Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

DNS as Resolution Infrastructure for Persistent Identifiers


DOI: http://dx.doi.org/10.15439/2017F114

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 10851094 ()

Full text

Abstract. The concept of persistent identification is increasingly important for research data management. At the beginnings it was only considered as a persistent naming mechanism for research datasets, which is achieved by providing an abstraction for addresses of research datasets. However, recent developments in research data management have led persistent identification to move towards a concept which realizes a virtual global research data network. The base for this is the ability of persistent identifiers of holding semantical information about the identified dataset itself. Hence, community-specific representations of research datasets are mapped into globally common data structures provided by persistent identifiers. This ultimately enables a standardized data exchange between diverse scientific fields. Therefore, for the immense amount of research datasets, a robust and performant global resolution system is essential. However, for persistent identifiers the number of resolution systems is in comparison to the count of DNS resolvers extremely small. For the Handle System for instance, which is the most established persistent identifier system, there are currently only five globally distributed resolvers available. The fundamental idea of this work is therefore to enable persistent identifier resolution over DNS traffic. On the one side, this leads to a faster resolution of persistent identifiers. On the other side, this approach transforms the DNS system to a data dissemination system.


  1. H. V. de Sompel, R. Sanderson, H. Shankar, and M. Klein, “Persistent identifiers for scholarly assets and the web: The need for an unambiguous mapping,” IJDC, vol. 9, no. 1, jul 2014. http://dx.doi.org/10.2218/ijdc.v9i1.320
  2. T. Kuhn and M. Dumontier, “Making digital artifacts on the web verifiable and reliable,” IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 9, pp. 2390–2400, Sept 2015. http://dx.doi.org/10.1109/TKDE.2015.2419657
  3. E. Bellini, C. Luddi, C. Cirinnà, M. Lunghi, A. Felicetti, B. Bazzanella, and P. Bouquet, “Interoperability knowledge base for persistent identifiers interoperability framework,” in Signal Image Technology and Internet Based Systems (SITIS), 2012 Eighth International Conference on. IEEE, 2012. http://dx.doi.org/10.1109/SITIS.2012.130 pp. 868–875.
  4. T. Weigel, S. Kindermann, and M. Lautenschlager, “Actionable persistent identifier collections,” Data Science Journal, vol. 12, no. 0, pp. 191–206, 2014. http://dx.doi.org/10.2481/dsj.12-058
  5. A. Karakannas and Z. Zhao, “Information centric networking for delivering big data with persistent identifiers,” 2014.
  6. A. E. Evrard, C. Erdmann, J. Holmquist, J. Damon, and D. Dietrich, “Persistent, global identity for scientists via orcid,” arXiv preprint https://arxiv.org/abs/1502.06274, 2015.
  7. C. H. Liu, B. Yang, and T. Liu, “Efficient naming, addressing and profile services in internet-of-things sensory environments,” Ad Hoc Networks, vol. 18, pp. 85 – 101, 2014. doi: http://doi.org/10.1016/j.adhoc.2013.02.008
  8. F. Berber, P. Wieder, and R. Yahyapour, “A high-performance persistent identification concept,” 2016 IEEE International Conference on Networking, Architecture and Storage (NAS), vol. 00, pp. 1–10, 2016. http://dx.doi.org/10.1109/NAS.2016.7549387
  9. J. Jung, E. Sit, H. Balakrishnan, and R. Morris, “Dns performance and the effectiveness of caching,” IEEE/ACM Trans. Netw., vol. 10, no. 5, pp. 589–603, Oct. 2002. http://dx.doi.org/10.1109/TNET.2002.803905
  10. E. Cohen and H. Kaplan, “Proactive caching of dns records: Addressing a performance bottleneck,” Comput. Netw., vol. 41, no. 6, pp. 707–726, Apr. 2003. http://dx.doi.org/10.1016/S1389-1286(02)00424-3. [Online]. Available: http://dx.doi.org/10.1016/S1389-1286(02)00424-3
  11. Y. Yu, D. Wessels, M. Larson, and L. Zhang, “Authority server selection in dns caching resolvers,” SIGCOMM Comput. Commun. Rev., vol. 42, no. 2, pp. 80–86, Mar. 2012. http://dx.doi.org/10.1145/2185376.2185387. [Online]. Available: http://doi.acm.org/10.1145/2185376.2185387
  12. S. Sarat, V. Pappas, and A. Terzis, “On the use of anycast in dns,” in Proceedings of 15th International Conference on Computer Communications and Networks, Oct 2006. http://dx.doi.org/10.1109/ICCCN.2006.286248. ISSN 1095-2055 pp. 71–78.
  13. J. Pan, Y. T. Hou, and B. Li, “An overview of dns-based server selections in content distribution networks,” Comput. Netw., vol. 43, no. 6, pp. 695–711, Dec. 2003. http://dx.doi.org/10.1016/S1389-1286(03)00293-7
  14. A. J. Su, D. R. Choffnes, A. Kuzmanovic, and F. E. Bustamante, “Drafting behind akamai: Inferring network conditions based on cdn redirections,” IEEE/ACM Transactions on Networking, vol. 17, no. 6, pp. 1752–1765, Dec 2009. http://dx.doi.org/10.1109/TNET.2009.2022157
  15. “Doi handbook data model,” http://www.doi.org, accessed: 2017-03-23.
  16. “Dns resource record types,” http://www.iana.org/assignments/dns-parameters/dns-parameters.xhtml, accessed: 2017-04-04.
  17. “Handle software package,” http://www.handle.net/download hnr.html, accessed: 2017-03-31.
  18. “Dynamic delegation discovery system (ddds),” https://tools.ietf.org/html/rfc3401, accessed: 2017-11-23.
  19. “Dns txt resource record,” https://tools.ietf.org/html/rfc1464, accessed: 2017-04-06.
  20. “Handlednsresolver source code,” http://hdl.handle.net/11022/0000-0003-88B2-A, accessed: 2017-04-06.
  21. “Dona foundation,” http://www.dona.net, accessed: 2016-11-23.