We organized the 73 strategic technologies into seven families for the purpose of administering our 2018 survey: analytics, infrastructure and operations, mobile, research and scholarship, security and privacy, social/personal/communication, and teaching and learning. This appendix defines the strategic technologies that we asked about and shows how technologies were grouped into each family. While a technology belonged to only one family for the purpose of administering our survey, a single technology may be listed in a number of different IT domains as presented in this report.

Flexible interactive platforms for descriptive and predictive analytics of institutional data: Flexible interactive analytics platforms allow a wide range of users to perform interactive analysis of institutional data, reflecting a shift away from IT-centric analytics solutions to ones that do not require advanced technical or data-science skills.

Massively scalable database architectures and software: Massively scalable database architectures allow for the distributed processing of very large data sets by dividing the work across computer clusters. This technology allows for high performance and highly scalable data management that can handle massive data.

Mobile apps for institutional BI/analytics: These mobile apps allow users to access institutional BI and analytics resources and technologies via handheld devices.

Predictive analytics for institutional performance: Predictive analytics for institutional performance is the application of analytics for improving institutional services and business practices. It uses modeling to determine what will happen based on historical and transactional data.

Predictive analytics for student success (institutional level): Predictive analytics for student success is the statistical analysis of massive amounts of data to create models that establish risk factors relating to student persistence, retention, and completion. These models enable proactive institutional support of student success.

Predictive learning analytics (course level): Predictive learning analytics is the practice of gathering and analyzing a variety of learner data that results in predictions about the likelihood of future student outcomes in the course. These predictions can be used by students and instructors.

Talent/workforce analytics: Talent or workforce analytics uses data from HR or other employee information sources to optimize workforce efforts and promote staff engagement. A mature workforce analytics practice links planning and decisions about staffing to institutional goals.

Text/content analytics: Text/content analytics is a set of techniques and processes that analyze unstructured, text-based information to discern themes and patterns that can be used as data for analysis and decision making.

Uses of the Internet of Things for campus management: The Internet of Things (IoT) refers to the networking of small, often everyday objects equipped with both computing and sensing capabilities, as well as the capacity to send and receive data via the Internet. For campus management, the IoT is being used in areas such as facilities management, where remote monitoring of conditions can allow more efficiency in HVAC and lighting. In addition, smart devices can alert staff to equipment that needs servicing before a problem arises, and parking monitoring systems can alert students to vacant campus parking spaces.

Application performance monitoring: Application performance monitoring tools track the performance of applications in relation to end users' experiences and to internal metrics (for example, for load and capacity) that may be leading indicators of future performance issues. The goal of these tools is to automate tracking and improve the reliability of application performance.

Blended data center (on premises and cloud based): As institutions move services to the cloud, they usually move into a blended environment where they continue to maintain an on-premises data center while also managing a set of services that may run the gamut from software as a service to infrastructure as a service. While cloud-based solutions offer advantages related to agility, performance, and scalability, the blended environment requires a shift in strategy to one that encompasses both environments.

Cloud monitoring platform to track distributed infrastructure apps, tools, and services (e.g., Datadog): The proliferation of cloud applications and services is challenging to support because it can result in a mix of distributed and centralized systems and tools, some under IT's control and some not. Cloud monitoring platforms allow institutions to track the expanding set of cloud resources.

Data center capacity planning and management tools: Data center capacity planning allows IT to meet the institution's evolving needs for data center resources such as storage, power load, and cooling capacity. Some vendors provide tools for capacity planning. IT service management frameworks such as ITIL describe subprocesses for capacity management that include business capacity management, service capacity management, and component capacity management.

Ethernet fabrics: Ethernet fabrics are a data center network protocol that enables connections between multiple physical and virtual devices as part of an integrated network system. The goal is to increase flexibility and bandwidth and provide a scalable, low-latency networking approach.

Institutional support for public-cloud storage (e.g., Box): Public-cloud storage options provide easy access, sharing, and backup of files and data. Institutions are moving to such options to provide cloud storage and collaboration services that work with the university's identity management system, integrate with other services, and provide contractual assurances of privacy, security, and uptime.

Integration platform as a service: The typical institution's enterprise environment is made up of a complex mix of applications and architectures, some in the cloud and some on-premises, that need to communicate with each other and share data appropriately. Instead of handling data integration in-house, some institutions are turning to integration platform as a service (iPaaS), which is a suite of generally cloud-based services that support and enable integration among disparate systems.

IPv6: Internet protocol version 6 (IPv6) is designed to address several problems of IPv4, the most pressing of which is the exhaustion of IPv4 addresses. In addition to simply providing more addresses, IPv6 allows for greater efficiency of IT systems, streamlined systems administration, and security improvements.

IT accessibility assessment tools: IT accessibility assessment tools allow institutions to test the designs of their web pages and other online materials to ensure they are usable by individuals with disabilities.

IT asset management tools (e.g., CMDB): IT asset management tools provide an account of the significant components of the IT environment, including dependencies and life cycles. As IT assets expand beyond central IT, both on campus and in the cloud, asset management becomes more complex. IT asset management tools can help institutions better understand, plan for, and make decisions about the resulting technology mix.

Life-cycle contract management: Life-cycle contract management refers to a formal process or system for managing contracts from the time of negotiation through compliance to renewal. Life-cycle contract management systems have the potential to create efficiencies and lead to cost savings. They also can increase compliance with regulations and other requirements.

Next-generation Wi-Fi (e.g., 802.11ah, HaLow): Next-generation Wi-Fi addresses the increasing need for connectivity related to the Internet of Things (IoT). IoT devices might need more than enterprise Wi-Fi and could require additional hardware, security, and management applications. Next-generation Wi-Fi such as 802.11ah operates at low frequency, offers longer range, requires less power, and allows many more devices to connect to a base station.

Private-cloud computing: Private-cloud computing refers to cloud infrastructure operating for a single institution and closed to other use. Some institutions have used virtualization technologies to run parts of their environments on private-cloud virtualized platforms.

Service-level reporting tools: Service-level reporting tools allow institutions to track and report on IT service delivery and management. They facilitate tasks and workflows associated with delivering IT services and track how well the delivery of services conforms to service-level commitments.

Software-defined networks: Software-defined networks (SDN) are an approach to designing, building, and operating networks that allow system administrators and network engineers to respond quickly to ever-changing network requirements and to optimize resources. SDNs may do for networks what virtualization has done for servers, allowing administrators to manage the network services in a simpler way and enabling network end users and applications to configure the network according to their needs.

Tools to support cross-institutional and international collaborations: Collaborating with colleagues beyond the institution is getting easier through a variety of options that include enterprise-level collaboration tools and free web-based tools. Enterprise tools offer more assurance of privacy and security through the institution's identity management system.

Uses of APIs: An API defines how a system interacts with other systems and how data can be shared and manipulated across programs. A good set of APIs is like building blocks that allow developers to more easily use data and technologies from various programs. APIs are used in many ways in higher education—for example, to pull data from the student information system into the learning management system, to integrate cloud-based with on-premises services, as an approach to security, and to access web-based resources.

Development tools to support multiple key platforms: Developers must program applications to run on a variety of mobile devices that use different operating systems. Design strategies include responsive web design, which provides an optimal experience across a wide range of devices. Development tools exist that aid cross-platform development.

High-precision location-sensing technologies: These technologies enable applications to use precise indoor location, allowing systems to know an individual's location to within a few meters. This precise sensing, combined with the Internet of Things and mobile apps, will make possible more-personalized services and information.

Mobile app development: Mobile app development is the organizational capability for the development of mobile applications. Organizations must make decisions about native apps for specific devices and mobile web development strategies. Issues of accessibility, security, data protection, and responsive web design also must be addressed when considering mobile app development.

Mobile apps for enterprise applications: Mobile apps for enterprise applications refers to web-based applications that run on mobile devices and are designed to integrate with all aspects of an organization's businesses and processes. These apps make it possible to access enterprise-wide resources (such as course catalogs, student information systems, and human resource systems) and conduct enterprise transactions from mobile devices.

Mobile device management: Mobile device management is the approach an institution takes for the policies, support, and procedures related to the variety of cell phones, tablets, and laptops on campus. Mobile device management involves a balance between the security of institutional data and user convenience and productivity. Some institutions use third-party products and services to manage mobile devices. Considerations include data security issues, support for personally owned equipment, and application management.

Cloud-based HPC: High-performance computing (HPC) requires substantial processing, high-speed connections, and parallel input/output. When HPC is provided by cloud vendors, additional characteristics typical of cloud are inherited: the ability to scale up and down quickly on demand in a pay-as-you-go environment.

Institutional repositories for research data: The management and curation of research data—including providing continued access to these data—is an important role for many institutions. In addition, publisher or grant-agency guidelines may require data to be in a repository. Institutional repositories help enable local, ongoing management and access, as well as serve as a place to host and share data where appropriate discipline-specific or national repositories are not available.

Science DMZ: Science DMZ provides a network-architecture approach that is optimized for high-performance scientific applications and the transfer of large research data sets over high-speed wide-area networks. It supports big-data movement by improving security, cost-effectiveness, and the nimble handling of large (mostly) scientific data sets. Science DMZ also addresses issues of systematic performance monitoring and file transfer and serves to simplify the use of software-defined networking (SDN) over wide-area network paths.

Tools to support cross-institutional and international research data-sharing: A core mission of higher education is research, and researchers are increasingly working with colleagues from other institutions and internationally. Understanding the issues of sharing research data with these colleagues is paramount for IT to provide the tools and support that enable this sharing. Tools in this space may address issues ranging from metadata to data access, usage rights, and file format interoperability.

Uses of the Internet of Things for research: The Internet of Things (IoT) continues to generate vast new amounts of data from a multitude of potentially intersecting IoT devices. Growth in this area will necessarily influence how research is conducted and identify new areas of research.

Applications of analytics to security (such as user behavioral analytics): The application of data-collection and sophisticated analytics within security tools and technologies enables IT organizations to quickly identify and respond to threats to institutional IT systems and data.

Cloud access security broker: A cloud access security broker (CASB) is a service that applies institutional security policies, such as authentication and authorization rules, to cloud-based resources. A CASB extends institutional information security policies and practices to the cloud-based services that the institution uses.

Cloud-based identity services (e.g., Duo, OneLogin, PortalGuard): Cloud-based identity services manage identification and authentication processes to IT systems or data. Authentication services ensure that only authorized individuals (or other systems) are permitted to access IT systems and data.

Cloud-based security services (e.g., Duo, Qualys ThreatPROTECT, cloud-based e-mail security solutions): These services are usually used in conjunction with on-premises services and tools to enhance an institution's information security posture.

Content-aware data loss prevention: Content-aware data loss prevention (DLP) tools enable the dynamic application of security policy based on the content and the context of data. These tools identify and protect sensitive data elements.

Database encryption: Database encryption is the process of encrypting data within a database so that the data are rendered unreadable without the decryption key. Often suggested as a way to protect sensitive data, database encryption can be costly and requires more storage space than a nonencrypted database.

DDoS prevention products and services: A distributed denial of service (DDoS) attack uses multiple systems to target a single IT system, swamping that system and preventing authorized users from accessing it. Various products and services can be used to protect institutions from DDoS attacks.

DNS security: Domain name systems/servers (DNS) translate textual domain names (such as educause.edu) to IP addresses. DNS security describes a suite of security specifications—such as DNS security extensions (DNSSEC), OpenDNS, or DNS-RPZ—for ensuring the integrity and authenticity of the institutional DNS.

End-to-end communications encryption: This type of encryption encrypts digital communication from the sender to receiver as it travels across communications networks.

Enterprise GRC systems: This refers to integrated IT applications that typically offer "modules" that help automate institutional governance, risk, and compliance (GRC) processes and reporting, such as managing the policy-development process, tracking legal requirements, monitoring and ensuring that compliance obligations are met, automating risk assessment exercises and tracking mitigation activities, and automating incident or issue tracking.

E-signature technologies (e.g., DocuSign, Adobe Sign, and SignNow): These technologies allow users to electronically sign documents to authenticate the identity of the signer.

Federated identity technologies: These technologies and standards are used to share identity information between organizations (or across security domains).

Next-generation firewalls: These firewalls incorporate application-level inspection, intrusion prevention, and intelligence from outside the firewall. They differ from stand-alone network-intrusion prevention systems.

Privacy-enhancing technologies (e.g., limited-disclosure technologies, anonymous credentials): Privacy-enhancing technologies and tools protect a user's personally identifiable information during online transactions.

SIEM (context-aware security): Security information and event management (SIEM) tools are used to gather security log data across multiple IT systems and present the data via a single interface for action.

Threat intelligence technologies: These services or tools generate and share cyber threat intelligence information with other tools and services (and institutions).

Blockchain: Blockchain is a public, distributed ledger of transactions maintained by a peer-to-peer network. Its most notable current use is to support value exchange with Bitcoin, but it has also been considered in the context of credentialing.

Cryptocurrencies (e.g., Bitcoin): Cryptocurrencies are digital currencies that use encryption technologies to control the creation and transfer of the units of currency. Bitcoin is a common example of a cryptocurrency.

Institutional support for speech recognition: Speech-recognition systems translate human speech into text or commands. Institutional support for such technologies may focus on straightforward educational applications (e.g., language learning) or improving accessibility for students who are blind or physically disabled or have learning disabilities.

Integration/uses of voice-user interfaces: Voice-user interfaces (VUIs) make possible human interaction with computers through a voice/speech platform in order to initiate an automated service or process. A VUI is the interface to any speech application.

Location-based computing: Location-based computing uses location data to deliver online content to users based on their physical location, using various technologies including GPS, cell phone infrastructure, and wireless access points.

Support for use of personal cloud services: Faculty, staff, and students may use personal cloud services such as Apple's iCloud or Google Drive instead of or in addition to institutionally supported storage services. Institutional support includes guidelines, education, and policies to ensure adequate information security.

Active learning classrooms: Active learning classrooms (ALCs) are student-centered, technology-rich learning environments designed on the principles of active pedagogical approaches. ALCs typically feature movable furniture, large displays, projectors, and other tools that support active learning.

Adaptive learning: Adaptive learning is one dimension of personalized learning, which aims to provide efficient, effective, and customized learning paths to engage individual learners. Adaptive learning technology dynamically adjusts to student interactions and performance levels, delivering content in an appropriate sequence that individual learners need in order to make progress.

Augmented and virtual reality for teaching and learning: Augmented reality (AR) superimposes graphics, video, text, or other content over a user's field of vision, layering digital content onto the real world. Virtual reality (VR) creates an immersive, 3D environment with which users can interact. These technologies can be used as an experience consumed by the learner or as a programming exercise in which learners create AR and VR experiences.

Courseware: Courseware is any digital curricular resource that contains a blend of content, study aids, and instructional expertise. Courseware is typically housed and delivered by a digital platform or application. Courseware's content is a direct descendent of the textbook, and study aids might include tools such as highlighting, commenting, and ways to interact with learners and instructors. Courseware that contains sophisticated instructional (or tutoring) capability is often called adaptive courseware or adaptive learning technology.

Digital microcredentials (including badging): A digital microcredential is like a mini-degree or certification that conveys information about a competency or skill related to a specific topic area. Digital microcredentials or digital badges can be issued by anyone and typically contain detailed metadata that communicate what the learner has learned or is able to do as a result of earning the credential.

Games and gamification: Gamification or game-based learning refers to the use of a pedagogical approach that utilizes gaming designs and principles but that is implemented within a nongame context, such as an instructional setting. Gamified learning environments are meant to support learner engagement and motivation, problem solving, critical thinking, and decision-making skills development.

Incorporation of mobile devices in teaching and learning: Mobile devices integrated into courses can be used for course assignments, field work, collaboration, and other activities. Such integration includes ensuring that course content functions well on mobile devices, as well as leveraging the unique capabilities of mobile devices for learning.

Next-generation LMS/digital learning environment: Next-generation learning environments replace conventional learning tools with a digital environment based on open standards that can be highly customized to support key learning functions such as analytics, collaboration, and universal design. Such environments are characterized by interoperability, personalization, collaboration, accessibility, and analytics.

Open educational resources: Open educational resources (OER) are freely accessible, openly licensed documents and media that may be useful for teaching, learning, assessing, and research. OER are used in various learning settings to include online, face-to-face, and blended, as well as structured learning environments such as college courses and self-paced, student-driven learning.

Remote proctoring services: Remote proctoring allows students to take an assessment at a remote location while ensuring the integrity of the exam. Online education, in particular, faces the challenge of conducting trustworthy assessments at a distance. The twin goals of all such systems are to ensure that people taking tests are the people they claim to be and that test-takers do not cheat during the exam.

Student success planning systems: Student success planning systems aggregate a broad range of academic, learning, financial, and other data, enabling personnel throughout the institution to collaborate in support of retention and completion.

Technologies for improving analysis of student data: These technologies enable immediate access to and rapid analysis of large, complex data sets, making it possible to discern trends in student engagement, in the types of difficulties students are encountering, and in the likelihood of success in attaining credentials across the student body.

Technologies for offering self-service resources that reduce advisor workloads: These platforms make tools such as online registration, scheduling, and academic planning available directly to students, enabling those with professional responsibilities for guiding students to reserve in-person appointments for higher-level interactions and counseling on individual issues.

Technologies for planning and mapping student educational plans: Educational planning tools allow students and advisors to work together to build customized pathways through the curriculum that are appropriate for each individual's interests and goals. In addition, these technologies offer a reliable way to chart and track progress toward a degree or credential. They also support institutions in the development of schedules that match demand.

Uses of the Internet of Things for teaching and learning: The Internet of Things (IoT) refers to the network of small, often everyday objects equipped with both computing and sensing capabilities, as well as the capacity to send and receive data via the Internet. The two dimensions of the curricular use of the IoT are as a way of providing learning data about student activities and as a source of student projects in disciplines such as computer science and engineering. The IoT may also be a domain of student extracurricular activity through makerspaces and related activities.