1. DATA FOUNDATION TERMINOLOGY WG 4 th Plenary Update THE PLUM GOALS This model together with the derived terminology can be used Across communities and stakeholders to better synchronize conceptualization To enable better understanding within and between communities and finally To stimulate tool building, such as for data services, supportive of the basic model's use OUTCOMES "Model overview" document summarizing about 20 models for data organization in use today "Model analysis & synthesis" document including an abstract data organization model derived from the above A "core set of terms and definitions" describing the abstract data model (snapshot of the ongoing discussion) Use Cases illustrating the applicability of the terminology to real-world situations TeD-T: Term Definition Tool at http://dft-tool.rd-alliance.org enabling and documenting the evolution and discussion of the terminology WG Chairs: Peter Wittenburg, Gary Berg-Cross, Raphael Ritz | Over 40 members of the WG. More information : https://rd-alliance.org/group/data-foundation-and-terminology-wg.html Reaping the Fruits, 22-24 Sept ‘14 The DFT WG task is to describe a basic, abstract data organization model which can be used to derive a reference data terminology.

2. DATA TYPE REGISTRIES WG 4 th Plenary Update THE PLUM Data sharing requires that data can be parsed, understood, and reused by people and applications other than those that created the data. The Data Type Registries Working Group is evaluating approaches based on use cases to define and allow registration of data types and subsequently enable resolution of those data types for consumption by humans and computer applications. Data types may be thought of as, for instance, a flexible extension to the notion of MIME types. GOALS To build a Data Type Registry that enables:  data producers and data managers to easily and consistently describe data structures, assumptions, and usage conventions in the form of data type records.  data consumers, including both humans and automated systems, to process and understand data with the help of registered data types. OUTCOMES  Design, implementation and release an open source version of the Registry software by CNRI. A few prototypes have been released to date (http://typeregistry.org/)  Multiple groups including the EUDAT project in Europe, NIST in the US, and the International DOI Foundation to put significant efforts into exercising the prototype or a variation of it.  The Registry designed as low-level infrastructure with wide applicability.  Potential establishment of multiple type registries. The current prototype is stand-alone, but the basic design allows for federation of distributed and separately administered registries.  Contribution to an evolving infrastructure connecting various RDA WG outcomes, e.g., it is a key component in the PID Information Types WG, as will be discussed in the Data Fabric IG. The working group, consisting of around 50 members, is nearing the end of its approved RDA timeline. The Data Type Registry, while it will specifically benefit data consumers, requires significant input from data production and management groups, e.g., those who create and manage specific data structures. Thus, participation from those people and organizations, in the form of data type registration, is needed to propel adoption and integration of the Data Type Registry concept into operational and research environments. The working group, consisting of around 50 members, is nearing the end of its approved RDA timeline. The Data Type Registry, while it will specifically benefit data consumers, requires significant input from data production and management groups, e.g., those who create and manage specific data structures. Thus, participation from those people and organizations, in the form of data type registration, is needed to propel adoption and integration of the Data Type Registry concept into operational and research environments. Reaping the RDA Fruits, September 10, 2015 Use cases include human interpretation of data, machine processing, finding data by type, connecting data to available processing services, characterizing the types of data in a given repository, assigning an existing and well- known type to newly collected data, and evaluating ingest data according to a type specification.

3. PID INFORMATION TYPES WG Reaping the RDA Fruits, September 10, 2015 4 th Plenary Update THE PLUM It is becoming increasingly necessary to automate tasks associated with research and scholarly communication infrastructures. Identifiers (PIDs) already provide key linkages among the individual entities managed within these infrastructures, but consistent methods of defining and exposing the properties associated with these entities have not yet emerged. The PID Information Types WG has addressed these challenges and produced practical outcomes ready for adoption. Chairs : Tobias Weigel, Tim DiLauro It is becoming increasingly necessary to automate tasks associated with research and scholarly communication infrastructures. Identifiers (PIDs) already provide key linkages among the individual entities managed within these infrastructures, but consistent methods of defining and exposing the properties associated with these entities have not yet emerged. The PID Information Types WG has addressed these challenges and produced practical outcomes ready for adoption. Chairs : Tobias Weigel, Tim DiLauro Goals:  Define information types; how they relate to digital objects and their PIDs and metadata; and how they can be stored, accessed and managed.  Determine how information types can be used in typical e-infrastructure workflows.  Develop the necessary tools to deal with the associated extra information on PIDs: an API and a conceptual framework giving structure to types, while providing scaffolding for future types as they emerge.  Present some first exemplary types that highlight practical usage scenarios for types in data management OUTCOMES The PIT WG has developed essential core types for information associated with PIDs, an accompanying conceptual architecture to organize these types and an application programming interface (API) to access and manage them.  The API is agnostic towards particular use cases; a higher level service, for example, might employ the API to determine whether it can provide its services for a given entity.  Providing such capabilities through the PID infrastructure would enable more performant, more comprehensive, and more manageable services, while reducing the overall cost of providing them. The outcomes support the future development of a coherent data fabric, in which PIDs can form an elemental access and management interface for digital objects independent from particular PID systems. PID Information Types aggregate essential state information for data objects and data collections and the harmonization effort will help to streamline development towards common interfaces. Using our results The PIT WG encourages RDA members interested in adopting the outputs and in future development to collaborate with PIT and its members. The outcomes are particularly relevant to PID providers and institutions providing e-infrastructure, archiving, and citation services.

4. PRACTICAL POLICY WG Reaping the RDA Fruits, September 10, 2015 4 th Plenary Update THE PLUM Computer actionable policies are used to enforce management, automate administrative tasks, validate assessment criteria, and automate scientific analyses. The Practical Policy Working Group assembles a collection of production and research policies, analyze the submitted policies to identify best practices, and promote the formation of policy-based data management systems. GOALS :  To bring together practitioners in policy making and policy implementation  To identify typical application scenarios for policies such as replication, preservation etc.  To collect and to register practical policies  To enable sharing, revising, adapting, and re-using of computer actionable policies OUTCOMES  a survey identified eleven generic policy areas of interest for the majority of the institutions and in common to almost all data management systems  templates for the production policies to be reported in the “Outcomes Policy Templates: Practical Policy Working Group, September 2014” document  a collection of example policies, their description (in English) to be included in the document “Implementations: Practical Policy Working Group, September 2014” Who ? Adopters and reviewers of the policy sets:  practitioners in policy making and policy implementation  data centers  communities building up data collections Who ? Adopters and reviewers of the policy sets:  practitioners in policy making and policy implementation  data centers  communities building up data collections