Linking to Scientific Data: Identity Problems of Unruly and Poorly Bounded Digital Objects

Abstract

Within information systems, a significant aspect of search and retrieval across information objects, such as datasets, journal articles, or images, relies on the identity construction of the objects. This paper uses identity to refer to the qualities or characteristics of an information object that make it definable and recognizable, and can be used to distinguish it from other objects. Identity, in this context, can be seen as the foundation from which citations, metadata and identifiers are constructed.In recent years the idea of including datasets within the scientific record has been gaining significant momentum, with publishers, granting agencies and libraries engaging with the challenge. However, the task has been fraught with questions of best practice for establishing this infrastructure, especially in regards to how citations, metadata and identifiers should be constructed. These questions suggests a problem with how dataset identities are formed, such that an engagement with the definition of datasets as conceptual objects is warranted.This paper explores some of the ways in which scientific data is an unruly and poorly bounded object, and goes on to propose that in order for datasets to fulfill the roles expected for them, the following identity functions are essential for scholarly publications: (i) the dataset is constructed as a semantically and logically concrete object, (ii) the identity of the dataset is embedded, inherent and/or inseparable, (iii) the identity embodies a framework of authorship, rights and limitations, and (iv) the identity translates into an actionable mechanism for retrieval or reference.

Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data

“…However, this is not simply a problem of assigning identifiers or metadata. For the purposes of aggregation, computation, verification, reproducibility, and replicability, the data set must be defined so that it can be referenced in a way that yields a concrete search result (Wynholds, 2011).…”

“…As Borgman (2012b) notes, however, the dimensions of data identity are unsettled; there is not yet a clearly agreed upon set of dimensions for data identity, nor for the levels needed to read, interpret, combine, compute upon and trust data. Similarly, Wynholds (2011) states that data are currently "unruly and poorly bounded objects" within scholarly works, and Renear, Sacchi, and Wickett (2010) assert that "Although definitions of data sets do appear to fit a common pattern, with recurring phrases and semantically similar terms, it is clear that there is no single well-defined concept of data set" (p. 3).…”

“…Although the ability to cite data in some standard way is a building block of this infrastructure, data citation has yet to be broadly systematized or institutionally adopted, as discussed in Chapter 1. Complex challenges, both social and technical, have continued to impede the process (Wynholds, 2011).…”

Approaches to maintaining provenance throughout the additive manufacturing process

“…DIGITAL IDENTITY There is a general acceptance for the current signing principles and roles followed in the digital and physical domain, implementation of signing principles on additive manufacturing objects or 3D objects will contribute to digital identity using the uniqueness of the signed objects. Using the framework presented in Figure 2 we can establish digital identity by assigning a unique identifier to a data set using the signing data [20]. Currently unique identification numbers are assigned to physical object such as in packaging products, we can produce uniqueness in a 3D printed object by adding to signature to the 3D design rather than removing a part like in the case of watermarking 3D objects where the least significant bit is manipulated to imbed information [2].Our model insures the integrity of a 3D object because we do not remove from the object only add to it.…”

Data, data use, and scientific inquiry

“…Over the last decade we have been conducting interview and field studies to investigate scientific data practices in environmental sciences, marine biology, ecology, seismology, computer science, engineering, and astronomy [1,3,[14][15][16][17][18][19]. Portions of the studies included questions about how data were collected by individuals, teams, other parties.…”