared between two or more processors. These methods were feasible when the performance difference between the cache and memory were less than one order of magnitude. Modern processors with caches that are more than two orders of magnitude faster than main memory would not perform anywhere near optimal without more sophisticated methods for data consistency. Bus based systems use eavesdropping (snooping) methods since buses are inherently broadcast. Modern systems with point-to point links use broadcast methods with snoop filter options to improve performance. Since broadcast and eavesdropping are inherently non-scalable, these are not used in SCI. Instead, SCI uses a distributed directory-based cache coherence protocol with a linked list of nodes containing processors that share a particular cache line. Each node holds a directory for the main memory of the node with a tag for each line of memory (same line length as the cache line). The memory tag holds a pointer to the head of the linked list and a state code for the line (three states – home, fresh, gone). Associated with each node is also a cache for holding remote data with a directory containing forward and backward pointers to nodes in the linked list sharing the cache line. The tag for the cache has seven states (invalid, only fresh, head fresh, only dirty, head dirty, mid valid, tail valid). The distributed directory is scalable. The overhead for the directory based cache coherence is a constant percentage of the node’s memory and cache. This percentage is in the order of 4% for the memory and 7% for the cache. == Legacy == SCI is a standard for connecting the different resources within a multiprocessor computer system, and it is not as widely known to the public as for example the Ethernet family for connecting different systems. Different system vendors implemented different variants of SCI for their internal system infrastructure. These different implementations interface to very intricate mechanisms in processors and memory systems and each vendor has to preserve some degrees of
Information security
Information security is the practice of protecting information by mitigating information risks. It is part of information risk management. It typically involves preventing or reducing the probability of unauthorized or inappropriate access to data or the unlawful use, disclosure, disruption, deletion, corruption, modification, inspection, recording, or devaluation of information. It also involves actions intended to reduce the adverse impacts of such incidents. Protected information may take any form, e.g., electronic or physical, tangible (e.g., paperwork), or intangible (e.g., knowledge). Information security's primary focus is the balanced protection of data confidentiality, integrity, and availability (known as the CIA triad, unrelated to the US government organization) while maintaining a focus on efficient policy implementation, all without hampering organization productivity. This is largely achieved through a structured risk management process. To standardize this discipline, academics and professionals collaborate to offer guidance, policies, and industry standards on passwords, antivirus software, firewalls, encryption software, legal liability, security awareness and training, and so forth. This standardization may be further driven by a wide variety of laws and regulations that affect how data is accessed, processed, stored, transferred, and destroyed. While paper-based business operations are still prevalent, requiring their own set of information security practices, enterprise digital initiatives are increasingly being emphasized, with information assurance now typically being dealt with by information technology (IT) security specialists. These specialists apply information security to technology (most often some form of computer system). IT security specialists are almost always found in any major enterprise/establishment due to the nature and value of the data within larger businesses. They are responsible for keeping all of the technology within the company secure from malicious attacks that often attempt to acquire critical private information or gain control of the internal systems. There are many specialist roles in Information Security including securing networks and allied infrastructure, securing applications and databases, security testing, information systems auditing, business continuity planning, electronic record discovery, and digital forensics. == Standards == Information security standards are guidelines generally outlined in published materials that aim to protect a user's or an organization's cyber environment from threats. This environment includes the users themselves, hardware such as devices and networks, software such as applications or services, and any information in storage or transit. These standards comprise security concepts, technologies, and guidelines to deal with an adverse event. They may also include assessment criteria and certification for organizations implementing a minimum level of security. These standards are developed by various international and national bodies to prevent or mitigate cyber-attacks, ensure consistency among developers, and establish a minimum standard in industries susceptible to an attack. The ISO/IEC 27000 family, published by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), provides information about the guidelines and requirements for an Information Security Management System (ISMS). The Common Criteria (ISO/IEC 15408) provides guidelines on evaluating and certifying the security of a system. The IEC 62443 establishes security standards for automation and control systems. Similarly, the ISO/SAE 21434, ETSI EN 303 645, and EN 18031 provide standards for road vehicles, the Internet of Things, and radio-based systems respectively. The NIST Cybersecurity Framework (NIST CSF) is a set of guidelines developed by the U.S. National Institute of Standards and Technology to help organizations with risk management. NIST also publishes various Federal Information Processing Standards (FIPS) and Special Publications. The United Kingdom has introduced Cyber Essentials, which is a certification scheme to protect organizations against common security threats. The Australian Cyber Security Centre publishes the Essential Eight mitigation strategies. The Payment Card Industry Data Security Standard (PCI DSS) regulates handling of cardholder data in order to reduce credit card fraud. UL has published standards related to specific industries such as UL 2900-2-3 for security and life safety signaling systems and UL-2900-2-1 for healthcare and wellness systems. == Threats == Information security threats come in many different forms. Some of the most common threats today are software attacks, theft of intellectual property, theft of identity, theft of equipment or information, sabotage, and information extortion. Viruses, worms, phishing attacks, and Trojan horses are a few common examples of software attacks. The theft of intellectual property has also been an extensive issue for many businesses. Identity theft is the attempt to act as someone else usually to obtain that person's personal information or to take advantage of their access to vital information through social engineering. Sabotage usually consists of the destruction of an organization's website in an attempt to cause loss of confidence on the part of its customers. Information extortion consists of theft of a company's property or information as an attempt to receive a payment in exchange for returning the information or property back to its owner, as with ransomware. One of the most functional precautions against these attacks is to conduct periodical user awareness. Governments, military, corporations, financial institutions, hospitals, non-profit organizations, and private businesses amass a great deal of confidential information about their employees, customers, products, research, and financial status. Should confidential information about a business's customers or finances or new product line fall into the hands of a competitor or hacker, a business and its customers could suffer widespread, irreparable financial loss, as well as damage to the company's reputation. From a business perspective, information security must be balanced against cost; the Gordon-Loeb Model provides a mathematical economic approach for addressing this concern. For the individual, information security has a significant effect on privacy, which is viewed very differently in various cultures. == History == Since the early days of communication, diplomats and military commanders understood that it was necessary to provide some mechanism to protect the confidentiality of correspondence and to have some means of detecting tampering. Julius Caesar is credited with the invention of the Caesar cipher c. 50 B.C., which was created in order to prevent his secret messages from being read should a message fall into the wrong hands. However, for the most part protection was achieved through the application of procedural handling controls. Sensitive information was marked up to indicate that it should be protected and transported by trusted persons, guarded and stored in a secure environment or strong box. As postal services expanded, governments created official organizations to intercept, decipher, read, and reseal letters (e.g., the U.K.'s Secret Office, founded in 1653). In the mid-nineteenth century more complex classification systems were developed to allow governments to manage their information according to the degree of sensitivity. For example, the British Government codified this, to some extent, with the publication of the Official Secrets Act in 1889. Section 1 of the law concerned espionage and unlawful disclosures of information, while Section 2 dealt with breaches of official trust. A public interest defense was soon added to defend disclosures in the interest of the state. A similar law was passed in India in 1889, The Indian Official Secrets Act, which was associated with the British colonial era and used to crack down on newspapers that opposed the Raj's policies. A newer version was passed in 1923 that extended to all matters of confidential or secret information for governance. By the time of the First World War, multi-tier classification systems were used to communicate information to and from various fronts, which encouraged greater use of code making and breaking sections in diplomatic and military headquarters. Encoding became more sophisticated between the wars as machines were employed to scramble and unscramble information. The establishment of computer security inaugurated the history of information security. The need for such appeared during World War II. The volume of information shared by the Allied countries during the Second World War necessitated formal alignment of classification systems and procedural controls. An arcane range of markings evol
Eduroam
eduroam (a portmanteau of education and roaming) is an international Wi-Fi internet access roaming service for users in research, higher education and further education. It provides researchers, teachers, and students network access when visiting an institution other than their own. Users are authenticated with credentials from their home institution, regardless of the location of the eduroam access point. Authorization to access the Internet and other resources are handled by the visited institution. Users do not have to pay to use eduroam. In some countries, Internet access via eduroam is also available at other locations than the participating institutions, e.g. in libraries, public buildings, railway stations, city centres and airports. It is also available at many primary and secondary education institutions in Brazil and the US. == History == The eduroam initiative started in 2002 when during the preparations for the creation of TERENA's task force TF-Mobility, Klaas Wierenga of SURFnet shared the idea of combining a RADIUS-based infrastructure with IEEE 802.1X technology to provide roaming network access across research and education networks. Initially, the service was joined by institutions in the Netherlands, Germany, Finland, Portugal, Croatia and the United Kingdom. Later, other NRENs in Europe embraced the idea and started joining the infrastructure, which was then called eduroam. Since 2004, the European Union co-funded further research and development work related to the eduroam service through the GN2 and GN3 projects. From September 2007, the European Union also funded through these projects the continued operation and maintenance of the eduroam service at the European level. The first non-European country to join eduroam was Australia, in December 2004. In Canada, eduroam started as an initiative of the University of British Columbia, which was later taken over by CANARIE as a service of its Canadian Access Federation. In the United States, eduroam was initially a pilot project between the National Science Foundation and the University of Tennessee (UTK). In 2012, Internet2 announced the addition of eduroam to its NET+ service offerings. AnyRoam LLC, a private company, was formed by former UTK staff to serve as an Internet2 active corporate member administering the US top-level servers. In 2021, Internet2 assumed direct management of the eduroam service for US-based organizations. == Technology == The eduroam service uses IEEE 802.1X as the authentication method and a hierarchical system of RADIUS servers. The hierarchy typically consists of RADIUS servers at the participating institutions, national RADIUS servers run by the National Roaming Operators, and regional top-level RADIUS servers for individual world regions. In some cases, institutions contact each other directly via DNS lookups () When a user visits a remote institution, the user's device presents their credentials to the local RADIUS server. That RADIUS server discovers that it is not responsible for the realm of the user's home institution and proxies the access request to another RADIUS server, typically the national RADIUS server. If the visited institution is in a different country than the home institution, the request is in turn proxied to the regional top-level RADIUS server, and then to the national RADIUS server of the user's home country. That national server forwards the credentials to the home institution, where they are verified. The RADIUS response travels back over the proxy-hierarchy to the visited institution and the user is granted access. In eduroam, the user credentials are always presented in the form of an EAP method (). The EAP method is responsible for ensuring that the users credentials are secure, and private. The users credentials can then travel via a number of intermediate servers, not under the control of the home institution of the user. This requirement limits the types of EAP methods that can be used. EAP methods which do not provide for security or privacy of user credentials cannot be used in eduroam. The most commonly used EAP methods in eduroam are EAP-TLS, PEAP, and EAP-TTLS. The methods used generally fall into two broad categories: those that use credentials in the form of some public-key mechanism with certificates and those that use so-called tunnelled authentication with "inner" passwords or other credentials. Most institutions use a tunnelled authentication method that requires a server certificate. These server certificates are used to set up a secure tunnel between the mobile device and the authentication server, through which the user credentials (e.g. name and password) are securely transported. A complication arises if the user's home institution does not use a two-letter country-code top-level domain as part of its realm, but a generic top-level domain such as .edu or .org. By inspection of such realms, it is not possible to determine which national RADIUS server the request should be routed to. Such domains will thus, by default, fail to work in international roaming. The workaround for this problem involves the creation of exceptions in the international RADIUS request routing tables; however, this workaround does not scale as the number of exception entries grows. Several solutions have been proposed to eliminate this workaround in the future, the most promising of which is RADIUS over TLS with Dynamic Discovery, which does not rely on static routing tables inside a RADIUS server configuration to route requests to their proper destination. Instead, the participating institution adds one NAPTR DNS resource record to its own domain's DNS zone, which states by which server eduroam authentication for the domain is handled. == Governance == GÉANT has established a lightweight global governance structure. Recognising the large variety in the organisation and funding of research and education (networking) in different countries and regions, rules imposed on the operations of eduroam are limited to technical and administrative requirements that are necessary to ensure the smooth and secure operations of eduroam worldwide. Moreover, the eduroam operators have the leading role in creating and maintaining the rules of the global eduroam governance. The Global eduroam Governance Committee (GeGC) has the central role in the global eduroam governance structure. While its structure has evolved over time, it presently has three representatives from each of five regions — mirroring those used by the Regional Internet registries — serving a two-year term. In addition, GÉANT may appoint one or more experts as non-voting members of the GeGC. == Geographical deployment == eduroam is available at selected locations in countries with a National Roaming Operator that has signed the eduroam Compliance Statement. Those sixty-seven countries are listed below. In addition, there may be pilot deployments in countries that are in the process of joining eduroam. === Middle East === eduroam is deployed in: === Europe === The NRENs that are members of the consortium of the GN3 project have joined the European eduroam confederation by signing the confederation's policy that requires its members to comply with a set of technical and organisational requirements, which are more specific than those in the global eduroam Compliance Statement. As a consequence, eduroam is deployed in the following countries: In addition, three NRENs that are associate members of the consortium of the GN3 project without voting rights joined the European eduroam confederation; they represent Belarus (UIIP), Moldova (RENAM) and Russia (Joint Supercomputer Center of the Russian Academy of Sciences). Finally, five NRENs not involved in the GN3 project joined the European eduroam confederation on a voluntary basis, enabling the deployment of the service in: The European top-level RADIUS servers are operated by SURFnet and Forskningsnettet. === Asia-Pacific === eduroam is deployed in the following countries and economies: The Asia-Pacific top-level RADIUS servers are operated by AARNet and by the University of Hong Kong. === North America === eduroam is deployed in: === Latin America === eduroam is deployed in: === Africa === eduroam is deployed in: The inter-African RADIUS servers are operated by West-African research and education network WACREN, the UbuntuNet Alliance and TENET.
Device-independent pixel
A device-independent pixel (also: density-independent pixel, dip, dp) is a unit of length. A typical use is to allow mobile device software to scale the display of information and user interaction to different screen sizes. The abstraction allows an application to work in pixels as a measurement, while the underlying graphics system converts the abstract pixel measurements of the application into real pixel measurements appropriate to the particular device. For example, on the Android operating system a device-independent pixel is equivalent to one physical pixel on a 160 dpi screen, while the Windows Presentation Foundation specifies one device-independent pixel as equivalent to 1/96th of an inch. As dp is a physical unit it has an absolute value which can be measured in traditional units, e.g. for Android devices 1 dp equals 1/160 of inch or 0.15875 mm. While traditional pixels only refer to the display of information, device-independent pixels may also be used to measure user input such as input on a touch screen device.
Social employee
A social employee is a worker operating within a social business model. Following an organization's social computing guidelines, social employees use social media tools both for internal workflow and collaboration purposes and for external engagement with customers, prospects and stakeholders through a combination of social media marketing, content marketing, social marketing, and social selling. Social employee programs are considered to be as much about culture and engagement as they are about business processes and best practices. In addition to increased leads and sales, social employee best practices are said to improve business outcomes important to social media marketing, such as increased connections and web traffic, improved brand identification and "chatter", and better customer advocacy. == Overview == The term "social employee" was first introduced to describe those exhibiting the emerging characteristics of workers operating under a social business model. The term is often used interchangeably with similar designations like "employee advocate" or "social employee advocate". Crucial to the perceived value of the social employee is the concept of the digital footprint. While organizations are able to generate large bases of followers through social media, research shows that brand marketing and engagement efforts through these networks are not as effective as those of individual employees. In fact, some research indicates that employee experts are more trusted than any other member of an organization. Because of this, social employee programs are designed to train, empower, and support employee engagement efforts in the hopes of authentically engaging larger communities, increasing the frequency of shares, reviews, and other forms of "earned media" and expanding the brand's presence on the web. == The personal or employee brand == A foundational concept of the social employee is the idea of the personal or employee brand. This concept first gained popular attention in a 1997 FastCompany article by business leader Tom Peters titled "The Brand Called You". In the article, Peters argued that the premium placed on branding impacted workers' lives to such an extent that creating and cultivating a distinct personal brand had become a professional necessity. According to Peters, doing so built trust, loyalty, visibility, influence, and employability. With increased adoption of social media tools by both businesses and consumers in the early 21st century, many business leaders became increasingly concerned with social engagement, both internally among employees and externally with customers and other stakeholders. While many in the business community acknowledged the potential social tools had for improved collaboration, productivity, and brand messaging, the concern that employees would misrepresent their brand, disclose proprietary information, or otherwise damage their company's reputation or ability to conduct business persisted. As a result, many began to advocate for employee branding as a solution to this problem. This helped give new meaning to the concept of brand ambassadorship, positioning everyday employees in public, and potentially high-profile, engagement roles. == Characteristics == === Engaged === Because social employee advocacy is dependent on the perceived authenticity of the employee, engagement is highly valued in social organizations. Further, data show the measurable impact of employee engagement on organizational productivity and profitability: Happy employees were found to be 12 percent more productive. In one study, engaged employees were found to be 38 percent more likely to produce at above-average rates. In another, organizations with engaged employees had a 19 percent higher than average shareholder return, while organizations with disengaged employees experienced shareholder return that was 44 percent below average. Engaged companies were found to outperform disengaged companies by up to 202 percent. Companies with strong focus on culture were found to have an average 13.9 percent turnover rate, while those with a low focus experience were found to have a 48.4 percent turnover rate. === Flexible job environment and work–life balance === The number of professionals working mobile or remote has risen considerably since 2010. While estimates vary, one study found that number of organizations with mobile or remote employees is expected to rise from 24 percent in 2012 to 89 percent by 2020. Other research has estimated that by 2020, 105.4 million professionals will work remotely in America, about 72.3 percent of the total workforce. This change has been linked to a rise in social technologies, including biometrics, wearables, near-field communications, and augmented reality. Social employees have also put a greater emphasis on work–life balance, with many believing that advances in technology can directly support efforts in this area. Purported benefits of this shift include a more flexible workforce, reduced business costs, and greater organizational leverage in attracting and retaining top talent. === Buys into the brand's story === In 2009, thought leader Simon Sinek presented a speech called "How Great Leaders Inspire Action" at a TEDxPugetSound event. Sinek's central argument in this speech was, "People don't buy what you do. They buy why you do it." This concept—that the story behind a business or product offering is a more compelling sales tool than the product itself—is frequently cited in social media marketing as a way to build authentic connections with stakeholders. However, others have argued that for employees to share a brand's story authentically, they must be engaged in that story themselves, and as a result, many companies have made storytelling part of their culture programs. === Collaborative === An implicit tenet in social business is that social technologies aren't a barrier to productivity, but rather a path to increased connectivity. The shift in enterprise software systems like IBM Connections to incorporate social communication models, such as mentions, wikis, and newsfeeds, reflects the changing communication dynamics within business. With an increase in diversity and sophistication in collaborative software platforms, social organizations have sought to find new creative ways to utilize these tools and secure employee buy-in around them. Crowdsourcing has also become popular in social businesses. Examples include AT&T's program The Innovation Pipeline (TIP), begun in 2009, which has generated over 28,000 ideas that have led to over 75 projects with funding exceeding $44 million. IBM has also put considerable resources into such processes, producing its social computing guidelines through employee crowdsourcing, as well as its Connections platform through the Technology Adoption Program (TAP), a more formalized crowdsourcing initiative. Another popular form of internal collaboration is the hack day, or hackathon. Organizations such as Netflix, Facebook, and IBM use hack days to pull employees out of their day-to-day work environments and encourage them to collaborate in nontraditional ways in an attempt to drive disruptive innovation. Social employees are often encouraged to seek external collaboration opportunities with customers and prospects. For example, Procter & Gamble introduced the Live Well Collaborative to connect with external stakeholders and develop products and services for the 50+ demographic. === Social listener === A social listener is someone who engages in social listening, or social media monitoring, for professional means. Social employees can use social media monitoring for a variety of reasons, including professional development, industry news and trends, and gauging market sentiment. Some have argued that social listening is one of the most important components of social business, as it enables organizations to collect rich market data, make more informed strategic decisions, and respond to customer needs more authentically. === Customer-centric === Advocates of customer-centricity in social business argue that social media has changed the dynamic from one-way brand messaging to shared interactions between brand and customer. Brand and customer engagement is seen as a means of creating more lasting connections with customers and prospects and empowering them to become brand promoters. Customer-centric interactions are seen to have distinct value to brands, as research shows that prospects are far more likely to trust brand-related messaging from a friend or family member than they are from a brand. As a means of building social employees, some social advocates have also called for a broader definition of customer to include the employees themselves. In the book The Pursuit of Social Business Excellence, authors Vala Afshar and Brad Martin made the following argument: A social business operates with the guiding principle that each employee's responsi