Gamification in Information Retrieval

My last article was mainly about Collaborative Information Seeking – one of the trends in enterprise search. Another interesting topic is the use of games’ mechanics in CIS systems. I met up with this idea during previously mentioned ESE 2014 conference, but interest is so high, that this year in Amsterdam a GamifIR (workshops on Gamification for Information Retrieval) took place. IR community have debated about what kind of benefits can IR tasks bring from games’ techniques. Workshops cover gamified task in context of searching, natural language processing, analyzing user behavior or collaborating. The last one was discussed in article titled “Enhancing Collaborative Search Systems Engagement Through Gamification” and has been mentioned by Martin White in his great presentation about search trends on last ESE summit.

Gamification is a concept which provides and uses game elements in non-game environment. Its goal is to improve customers or employees motivation for using some services. In the case of Information Retrieval it is e.g. encouraging people to find information in more efficient way. It is quite instinctive because competition is  an inherent part of human nature. Long time ago, business sectors have noticed that higher engagement, activating new users and establishing interaction between them, rewarding the effort of doing something lead to measurable results. Even if quality of data given by users could be higher. Among those elements can be included: leaderboards, levels, badges, achievements, time or resources limitation, challenges and many others. There are even described design patterns and models connected with gameplay, components, game practices and processes. Such rules are essential because virtual badge has no value until being assigned by user.

Collaborative Information Seeking is an idea suited for people cooperating on complex task which leads to find specific information. Systems like this support team work, coordinate actions and improve communication in many different ways and with usage of various mechanisms. At first glance it seems that gamification is perfect adopted to CIS projects. Seekers become more social, feeling of competence foster actions which in turn are rewarded.

The most important thing is to know why do we need gamified system and what kind of benefits we will get. Next step is to understand fundamental elements of a game and find out how adopt them to IR case. In their article “Enhancing Collaborative Search Systems Engagement Through Gamification”, researchers of Granada and Holguin universities have listed propositions how to gamify CIS system.  Based on their suggestions I think essential points are to prepare highly sociable environment for seekers. Every player (seeker) needs to have own personal profile which stores previous achievements and can be customized. Constant feedback on progress, list of successful members, time limitations, keeping the spirit of competition by all kinds of widgets are important for motivating and building a loyalty. Worth to remember that points collected after achieving goals need to be converted into virtual values which can distinguish the most active players. Crucial thing is to construct clear and fair principles, because often information seeking with such elements is a fun and it can’t be ruined.

Researchers from Finnish universities, who published article “Does Gamification Work?”, have broken down a problem of gamifying into components and have thoroughly studied them. Their conclusion was that concept of gamification can work, but there are some weaknesses – context which is going to be gamified and the quality of the users. Probably, the main problem is lack of knowledge which elements really provide benefits.

Gamification can be treated as a new way to deal with complex data structures. Limitations of data analyzing can be replaced by mechanism which increase activity of users in Information Retrieval process. Even more – such concept may leads to more higher quality data, because of increased people motivation. I believe, Collaborative Information Seeking, Gamification and similar ideas are one of the solutions how to improve search experience by helping people to become better searchers than not by just tuning up algorithms.

Enterprise Search Europe 2014 – Short Review

ESE Summit

At the end of April  a third edition of Enterprise Search Europe conference took place.  The venue was Park Plaza Victoria Hotel in London. Two-day event was dedicated to widely understood search solutions. There were two tracks covering subjects relating to search management, big data, open source technologies, SharePoint and as always –  the future of search. According to the organizer’ information, there were 30 experts presenting their knowledge and experience in implementation search systems and making content findable. It was  opportunity to get familiar with lots of case studies focused on relevancy, text mining, systems architecture and even matching business requirements. There were also speeches on softer skills, like making  decisions or finding good  employees.

In a word, ESE 2014 summit was great chance to meet highly skilled professionals with competence in business-driven search solutions. Representatives from both specialized consulting companies and universities were present there. Even second day started from compelling plenary session about the direction of enterprise search. Presentation contained two points of view: Jeff Fried, CTO in BA-Insight and Elaine Toms, Professor of Information Science, University of Sheffield. From industrial aspect analyzing user behavior,  applying world knowledge or improving information structure is a  real success. On the other hand, although IR systems are currently in mainstream, there are many problems: integration is still a challenge, systems working rules are unclear, organizations neglect investments in search specialists. As Elaine Toms explained, the role of scientists is to restrain an uncertainty by prototyping and forming future researchers. According to her, major search problems are primitive user interfaces and too few systems services. What is more, data and information often become of secondary importance, even though it’s a core of every search engine.

Trends

Despite of many interesting presentations, particularly one caught my attention. It was “Collaborative Search” by Martin White, Conference Chair and Managing Director in Intranet Focus. The subject was current condition of enterprise search and  requirements which such systems will have to face in the future. Martin White is convinced that limited users satisfaction is mainly fault of poor content quality and insufficient information management. Presentation covered  absorbing results of various researches. One of them, described in “Characterizing and Supporting Cross-Device Search Tasks” document, was analysis of commercial search engine logs in order to find behavior patterns associated with cross device searching. Switching between devices can be a hindrance because of device multiplicity. That is why each user needs to remember both what he was searching and what has already been found. Findings show that there are lots of opportunities to handle information seeking more effectively in multi-device world. Saving and re-instating user session, using time between switching devices to get more results or making use of behavioral, geospatial data to predict task resumption are just a few examples of ideas.

Despite everything, the most interesting part of Martin White’s presentation was dedicated to Collaborative Information Seeking (CIS).

Collaborative Information Seeking

It is natural that difficult and complex tasks forced people to work together. Collaboration in information retrieval helps to use systems more effectively. This idea concentrate on situations when people should cooperate to seek information or sense-make. In fact, CIS covers on the one hand elements connected with organizational behavior or making decision, on the other – evolution of user interface and designing systems of immediate data processing. Furthermore, Martin White considers CIS context to be focused around the complex queries, “second phase” queries, results evaluation or ranking algorithms. This concept is able to bring the highest values in the domains like chemistry, medicine and law.

During the CIS exploration some definitions appeared:  collaborative information retrieval, social searching, co-browsing, collaborative navigation, collaborative information behavior, collaborative information synthesis.  My intention is to introduce some of them.

"Collaborative Information Seeking", Chirag Shah

1. “Collaborative Information Seeking”, Chirag Shah

Collaborative Information Retrieval (CIR) extends traditional IR for the purposes of many users. It supports scenarios when problem is complicated and when seeking common information is a need. To support groups’ actions, it is crucial to know how they work, what are their strengths and weaknesses. In general, it might be said that such system could be an overlay on search engine re-ranking results, based on users community knowledge. In agreement with Chirag Shah, the author of “Collaborative Information Seeking” book, there are some examples of systems where workgroup’s queries and related results are captured and used to filtering more relevant information for particular user. One of the most absorbing case is SearchTogether – interface designed for collaborative web search, described by Meredith R. Morris and Eric Horvitz. It allows to work both synchronously and asynchronously. History of queries, page metadata and annotations serve as information carrier for user. There had been implemented an automatic and manual division of labor. One of its feature was recommending pages to another information seeker. All sessions and past findings were persisted and stored for future collaborative searching.

Despite of many efforts made in developing such systems, probably none of them has been widely adopted. Perhaps it was caused partly by its non-trivial nature, partly by lack of concept how to integrate them with other parts of collaboration in organizations.

Another ideas associated with CIS are Social Search and Collaborative Filtering. First one is about how social interactions could help in searching together. What is interesting,  despite of rather weak ties between people in social networks, their enhancement may be already observed in collaborative networks. Second definition referred to provide more relevant search results based on user past behavior, but also community of users displaying similar interests. It is noteworthy that it is an example of asynchronous interaction, because its value is based on past actions – in contrast with CIS where emphasis is laid to active users communication. Collaborative Filtering has been applied in many domains: industry, financial, insurance or web. At present the last one is most common and it’s used in e-commerce business. CF methods make a base for recommender systems predicting users preferences. It is so broad topic, that certainly deserves a separate article.

CIS Barriers

Regardless of all these researches, CIS is facing many challenges nowadays. One of them is information security in the company. How to struggle out of situation when team members do not have the same security profile or when some person cannot even share with others what has been found? Discussed systems cannot be only created for information seeking, but also they need to  provide managing security, support situations when results were not found because of permissions or situations when it is necessary to view a new document created in cooperation process. If it is not enough, there are various organization’s barriers hindering CIS idea. They are divided into categories – organizational, technical, individual, and team. They consist of things such as organization culture and structure, multiple and un-integrated systems, individual person perception or varied conflicts appeared during team work. Barriers and their implications have been described in detail in document “Barriers to Collaborative Information Seeking in Organizations” by Arvind Karunakaran and Madhu Reddy.

Collaborative information seeking is exciting field of research and one of the search trend. Another absorbing topic is gamification adopting in IR systems. This is going to be a subject of my next article.

Solving Diversity in Information Retrieval

How to solve diversity in information retrieval and techniques for handling ambiguous queries was a topic of interest at the SIGIR 2013 conference in Dublin, Ireland, which I attended recently.

The issue of Diversity in Information Retrieval was covered at a number of presentations at the conference. It is search engine independent, since it uses only the set of result documents as input. When applied to the world of search it basically means an aim to produce a search result that covers as many of the relevant topics as possible.

This is done by retrieving, say 100-500 documents, instead of the normal 10.
These documents are then clustered based on their contents to create a number
of topic clusters. The search result is then constructed by selecting
(the normal 10) documents from the clusters in a round-robin fashion. This will
hopefully create a diverse search result, with as broad coverage as possible.

The technique can not only be used to solve the problem of ambiguous queries,
but also queries with several sub-topics associated with it. By iteratively
running a clustering algorithm on the result documents with 2 to 5 (or so)
clusters and measuring the separation between them and choosing the outcome
with the greatest separation, a diverse result set of documents can be created.
The clusters can also be used to ask follow up questions to the user, where
he/she is allowed to click on one of several tag clouds, containing the most
central terms of each cluster.

A cluster set of size 2 with a good separation would indicate that the query
may be ambiguous, with two different semantics meanings, while a size of 3-5
likely means that the there are a number of sub topics identified in the
results. In a way these clusters can be seen as a dynamic facet, but it is
still shallow since it only operates on the returned documents. Yet, it does
not require any additional knowledge about the documents other than the
information that is returned. This could also be extended by using topic
labelling to present the user with a single term or phrase, instead of a tag
cloud.

Regarding the conference itself I found it to be a nice and professional arrangement with lots of in depth topics and nice evening activities, including a historical tour of Dublin.

Event related data – the buzz word at ECIR 2013

One of the major trends at the 35th annual European Conference on Information Retrieval was event related data. The conference took place between the 24th and 27th of March this year in a snowy Moscow, Russia. It attracted around 300 participants from all over the globe, 3 of them findwizards. While ECIR 2013 provided talks on a large variety of topics from across the field, event related data was definitely a buzz word.

The keynote speaker opening the second day of conference was Rutgers University assistant professor and Mahaya inc. CTO Mor Naaman. In his talk, Mr Naaman let the following image explain why Mahaya inc. are in business.

 rome-then-and-now

The past two papal elections.

The image above clearly shows that the way people act at events has changed considerably in the past few years, nowadays everyone is a reporter and their stories can be found on social media. Using platforms such as Twitter, Facebook and YouTube as data sources Naaman’s company creates products which not only extracts, but also synchronizes event coverage. One interesting feature in their latest product is the synchronization of video clips, making it possible for a user to easily switch view when watching video footage of for example a concert.  An arguably even stronger feature of this use of social media is the fact that news and event footage can reach the world even if no press is present at the scene. Slides from this inspiring talk can be found here.

Another presentation the same day displayed promising results in the task of automatic event detection. Using machine learning algorithms a team of researchers from Hanover, Germany have designed a system for detecting and summarizing entity related events from Wikipedia edit history data. Basically the idea is that when a Wikipedia article is edited by a large amount of users in a short period of time that can mark an important event considering the subject of the article. More information about this research can be found here.

The last day of the conference opened with a presentation from Jimmy Lin of Twitter. His talk centered on the importance of fast real-time indexing in social media platform architecture. One of the strengths of Twitter is presenting the users with information about events as they happen. As an example of this he used the event of an earthquake hitting eastern USA in 2011. Tweets from locations closer to the epicenter of the earthquake reached Twitter users in New York City before the actual quake did. I have to admit “Twitter, faster than earthquakes” is a pretty good slogan.

So whether it’s using social media data to let people (re)visit events, automatic event detection in open source dictionaries, making sure your indexing is fast enough to let your users cover events as they happen or something else, event based data seems to be one of the driving forces in the field of IR at the moment.

Query Rules in SharePoint 2013

Leaving both the SharePoint Conference in Las Vegas and the recent European SharePoint Conference in Copenhagen behind, Findwise continues sharing impressions about the new search in SharePoint 2013! We have previously given an overview of what is new in search in SharePoint 2013 and discussed Microsoft’s focus areas for the release. In this post, we focus more on the ranking of the search results using the query rules.

Understanding user intent in search is one of the key developments in the new release. The screenshots below, showing out-of-the-box functionality on some sample content, exemplify how the search engine adapts to the user query. Keywords such as ‘deck’, ‘expert’, or ‘video’ can express the user’s needs and expectations for different search results and information types, and what the search engine does in this case is promoting those results that have a higher probability to be relevant to the user’s search.

Query rules

Source: Microsoft

 

The adaptability of the search results can seem remarkable, as we see in these examples, aiming to provide more relevant search results through a better understanding of the user intent. Actually, this is powered by a new feature in SharePoint 2013 called query rules. Even more interesting maybe is that you can define your own custom query rules matching your specific needs without writing any code!

The simplest query rule would be to promote a specific result for a given search query. For example, you can promote a product’s instruction manual when the users search for that product name. Previously, in SharePoint 2010, you were able to define such promoted results (or “best bets”) using the Search Keywords. The query rules in SharePoint 2013 extend this functionality, providing an easy way to create powerful search experiences that adapt to user intent and business needs.

When defining a query rule, there are two main things to consider: conditions and corresponding actions. The conditions specify when the rule will be applied and the actions specify what to do when the rule is matched. There are six different condition types and three action types that can be defined.

For example, a query condition can be that a query keyword matches a specified phrase or a term from a dictionary (such as ‘picture’, ‘download’ or a product name from the term store), or that the query is more popular for a certain result type (such as images when for example searching for ‘cameras’), or that it matches a given regular expression (useful for matching phone numbers for example). The correlated actions can consist of promoting individual results on top of the ranked search results (promoting for example the image library), promoting a group of search results (such as image results, or search results federated from a web search engine), or changing the ranking of the search results by modifying the query (by changing the sorting of results or filtering on a content type). Another thing to consider is where you define the rule. Query rules can be created at Search Service Application, Site Collection, or Site level. The rules are inherited by default but you can remove, add, configure and change the order of query rules at each level. Fortunately, it also allows you to test a query and see which rules will fire.

There is one more thing though that you need to take into account: some features of query rules are limited in some of the licensing plans. Some plans only allow you to add the promoted results, and the more advanced actions on query rules are disabled. Check TechNet for guidelines on managing query rules and a list of features available across different licensing plans.

With the query rules, you have the freedom and power to change the search experience and adapt it to your needs. Defining the right keywords to be matched on the user queries and mapping the conditions with the relevant actions is easy but the process must undoubtedly be well managed. The management of the query rules should definitely be part of your SharePoint 2013 search governance strategy.

Let’s have a chat about how you can create great search experiences that match your specific users and business needs!

Presentation: Enterprise Search – Simple, Complex and Powerful

Every second, more and more information is created and stored in various applications. corporate websites, intranets, SharePoint sites, document management systems, social platforms and many more – inside the firewall the growth of information is similar to that of the internet. However, even though major players on the web have shown that navigation can’t compete with search, the Enterprise Search and Findability Report shows that most organisations have only a small or even a non-existing budget for search.

Web Search and Enterprise Search

Web search engines like Google has made search look easy. For enterprise search, some vendors give promises of a magic box. Buy a search engine, plug it in and wait for the magic to happen! Imagine the disappointment when both search results and performance are poor and users can’t find what they are looking for…

When you start planning your enterprise search project you soon realize the complexity and challenge – how do you meet the expectations created by Google?

The Presentation

This presentation was originally presented at the joint NSW KM Forum and IIM September event in Sydney, Australia by Mattias Brunnert. It contains topics as:

  • Why search is important and how to measure success
  • Why Enterprise Search and Information Management should be friends
  • How to kick off your search program

The Enterprise Search and Findability Report 2012 is ready

No strategy, no budget, no resources. This is the common scenario for enterprise search and findability in many organisations today. Still Enterprise Search is considered a critical success factor in 75% of organisations that responded to the global survey that ran from March to May this year.

The Enterprise Search and Findability Report 2012 is now ready for download.

The Enterprise Search and Findability report 2012 shows that 60% of the respondents expressed that it is very/moderately hard to find the right information. Only 11% stated that it is fairly easy to search for information and as few as 3% consider it very easy to find the desirable information. This shows that there still is a large untapped potential for any organisation to get great value from investing in enterprise search. For a relatively small investment, preferably in personnel it is possible to make search a lot better. The survey also reveals that  organisations who are very satisfied with their search, have a (larger) budget, more resources and systematically work with analysing search.

What is your primary goal for utilising search technology in your organisation?Figure. What is your primary goal for utilising search technology in your organisation?

The primary goal for using search is to accelerate retrieval of known information sources, 91%, and to improve the re-use of content (information/knowledge), 72%. This indicates that often search within organisations is used as a discovery tool for what already is known. If looking over the next three years, as many as 77% think that the amount of information in the organisation will increase. This means that every year it will be even more important be able to find the right information and that means Enterprise search is still very much needed, as stated in the following great presentations (on video):  Why Business Success Depends on Enterprise Search (by Martin White of Intranet Focus) and The Enterprise Search Market – What should be on your radar? (by Alan Pelz-Sharpe of 451 Research)

Download the full report.

A look at European Conference on Information Retrieval (ECIR) 2012

European Conference on Information Retrieval

The 34th European Conference on Information Retrieval was held  1-5 April 2011, in the lovely but crowded city of Barcelona, Spain. The core conference attracted over 100 attendees, with a total of 35 accepted full papers, 28 posters, and 7 demos being presented. As opposed to the previous year, which had 2 parallel sessions, this year’s conference included a single running session. The accepted papers covered a diverse range of topics, and were divided into query representation, blog and online-community search, semi-structured retrieval, applications, evaluation, retrieval models, classification, categorisation and clustering, image and video retrieval, and systems efficiency.

The best paper award went to Guido Zuccon, Leif Azzopardi, Dell Zhang and Jun Wang for their work entitled “Top-k Retrieval using Facility Location Analysis” and presented by Leif Azzopardi during the retrieval models session. The authors propose using facility location analysis taken from the discipline of operations research to address the top-k retrieval problem of finding “the optimal set of k documents from a number of relevant documents given the user’s query”.

Meanwhile, “Predicting IMDB Movie Ratings using Social Media” by Andrei Oghina, Mathias Breuss, Manos Tsagkias and Maarten de Rijke won the best poster award. With a different goal from the best paper, the authors of the poster experiment with a prediction model for rating movies using a set of qualitative and quantitative features extracted from the stream of two social media channels, YouTube and Twitter. Their findings show that the highest predictive performance is obtained by combining features from both channels, and propose as future work to include other social media channels.

Workshop Days

The conference was preceded by a full day of workshops and tutorials running in parallel. I attended two workshops: Information Retrieval Over Query Sessions (SIR) during the morning and Task-Based and Aggregated Search (TBAS) in the afternoon. The second workshop ended with an interactive discussion. A third, full-day workshop was Searching 4 Fun!.

Industry Day

The last day was the Industry Day. Only 2 papers here, plus 5 oral contributions, and around 50 attendees. A strong focus of the talks given at the industry day was on opinion-mining: four of the six participating companies/institutions presented work on sentiment analysis and opinion mining from social media streams. Jussi Karlgren, from Gavagai, argued that sentiment analysis from social media can be used by companies for example in finding reviews or comments made about their product or service, analyse their market position, and predict price movements. Rianne Kaptein, from Oxyme, backed this up by adding that businesses are interested by what the consumers say about their brand, products or campaigns on social media streams. Furthermore, Hugo Zaragoza from Websays identified two basic needs inside a company: a need for help in reading so that someone can act, and a need for help in explaining so that it can convince. Very interesting topic indeed, and research in this direction will advance as companies become more aware of the business gains from opinion mining of social media.

Overall, ECIR 2012 was a very inspiring conference. It also seemed a very friendly conference, offering many opportunities to network with the fellow attendees. Despite that, several participants said that the number of attendees at this year’s conference has decreased in comparison with previous years. The workshops and the core conference gave me the impression that it has a strong focus on young researchers, as many of the accepted contributions had a student as a first author and presenter at the conference. The fact that there was only one session running at a time was a good decision in my opinion, as the attendees were not forced to miss presentations. Nevertheless, the workshops and tutorials were running in parallel, and although the proceedings of the workshops will be made freely available, I still feel that I missed something that day. The industry day was very exciting, offering the opportunity to share ideas between academia and industry. However, there were not so many presentations, and the topics were not as diverse. I propose that next year Findwise will be among the speakers at the Industry track!

ECIR 2013 will be held in Moscow, Russia, between 24-28 March. See you there!

Mobile clients and Enterprise Search – What are the Implications?

As we all know the smartphone user base is growing explosively. According to www.statcounter.com, internet access from handheld mobile devices has doubled yearly since 2009 adding up to 8,5 % of all page views globally in January 2012. And mobile users want to be able to do all the same things that they are able to do on their PC. And that includes access to the company’s Enterprise Search solution!

The benefits of the sales force being able to search for vital customer information before a meeting or for field service personnel being able to find documentation quickly are quite obvious. So how can an organization tweak its search solution in order to provide convenient access for the mobile users? And above all, what will it cost?

Well, to answer the last question first: much less than you think. Providing for the mobile user is mainly about creating a new front end/UI. The main bulk of your search solution remains the same; indexing, metadata structure and content publishing, for instance, remain essentially unaffected.

But you do need to provide a quite different UI in order for the user interaction to work smoothly considering the specific characteristics of the mobile client primarily when it comes to screen size/resolution and text input. But the smartphone also has a lot of features that the PC lacks – it is always available and it knows exactly where you are, it always has a camera, microphone, speaker, possibly a magnetometer and accelerometer and of course a touchscreen with motions like pinching and swiping etc. And many of these features can be quite useful as the following examples prove:

Illustration 1. Google Mobile Voice Search on the iPhone. Courtesy of UX Matters, www.uxmatters.com

  • Google Mobile App for iPhone: in this app, the iPhone senses when the phone is lifted towards the ear and hence knows when to listen for a search command. Since the phone also knows where the user is, a search for “restaurant” automatically generates hits with restaurants in your vicinity.
  • Scanning a Barcode or QR-code: scanning a Barcode or QR-code with your phone is another way of entering a search string. An example could be a product in a store where the customer could open a price-search-engine and scan the QR-code of the product and see where the best price is.

As you can see, there are plenty of opportunities for those who want to be creative. But for the most part, the I/O will still be done via the screen. At UX Matters there is a great article by Greg Nudelman describing the considerations when implementing search for mobile clients and suggestions for various design patterns that can be efficient (see http://www.uxmatters.com/mt/archives/2010/04/design-patterns-for-mobile-faceted-search-part-i.php). I have included a brief summary below together with illustrations courtesy of UX Matters. But first, some general considerations for mobile clients:

  • Use Javascript code to detect what type of device is accessing your search solution and if it is a mobile client you display the mobile interface.
  • Native App or Mobile Web App: Creating a Mobile Web App is easier and cheaper than creating a native App – for one thing you don’t have to create multiple versions for different OS’s (although you still need to test your solution with different browsers/resolutions). Performance wise there isn’t a big difference between Native Apps and Web Apps and mobile browsers are increasingly gaining access to most of the phones hardware as well.
  • Authentication: SSO for mobile web applications works the same as for desktop browsers.  There are also new solutions currently being launched enabling usage of the company’s existing Active Directory infrastructure. One example is Centrify Directcontrol for Mobile enabling a centralized administration within Active Directory of all device security settings, profiles, certificates and restrictions.
  • Use HTML5 instead of FLASH: iPhones don’t support FLASH but HTML5 is a very capable alternative
  • Testing: How the design looks for different resolutions can be tested through various emulators but it is always recommendable to test on a limited set of real smartphones as well.
  • Access needs to be quick and simple: user interaction is more cumbersome on a phone than on a PC. Normally try to avoid solutions that require more than 3 input actions.
  • Menu navigation: links on the right side are normally used to drill down in the menu hierarchy and left up/towards the home screen
  • Gestures: is a very powerful toolbox that can be used in many different ways to create an efficient UI. For example, use “pinch to show more” if you want to expand the summary information of a specific item in the search hit list or “swipe” to expose the metadata (or whatever action you want to assign to that gesture).
  • Be creative: the mobile client is inherently different from a PC, limited in some ways but more powerful in others. So if you just try to adopt design solutions from the PC and fit them into a mobile UI you are missing out on a lot of powerful design solutions that only make sense on a mobile client and you are definitely not giving the users the best possible search experience. Also, since mobile design is still evolving you don’t need to be limited by conventions and expectations as much as on the PC side – make the most of this freedom to be creative!
  • W3C mobile: for more information about mobile web development, see http://www.w3.org/Mobile/ which also includes a validating scheme to assess the readiness of content for the mobile web

Design patterns for mobile UI (with courtesy of Greg Nudelman/UX Matters)

Mobile faceting can be tricky but by using design patterns like “4 Corners”, “Modal Overlays”, “Watermarks” and “Teaser Design” the UI can become both intuitive and easy to learn as well as providing reasonably powerful functionality. As mentioned, these techniques are summaries from an article written by Greg Nudelman for UX Matters. If you are eager to learn more, feel free to check out Greg’s website and his upcoming workshops focused on mobile design http://www.designcaffeine.com/category/workshops/

4 Corners: instead of stealing scarce real estate by adding faceting options directly on the screen together with the search result, semitransparent buttons are available in each corner enabling the user to bring up a faceting menu by tapping in a corner (see illustration 2).

Modal Overlays: the modal overlay is displayed on top of the original page. The modal overlay works well together with the 4 corners design – tapping a corner opens up the overlay containing faceting functions like filtering and sorting (see illustration 2).

Illustration 2. Four Corners and Modal Overlay patterns. Courtesy of UX Matters, www.uxmatters.com

Watermarks: a great technique for guiding users and showing the possibility of using new functions. The watermarks, possibly animated, show a symbol for the available action, for instance arrows indicating that a swiping gesture could be used (see illustration 3).

Full-Page Refinement Options Pattern: gives the user plenty of refinement options to choose from (see illustration 3).

Illustration 3. Two variations of the Watermark pattern and a Refinement Options pattern. Courtesy of UX Matters, www.uxmatters.com

Teaser Design: show part of the next available content so that the user is aware that there is more content available (see illustration 4).

Illustration 4. Teaser design pattern facilitates the discovery of faceted search filters. Courtesy of UX Matters, www.uxmatters.com

Persistent Status Bar: always maintain a persistent status bar containing the search string together with applied filters in the search result page. This helps the user maintain orientation. Note that all of the illustrations above have a persistent status bar.

Conclusion

Although Best Practices for mobile UI design are still evolving, plenty of progress has already been made and there are several solutions and design patterns to choose from depending on the specific circumstances at hand. So an implementation project need not be rocket science, as long as you learn the right tricks…

Bringing enterprise information to the field, readily available in a mobile handset or tablet, will mobilize your employees. The UI requires rethinking as we have seen. And security needs to be addressed properly to avoid having sensitive data compromised. But other than that, you are ready to go!