The impact of ICT on systems biology and how to assess it

被引:0
作者
Petersen, Imme [1 ]
机构
[1] Univ Hamburg, Res Ctr Biotechnol Soc & Environm FSP BIOGUM, Lottestr 55, D-22529 Hamburg, Germany
关键词
systems biology; ICT; science assessment; technoscience; omics data; infrastructure; SCIENCE; INTEGRATION; HYPOTHESIS; TOOLS; STANDARDS; DATABASES; GENOMICS; FUTURE; ROLES; SENSE;
D O I
10.1080/13511610.2016.1197770
中图分类号
C91 [社会学];
学科分类号
030301 ; 1204 ;
摘要
The rise of systems biology has been deeply associated with the application of high-throughput technologies and the development of digital databases. Both have an important impact on how research is done today and what it achieves. The plethora and heterogeneity of data have caused a change in approaches of data handling and processing by using Information and Communication Technology (ICT). To facilitate data management and the access and sharing of data on biological structures and processes as well as to link different databases from disparate data sources, ICT infrastructures have been developed simultaneously with the emergence of systems approaches in biology. Using the concept of technoscience, I explore the relationship of data-driven technologies and scientific approaches in systems biology and how to assess it according to a new understanding of science assessment. The analysis shows that ICT infrastructures play an important role in the systems biology community, taking over all the relevant tasks regarding the integration, access and sharing of data. Therefore, ICT infrastructures are primarily regarded as service facilities to ease research activities. However, the separation of data management and data interpretation as two independent endeavours hides the fact that data-driven technologies fundamentally influence the epistemic status of data and cause epistemic shifts in research practices and processes. Accordingly, the frame of ICT for data management enables doing research, but it shapes the significance and meaning of data, practices and processes at the same time by defining how to handle data in ICT-driven science.
引用
收藏
页码:223 / 233
页数:11
相关论文
共 52 条
  • [1] Hypothesis, induction and background knowledge. Data do not speak for themselves. Replies to Donald A Gillies, Lawrence A Kelley and Michael Scott
    Allen, JF
    [J]. BIOESSAYS, 2001, 23 (09) : 861 - 862
  • [2] What's so special about model organisms?
    Ankeny, Rachel A.
    Leonelli, Sabina
    [J]. STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE, 2011, 42 (02): : 313 - 323
  • [3] [Anonymous], 2002, P ACM SIGACT SIGMOD, DOI DOI 10.1145/543613.543644
  • [4] [Anonymous], 1935, LOGIC SCI DISCOVERY
  • [5] From functional genomics to systems biology:: Concepts and practices
    Auffray, C
    Imbeaud, S
    Roux-Rouquié, M
    Hood, L
    [J]. COMPTES RENDUS BIOLOGIES, 2003, 326 (10-11) : 879 - 892
  • [6] Matters of Interest: The Objects of Research in Science and Technoscience
    Bensaude-Vincent, Bernadette
    Loeve, Sacha
    Nordmann, Alfred
    Schwarz, Astrid
    [J]. JOURNAL FOR GENERAL PHILOSOPHY OF SCIENCE, 2011, 42 (02) : 365 - 383
  • [7] Can computers help to explain biology?
    Brent, R
    Bruck, J
    [J]. NATURE, 2006, 440 (7083) : 416 - 417
  • [8] The ACGT project in retrospect: Lessons learned and future outlook
    Bucur, Anca
    Ruping, Stefan
    Sengstag, Thierry
    Sfakianakis, Stelios
    Tsiknakis, Manolis
    Wegener, Dennis
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE (ICCS), 2011, 4 : 1119 - 1128
  • [9] Clearing the standards landscape: the semantics of terminology and their impact on toxicogenomics
    Burgoon, Lyle D.
    [J]. TOXICOLOGICAL SCIENCES, 2007, 99 (02) : 403 - 412
  • [10] Burkhardt Hans., 1991, HDB METAPHYSICS ONTO