Improving Archaeologists’ Online Archive Experiences Through User-Centred Design

Traditionally, the preservation of archaeological data has been limited by the cost of materials and the physical space required to store them, but for the last 20 years, increasing amounts of digital data have been generated and stored online. New techniques in digital photography and document scanning have dramatically increased the amount of data that can be retained in digital format, while at the same time reducing the physical cost of production and storage. Vast numbers of hand written notes, grey literature documents, images of assemblages, contexts, and artefacts have been made available online. However, accessing these repositories is not always straightforward. Superficial interaction design, sparsely populated metadata, and heterogeneous schemas may prevent users from working the data that they need within archaeological archives. In this article, we present the work of the Digging into Archaeological Data and Image Search Metadata project (DADAISM), a multidisciplinary project that draws together the work of researchers from the fields of archaeology, interaction design, image processing and text mining to create an interactive system that supports archaeologists in their tasks in online archives. By adopting a user-centred approach with techniques grounded in contextual design, we identified the phases of archaeologists work in online archives, which are distinctive to this user group. The insights from this work drove the design and evaluation of an interactive system that successfully integrates content-based image based retrieval and improved metadata searching to deliver a positive user experience when working with online archives.

[1]  Maarten de Rijke,et al.  Aggregated search interface preferences in multi-session search tasks , 2013, SIGIR.

[2]  Gary Klein,et al.  Making Sense of Sensemaking 2: A Macrocognitive Model , 2006, IEEE Intelligent Systems.

[3]  P Kovesi,et al.  Phase congruency: A low-level image invariant , 2000, Psychological research.

[4]  Donghee Sinn.  Impact of digital archival collections on historical research , 2012, J. Assoc. Inf. Sci. Technol..

[5]  M. de Rijke,et al.  A subjunctive exploratory search interface to support media studies researchers , 2012, SIGIR '12.

[6]  Satoshi Sekine,et al.  A survey of named entity recognition and classification , 2007 .

[7]  Ryen W. White,et al.  Exploratory Search , 2008 .

[8]  A. Chalechale,et al.  Edge image description using angular radial partitioning , 2004 .

[9]  Michel Beaudouin-Lafon,et al.  Instrumental interaction: an interaction model for designing post-WIMP user interfaces , 2000, CHI.

[10]  Matti Pietikäinen,et al.  Robust Texture Classification by Subsets of Local Binary Patterns , 2000, ICPR.

[11]  Gary Klein,et al.  Making Sense of Sensemaking 1: Alternative Perspectives , 2006, IEEE Intelligent Systems.

[12]  Wendy E. Mackay,et al.  Reification, polymorphism and reuse: three principles for designing visual interfaces , 2000, AVI '00.

[13]  Michel Beaudouin-Lafon,et al.  Designing interaction, not interfaces , 2004, AVI.

[14]  Menno D. T. de Jong,et al.  Retrospective vs. concurrent think-aloud protocols: Testing the usability of an online library catalogue , 2003, Behav. Inf. Technol..

[15]  Diane Nahl,et al.  Composing Boolean Search Statements: Self-Confidence, Concept Analysis, Search Logic, and Errors. , 1996 .

[16]  Gary Marchionini,et al.  Exploratory search , 2006, Commun. ACM.

[17]  Noam Tractinsky,et al.  Assessing dimensions of perceived visual aesthetics of web sites , 2004 .

[18]  Alexander Serenko,et al.  Rigor and Relevance: The Application of The Critical Incident Technique to Investigate Email Usage , 2010, J. Organ. Comput. Electron. Commer..

[19]  Holtzblatt Karen,et al.  Contextual Inquiry: A Participatory Technique for System Design , 2017 .

[20]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  David Ellis,et al.  Modelling the information seeking patterns of engineers and research scientists in an industrial environment , 1997, J. Documentation.

[22]  M. de Rijke,et al.  Media studies research in the data‐driven age: How research questions evolve , 2016, J. Assoc. Inf. Sci. Technol..

[23]  Luis Salgado,et al.  Log-Gabor Filters for Image-Based Vehicle Verification , 2013, IEEE Transactions on Image Processing.

[24]  Karen Holtzblatt,et al.  Contextual design , 1997, INTR.

[25]  A. K. Lambers Posluschny.  To Whom it May Concern? The Users and Uses of Digital Archaeological Information , 2008 .

[26]  Mary Beth Rosson,et al.  Scenario-based design , 2002 .

[27]  Keith May,et al.  From the Slope of Enlightenment to the Plateau of Productivity: Developing Linked Data at the ADS , 2014 .

[28]  Stuart Jeffrey,et al.  Thinking Outside the Search Box : The Common Information Environment and Archaeobrowser , 2008 .

[29]  H. Rex Hartson,et al.  Remote evaluation for post-deployment usability improvement , 1998, AVI '98.

[30]  Jane You,et al.  Texture Classification by Texton: Statistical versus Binary , 2014, PloS one.

[31]  M Di Pierro.  web2py for Scientific Applications , 2011, Computing in Science & Engineering.

[32]  A. K. Lambers Posluschny.  Thinking Outside the Search Box: The Common Information Environment and Archaeobrowser , 2008 .

[33]  Akrivi Katifori,et al.  Historical research in archives: user methodology and supporting tools , 2010, International Journal on Digital Libraries.

[34]  Liming Chen,et al.  Image region description using orthogonal combination of local binary patterns enhanced with color information , 2013, Pattern Recognit..

[35]  Andrew McCallum,et al.  An Introduction to Conditional Random Fields for Relational Learning , 2007 .

[36]  Agma J. M. Traina,et al.  An Efficient Algorithm for Fractal Analysis of Textures , 2012, 2012 25th SIBGRAPI Conference on Graphics, Patterns and Images.

[37]  Joyce Celeste Chapman,et al.  Observing Users: An Empirical Analysis of User Interaction with Online Finding Aids , 2010 .

[38]  S Jeffrey,et al.  The Archaeotools project: faceted classification and natural language processing in an archaeological context , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.