Published March 26, 2020 | Version v1.0
Project deliverable Open

SSHOC D4.18 SSHOC Reference Ontology (beta version)

Description

This document serves as a beta (v 1.0) of the definition of the SSHOC Reference Ontology (SSHOCro). SSHOCro proposes an ontological model and RDF schema to be used as a top-level ontology for organizing knowledge and information found distributed across various primary sources of information in the Social Sciences and Humanities Open Cloud (SSHOC).

SSHOCro aspires to provide a semantic interoperability framework for the description of the SSHOC data lifecycle, by offering a conceptual model that can be used to (re)describe at a generic level the real-world lifecycle of creating, finding and using data –amongst other actions –as it actually takes place in the various domains of Social Sciences and Humanities. In practical terms, the use of such a model and schema for the research community is twofold: it can be applied as a standard to be used in the step of devising and implementing metadata capture scheme for tracking the data lifecycle in individual projects, institutions and disciplines; it can also be used to map, transform and integrate existing data across projects, institutions and disciplines into interoperable pools of information for reuse and exploitation. In this context, keeping track of the processes involved in the data lifecycle amounts to associating each stage to a set of activities performed in it.

The proposed ontology is based on the following considerations:

  1. Cultural and scientific data cannot be understood without knowledge about the meaning of the data and the ways and circumstances of their creation. This knowledge comprises the provenance of the data. It is essential to have metadata created for physical objects as well as for digital objects that bear cultural or scientific interest. Provenance is information about the origin, context, derivation, ownership, or history of some artifact. (Doerr & Theodoridou, 2011)
  2. Provenance of a resource is a record that describes entities and processes involved in producing and delivering or otherwise influencing that resource. Provenance provides a critical foundation for assessing authenticity, enabling trust, and allowing reproducibility. Provenance assertions are a form of contextual metadata and can themselves become important records with their own provenance. (W3C, 2011)
  3. The provenance metadata are actually data describing objects, people, places, times which are causally related by events while other relations are either deductions from events or found by observation events. (Doerr & Theodoridou, 2011)
  4. Provenance metadata are event centric and must be described in a historical order in order to ensure that there are no references to non-existent (non-recorded) events or objects. Generally, metadata is used to assess meaning (view, experimental setup, instrument settings), relevance (depicted objects, their status, their conditions), quality (calibration, tolerances, errors, artifacts) and possibilities of improvement and reprocessing. (Doerr & Theodoridou, 2011)
  5. Provenance has become even more critical in the web environment where data are sourced not only from established archives, but from many mixed credentialed providers. (Lagoze et al., 2013)
  6. There are a wide variety of data types and analytical techniques used within and across the disciplines and sub-disciplines that constitute the social sciences. (Playford et al., 2016)
  7. The social science & humanities research is a repetitive process of (i) formulating questions (ii) finding empirical evidence (iii) interpretation (inference, causation) (iv) verification in wider context (v) triggering new questions (Doerr et al., 2011)
  8. From a data processing point of view in the social science and humanities research there is a dominating “collection, connection, interpretation” pattern having 3 auxiliary activities concerning (i) the Persistent Storage, employing physical protected storage or electronic media and curation and access methods (ii) Publication and Presentation, employing, digital file or active database, sites and collections to be visited text, data, graphics, animation, Virtual Reality (iii) Information Selection, employing finding, retrieving, inspecting, and selecting actions

SSHOCro is modelled as an extension of CIDOC CRM, the ISO standard ontology for Cultural Heritage data, from which it inherits its event-centric orientation. CIDOC-CRM provides a common and extensible semantic framework that any procedural information can be mapped to. Instances of the CIDOC-CRM model can be merged into huge meaningful networks of knowledge about historical facts and contextual relationships (Doerr M., 2003) (ICOM/CIDOC- CRM SIG, 2019). The CIDOC-CRM model is intended to be a common language for domain experts and implementers to formulate requirements for information systems and to serve as a guide for good practice of conceptual modeling. In this way, it can provide the "semantic glue" needed to mediate between different sources of information, such as that published by museums, libraries and archives.

The SSHOCro is provided in RDF/S in the SSHOCro_v.1.0_beta.rdf, which is attached to this report.

Notes

Draft version - This is not yet accepted by the European Commission

Files

D4.18 SSHOC Reference Ontology (beta version) v1.0- report_26032020.pdf

Files (998.8 kB)

Additional details

Related works

Is supplemented by
Dataset: 10.5281/zenodo.3744926 (DOI)

Funding

SSHOC – Social Sciences & Humanities Open Cloud 823782
European Commission

References

  • Balafoutas, L. & Sutter, M. (2012). Affirmative action policies promote women and do not harm efficiency in the laboratory. Science 335, 579–582
  • Camerer C.F. et al. (2018). Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Open Science Framework. Retrieved February 25, 2020, from https://osf.io/pfdyw/
  • Bruseker G., Doerr M. & Theodoridou M. (2018). PARTHENOS D5.5 Report on the Common Semantic Framework. Available from Zenodo: https://zenodo.org/record/2575465#.XjQOamgzaUk
  • Corti L. & van den Eynden V. (2015). Learning to manage and share data: jump-starting the research methods curriculum, International Journal of Social Research Methodology, 18:5, 545-559
  • Doerr, M., Bekiari, Ch., Kritsotaki, A., & Hiebel, G.H, Theodoridou, M. (2014). Modelling Scientific Activities: Proposal for a global schema for integrating metadata about scientific observation. CIDOC - International Documentation Committee of ICOM: Conference 6th-11th Sept. 2014 in Dresden. Available from http://network.icom.museum/cidoc/archive/past-conferences/2014-dresden/